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Barbour SJ, Fervenza FC, Induruwage D, Brenchley PE, Rovin B, Hladunewich MA, Reich HN, Lafayette R, Aslam N, Appel GB, Zand L, Kiryluk K, Liu L, Cattran DC. Anti-PLA2R Antibody Levels and Clinical Risk Factors for Treatment Nonresponse in Membranous Nephropathy. Clin J Am Soc Nephrol 2023; 18:1283-1293. [PMID: 37471101 PMCID: PMC10578640 DOI: 10.2215/cjn.0000000000000237] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 07/12/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND The 2021 Kidney Disease Improving Global Outcomes (KDIGO) guidelines recommend following anti-phospholipase A2 receptor (PLA2R) antibody levels as a marker of treatment response in membranous nephropathy; however, the optimal timing to evaluate antibody levels and how to combine them with other clinical variables are currently unknown. METHODS We used a cohort of 85 patients from the Membranous Nephropathy Trial Of Rituximab (MENTOR) with anti-PLA2R antibodies ≥14 RU/ml to identify risk factors for not experiencing proteinuria remission after 12 months of treatment with cyclosporine or rituximab. Three landmark times were considered: at baseline and after 3 and 6 months of treatment. Logistic regression model performance was evaluated using C-statistics and model fit (Akaike information criterion [AIC], R 2 ). RESULTS The model at baseline that best predicted no remission included anti-PLA2R antibodies >323 RU/ml and creatinine clearance; the best model after 3 months included the change from baseline in both antibody and albumin levels; and the best model after 6 months included antibody levels >14 RU/ml, creatinine clearance, and the change from baseline in albumin. Compared with the model at baseline, the model at 3 months had better model fit (AIC 70.9 versus 96.4, R 2 51.8% versus 30.1%) and higher C-statistic (0.93 versus 0.83, P = 0.008). The model at 6 months had no difference in performance compared with the model at 3 months (AIC 68.6, R 2 53.0%, C-statistic 0.94, P = 0.67). CONCLUSIONS In patients with membranous nephropathy treated with cyclosporine or rituximab in the MENTOR trial, we found that the optimal method to evaluate risk factors for the probability of treatment response was to use anti-PLA2R antibody levels combined with albumin levels after 3 months of treatment, which was significantly better than using antibody levels alone or risk factor evaluation at baseline, with no added benefit of waiting until 6 months of treatment. PODCAST This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_10_09_CJN0000000000000237.mp3.
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Pividori M, Lu S, Li B, Su C, Johnson ME, Wei WQ, Feng Q, Namjou B, Kiryluk K, Kullo IJ, Luo Y, Sullivan BD, Voight BF, Skarke C, Ritchie MD, Grant SFA, Greene CS. Projecting genetic associations through gene expression patterns highlights disease etiology and drug mechanisms. Nat Commun 2023; 14:5562. [PMID: 37689782 PMCID: PMC10492839 DOI: 10.1038/s41467-023-41057-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Accepted: 08/18/2023] [Indexed: 09/11/2023] Open
Abstract
Genes act in concert with each other in specific contexts to perform their functions. Determining how these genes influence complex traits requires a mechanistic understanding of expression regulation across different conditions. It has been shown that this insight is critical for developing new therapies. Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Here we introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis. This representation is based on modules of genes with similar expression patterns across the same conditions. We observe that diseases are significantly associated with gene modules expressed in relevant cell types, and our approach is accurate in predicting known drug-disease pairs and inferring mechanisms of action. Furthermore, using a CRISPR screen to analyze lipid regulation, we find that functionally important players lack associations but are prioritized in trait-associated modules by PhenoPLIER. By incorporating groups of co-expressed genes, PhenoPLIER can contextualize genetic associations and reveal potential targets missed by single-gene strategies.
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Menon R, Otto EA, Barisoni L, Melo Ferreira R, Limonte CP, Godfrey B, Eichinger F, Nair V, Naik AS, Subramanian L, D'Agati V, Henderson JM, Herlitz L, Kiryluk K, Moledina DG, Moeckel GW, Palevsky PM, Parikh CR, Randhawa P, Rosas SE, Rosenberg AZ, Stillman I, Toto R, Torrealba J, Vazquez MA, Waikar SS, Alpers CE, Nelson RG, Eadon MT, Kretzler M, Hodgin JB. Defining the molecular correlate of arteriolar hyalinosis in kidney disease progression by integration of single cell transcriptomic analysis and pathology scoring. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.14.23291150. [PMID: 37398386 PMCID: PMC10312894 DOI: 10.1101/2023.06.14.23291150] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Arteriolar hyalinosis in kidneys is an independent predictor of cardiovascular disease, the main cause of mortality in chronic kidney disease (CKD). The underlying molecular mechanisms of protein accumulation in the subendothelial space are not well understood. Using single cell transcriptomic data and whole slide images from kidney biopsies of patients with CKD and acute kidney injury in the Kidney Precision Medicine Project, the molecular signals associated with arteriolar hyalinosis were evaluated. Co-expression network analysis of the endothelial genes yielded three gene set modules as significantly associated with arteriolar hyalinosis. Pathway analysis of these modules showed enrichment of transforming growth factor beta / bone morphogenetic protein (TGFβ / BMP) and vascular endothelial growth factor (VEGF) signaling pathways in the endothelial cell signatures. Ligand-receptor analysis identified multiple integrins and cell adhesion receptors as over-expressed in arteriolar hyalinosis, suggesting a potential role of integrin-mediated TGFβ signaling. Further analysis of arteriolar hyalinosis associated endothelial module genes identified focal segmental glomerular sclerosis as an enriched term. On validation in gene expression profiles from the Nephrotic Syndrome Study Network cohort, one of the three modules was significantly associated with the composite endpoint (> 40% reduction in estimated glomerular filtration rate (eGFR) or kidney failure) independent of age, sex, race, and baseline eGFR, suggesting poor prognosis with elevated expression of genes in this module. Thus, integration of structural and single cell molecular features yielded biologically relevant gene sets, signaling pathways and ligand-receptor interactions, underlying arteriolar hyalinosis and putative targets for therapeutic intervention.
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Gupta Y, Friedman DJ, McNulty M, Khan A, Lane B, Wang C, Ke J, Jin G, Wooden B, Knob AL, Lim TY, Appel GB, Huggins K, Liu L, Mitrotti A, Stangl MC, Bomback A, Westland R, Bodria M, Marasa M, Shang N, Cohen DJ, Crew RJ, Morello W, Canetta P, Radhakrishnan J, Martino J, Liu Q, Chung WK, Espinoza A, Luo Y, Wei WQ, Feng Q, Weng C, Fang Y, Kullo IJ, Naderian M, Limdi N, Irvin MR, Tiwari H, Mohan S, Rao M, Dube G, Chaudhary NS, Gutiérrez OM, Judd SE, Cushman M, Lange LA, Lange EM, Bivona DL, Verbitsky M, Winkler CA, Kopp JB, Santoriello D, Batal I, Brant Pinheiro SV, Araújo Oliveira E, E Silva ACS, Pisani I, Fiaccadori E, Lin F, Gesualdo L, Amoroso A, Ghiggeri GM, D'Agati VD, Magistroni R, Kenny EE, Loos RJF, Montini G, Hildebrandt F, Paul DS, Petrovski S, Goldstein DB, Kretzler M, Gbadegesin R, Gharavi AG, Kiryluk K, Sampson MG, Pollak MR, Sanna-Cherchi S. Strong protective effect of the APOL1 p.N264K variant against G2-associated focal segmental glomerulosclerosis and kidney disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.02.23293554. [PMID: 37577628 PMCID: PMC10418582 DOI: 10.1101/2023.08.02.23293554] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Black Americans have a significantly higher risk of developing chronic kidney disease (CKD), especially focal segmental glomerulosclerosis (FSGS), than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of Black Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1 -associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.
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Kiryluk K, Freedberg DE, Radhakrishnan J, Segall L, Jacobson JS, Mathur M, Mohan S, Neugut AI. Global Incidence of IgA Nephropathy by Race and Ethnicity: A Systematic Review. KIDNEY360 2023; 4:1112-1122. [PMID: 37227924 PMCID: PMC10476677 DOI: 10.34067/kid.0000000000000165] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 05/08/2023] [Indexed: 05/27/2023]
Abstract
Key Points In 16 studies conducted abroad, IgA nephropathy incidence varied from 0.06 in South Africa to 4.2 per 100,000 in Japan. Globally, the incidence of IgA nephropathy seemed higher in Asians than in non-Asians and higher in male patients than in female patients. Five studies conducted in the United States found no consistent difference in incidence between Black patients and White patients. Background The reported incidence of IgA nephropathy varies widely across studies and may vary on the basis of race/ethnicity. This study systematically reviewed the incidence of IgA nephropathy in the United States and other countries and explored variability on the basis of the racial/ethnic composition and other demographic characteristics of different populations. Methods This was a systematic review. Studies were eligible for inclusion if they contained data collected from January 1, 1974, to December 31, 2021, and reported IgA nephropathy incidence at a population level (i.e. , cases of IgA nephropathy per 100,000 population). Results Five US and 16 international studies were included; three of the US studies reported the race-specific incidence of IgA nephropathy. In the United States, the reported incidence of IgA nephropathy ranged from 0.39 per 100,000 in Tennessee to 1.4 per 100,000 in Minnesota; internationally, IgA nephropathy ranged from 0.06 per 100,000 in South Africa to 4.2 per 100,000 in Japan. Findings regarding the incidence of IgA nephropathy in the United States by race were inconsistent: One study found a higher incidence among White patients compared with Black patients, one study found a lower incidence in White patients, and one study found no difference. Globally, the incidence of IgA nephropathy seemed to be higher in Asian than in non-Asian populations and higher in male patients than in female patients. Conclusions Reported incidence of IgA nephropathy varies widely; there is no consensus regarding the relationship between race and IgA nephropathy. Incidence rates seemed to be higher in Asians than non-Asians and in male patients than female patients. We recommend that future studies should report IgA nephropathy incidence rates by race/ethnicity and account for the demographic characteristics of the background population.
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Bhatraju PK, Stanaway IB, Palmer MR, Menon R, Schaub JA, Menez S, Srivastava A, Wilson FP, Kiryluk K, Palevsky PM, Naik AS, Sakr SS, Jarvik GP, Parikh CR, Ware LB, Ikizler TA, Siew ED, Chinchilli VM, Coca SG, Garg AX, Go AS, Kaufman JS, Kimmel PL, Himmelfarb J, Wurfel MM. Genome-wide Association Study for AKI. KIDNEY360 2023; 4:870-880. [PMID: 37273234 PMCID: PMC10371295 DOI: 10.34067/kid.0000000000000175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 04/03/2023] [Indexed: 06/06/2023]
Abstract
Key Points Two genetic variants in the DISP1-TLR5 gene locus were associated with risk of AKI. DISP1 and TLR5 were differentially regulated in kidney biopsy tissue from patients with AKI compared with no AKI. Background Although common genetic risks for CKD are well established, genetic factors influencing risk for AKI in hospitalized patients are poorly understood. Methods We conducted a genome-wide association study in 1369 participants in the Assessment, Serial Evaluation, and Subsequent Sequelae of AKI Study; a multiethnic population of hospitalized participants with and without AKI matched on demographics, comorbidities, and kidney function before hospitalization. We then completed functional annotation of top-performing variants for AKI using single-cell RNA sequencing data from kidney biopsies in 12 patients with AKI and 18 healthy living donors from the Kidney Precision Medicine Project. Results No genome-wide significant associations with AKI risk were found in Assessment, Serial Evaluation, and Subsequent Sequelae of AKI (P < 5×10 −8 ). The top two variants with the strongest association with AKI mapped to the dispatched resistance-nodulation-division (RND) transporter family member 1 (DISP1) gene and toll-like receptor 5 (TLR5) gene locus, rs17538288 (odds ratio, 1.55; 95% confidence interval, 1.32 to 182; P = 9.47×10 −8 ) and rs7546189 (odds ratio, 1.53; 95% confidence interval, 1.30 to 1.81; P = 4.60×10 −7 ). In comparison with kidney tissue from healthy living donors, kidney biopsies in patients with AKI showed differential DISP1 expression in proximal tubular epithelial cells (adjusted P = 3.9× 10−2) and thick ascending limb of the loop of Henle (adjusted P = 8.7× 10−3) and differential TLR5 gene expression in thick ascending limb of the loop of Henle (adjusted P = 4.9× 10−30). Conclusions AKI is a heterogeneous clinical syndrome with various underlying risk factors, etiologies, and pathophysiology that may limit the identification of genetic variants. Although no variants reached genome-wide significance, we report two variants in the intergenic region between DISP1 and TLR5 , suggesting this region as a novel risk for AKI susceptibility.
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Spotnitz M, Acharya N, Cimino JJ, Murphy S, Namjou B, Crimmins N, Walunas T, Liu C, Crosslin D, Benoit B, Rosenthal E, Pacheco JA, Ostropolets A, Reyes Nieva H, Patterson JS, Richter LR, Callahan TJ, Elhussein A, Pang C, Kiryluk K, Nestor J, Khan A, Mohan S, Minty E, Chung W, Wei WQ, Natarajan K, Weng C. A metadata framework for computational phenotypes. JAMIA Open 2023; 6:ooad032. [PMID: 37181728 PMCID: PMC10168627 DOI: 10.1093/jamiaopen/ooad032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/10/2023] [Accepted: 04/21/2023] [Indexed: 05/16/2023] Open
Abstract
With the burgeoning development of computational phenotypes, it is increasingly difficult to identify the right phenotype for the right tasks. This study uses a mixed-methods approach to develop and evaluate a novel metadata framework for retrieval of and reusing computational phenotypes. Twenty active phenotyping researchers from 2 large research networks, Electronic Medical Records and Genomics and Observational Health Data Sciences and Informatics, were recruited to suggest metadata elements. Once consensus was reached on 39 metadata elements, 47 new researchers were surveyed to evaluate the utility of the metadata framework. The survey consisted of 5-Likert multiple-choice questions and open-ended questions. Two more researchers were asked to use the metadata framework to annotate 8 type-2 diabetes mellitus phenotypes. More than 90% of the survey respondents rated metadata elements regarding phenotype definition and validation methods and metrics positively with a score of 4 or 5. Both researchers completed annotation of each phenotype within 60 min. Our thematic analysis of the narrative feedback indicates that the metadata framework was effective in capturing rich and explicit descriptions and enabling the search for phenotypes, compliance with data standards, and comprehensive validation metrics. Current limitations were its complexity for data collection and the entailed human costs.
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Lake BB, Menon R, Winfree S, Hu Q, Melo Ferreira R, Kalhor K, Barwinska D, Otto EA, Ferkowicz M, Diep D, Plongthongkum N, Knoten A, Urata S, Mariani LH, Naik AS, Eddy S, Zhang B, Wu Y, Salamon D, Williams JC, Wang X, Balderrama KS, Hoover PJ, Murray E, Marshall JL, Noel T, Vijayan A, Hartman A, Chen F, Waikar SS, Rosas SE, Wilson FP, Palevsky PM, Kiryluk K, Sedor JR, Toto RD, Parikh CR, Kim EH, Satija R, Greka A, Macosko EZ, Kharchenko PV, Gaut JP, Hodgin JB, Eadon MT, Dagher PC, El-Achkar TM, Zhang K, Kretzler M, Jain S. An atlas of healthy and injured cell states and niches in the human kidney. Nature 2023; 619:585-594. [PMID: 37468583 PMCID: PMC10356613 DOI: 10.1038/s41586-023-05769-3] [Citation(s) in RCA: 124] [Impact Index Per Article: 124.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 01/30/2023] [Indexed: 07/21/2023]
Abstract
Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.
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Kiryluk K, Sanchez-Rodriguez E, Zhou XJ, Zanoni F, Liu L, Mladkova N, Khan A, Marasa M, Zhang JY, Balderes O, Sanna-Cherchi S, Bomback AS, Canetta PA, Appel GB, Radhakrishnan J, Trimarchi H, Sprangers B, Cattran DC, Reich H, Pei Y, Ravani P, Galesic K, Maixnerova D, Tesar V, Stengel B, Metzger M, Canaud G, Maillard N, Berthoux F, Berthelot L, Pillebout E, Monteiro R, Nelson R, Wyatt RJ, Smoyer W, Mahan J, Samhar AA, Hidalgo G, Quiroga A, Weng P, Sreedharan R, Selewski D, Davis K, Kallash M, Vasylyeva TL, Rheault M, Chishti A, Ranch D, Wenderfer SE, Samsonov D, Claes DJ, Akchurin O, Goumenos D, Stangou M, Nagy J, Kovacs T, Fiaccadori E, Amoroso A, Barlassina C, Cusi D, Del Vecchio L, Battaglia GG, Bodria M, Boer E, Bono L, Boscutti G, Caridi G, Lugani F, Ghiggeri G, Coppo R, Peruzzi L, Esposito V, Esposito C, Feriozzi S, Polci R, Frasca G, Galliani M, Garozzo M, Mitrotti A, Gesualdo L, Granata S, Zaza G, Londrino F, Magistroni R, Pisani I, Magnano A, Marcantoni C, Messa P, Mignani R, Pani A, Ponticelli C, Roccatello D, Salvadori M, Salvi E, Santoro D, Gembillo G, Savoldi S, Spotti D, Zamboli P, Izzi C, Alberici F, Delbarba E, Florczak M, Krata N, Mucha K, Pączek L, Niemczyk S, Moszczuk B, Pańczyk-Tomaszewska M, Mizerska-Wasiak M, Perkowska-Ptasińska A, Bączkowska T, Durlik M, Pawlaczyk K, Sikora P, Zaniew M, Kaminska D, Krajewska M, Kuzmiuk-Glembin I, Heleniak Z, Bullo-Piontecka B, Liberek T, Dębska-Slizien A, Hryszko T, Materna-Kiryluk A, Miklaszewska M, Szczepańska M, Dyga K, Machura E, Siniewicz-Luzeńczyk K, Pawlak-Bratkowska M, Tkaczyk M, Runowski D, Kwella N, Drożdż D, Habura I, Kronenberg F, Prikhodina L, van Heel D, Fontaine B, Cotsapas C, Wijmenga C, Franke A, Annese V, Gregersen PK, Parameswaran S, Weirauch M, Kottyan L, Harley JB, Suzuki H, Narita I, Goto S, Lee H, Kim DK, Kim YS, Park JH, Cho B, Choi M, Van Wijk A, Huerta A, Ars E, Ballarin J, Lundberg S, Vogt B, Mani LY, Caliskan Y, Barratt J, Abeygunaratne T, Kalra PA, Gale DP, Panzer U, Rauen T, Floege J, Schlosser P, Ekici AB, Eckardt KU, Chen N, Xie J, Lifton RP, Loos RJF, Kenny EE, Ionita-Laza I, Köttgen A, Julian BA, Novak J, Scolari F, Zhang H, Gharavi AG. Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for IgA nephropathy. Nat Genet 2023; 55:1091-1105. [PMID: 37337107 DOI: 10.1038/s41588-023-01422-x] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 05/05/2023] [Indexed: 06/21/2023]
Abstract
IgA nephropathy (IgAN) is a progressive form of kidney disease defined by glomerular deposition of IgA. Here we performed a genome-wide association study of 10,146 kidney-biopsy-diagnosed IgAN cases and 28,751 controls across 17 international cohorts. We defined 30 genome-wide significant risk loci explaining 11% of disease risk. A total of 16 loci were new, including TNFSF4/TNFSF18, REL, CD28, PF4V1, LY86, LYN, ANXA3, TNFSF8/TNFSF15, REEP3, ZMIZ1, OVOL1/RELA, ETS1, IGH, IRF8, TNFRSF13B and FCAR. The risk loci were enriched in gene orthologs causing abnormal IgA levels when genetically manipulated in mice. We also observed a positive genetic correlation between IgAN and serum IgA levels. High polygenic score for IgAN was associated with earlier onset of kidney failure. In a comprehensive functional annotation analysis of candidate causal genes, we observed convergence of biological candidates on a common set of inflammatory signaling pathways and cytokine ligand-receptor pairs, prioritizing potential new drug targets.
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Gisch DL, Brennan M, Lake BB, Basta J, Keller M, Ferreira RM, Akilesh S, Ghag R, Lu C, Cheng YH, Collins KS, Parikh SV, Rovin BH, Robbins L, Conklin KY, Diep D, Zhang B, Knoten A, Barwinska D, Asghari M, Sabo AR, Ferkowicz MJ, Sutton TA, Kelly KJ, Boer IHD, Rosas SE, Kiryluk K, Hodgin JB, Alakwaa F, Jefferson N, Gaut JP, Gehlenborg N, Phillips CL, El-Achkar TM, Dagher PC, Hato T, Zhang K, Himmelfarb J, Kretzler M, Mollah S, Jain S, Rauchman M, Eadon MT. The chromatin landscape of healthy and injured cell types in the human kidney. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.543965. [PMID: 37333123 PMCID: PMC10274789 DOI: 10.1101/2023.06.07.543965] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. However, comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measured dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We established a comprehensive and spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we noted distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3 , KLF6 , and KLF10 regulated the transition between health and injury, while in thick ascending limb cells this transition was regulated by NR2F1 . Further, combined perturbation of ELF3 , KLF6 , and KLF10 distinguished two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.
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Lennon NJ, Kottyan LC, Kachulis C, Abul-Husn N, Arias J, Belbin G, Below JE, Berndt S, Chung W, Cimino JJ, Clayton EW, Connolly JJ, Crosslin D, Dikilitas O, Velez Edwards DR, Feng Q, Fisher M, Freimuth R, Ge T, Glessner JT, Gordon A, Guiducci C, Hakonarson H, Harden M, Harr M, Hirschhorn J, Hoggart C, Hsu L, Irvin R, Jarvik GP, Karlson EW, Khan A, Khera A, Kiryluk K, Kullo I, Larkin K, Limdi N, Linder JE, Loos R, Luo Y, Malolepsza E, Manolio T, Martin LJ, McCarthy L, Meigs JB, Mersha TB, Mosley J, Namjou B, Pai N, Pesce LL, Peters U, Peterson J, Prows CA, Puckelwartz MJ, Rehm H, Roden D, Rosenthal EA, Rowley R, Sawicki KT, Schaid D, Schmidlen T, Smit R, Smith J, Smoller JW, Thomas M, Tiwari H, Toledo D, Vaitinadin NS, Veenstra D, Walunas T, Wang Z, Wei WQ, Weng C, Wiesner G, Xianyong Y, Kenny E. Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.25.23290535. [PMID: 37333246 PMCID: PMC10275001 DOI: 10.1101/2023.05.25.23290535] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE's experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings.
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Yang Z, Wang C, Liu L, Khan A, Lee A, Vardarajan B, Mayeux R, Kiryluk K, Ionita-Laza I. CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses. Nat Genet 2023; 55:1057-1065. [PMID: 37169873 DOI: 10.1038/s41588-023-01392-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 04/11/2023] [Indexed: 05/13/2023]
Abstract
Fine-mapping is commonly used to identify putative causal variants at genome-wide significant loci. Here we propose a Bayesian model for fine-mapping that has several advantages over existing methods, including flexible specification of the prior distribution of effect sizes, joint modeling of summary statistics and functional annotations and accounting for discrepancies between summary statistics and external linkage disequilibrium in meta-analyses. Using simulations, we compare performance with commonly used fine-mapping methods and show that the proposed model has higher power and lower false discovery rate (FDR) when including functional annotations, and higher power, lower FDR and higher coverage for credible sets in meta-analyses. We further illustrate our approach by applying it to a meta-analysis of Alzheimer's disease genome-wide association studies where we prioritize putatively causal variants and genes.
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Ahram DF, Lim TY, Ke J, Jin G, Verbitsky M, Bodria M, Kil BH, Chatterjee D, Piva SE, Marasa M, Zhang JY, Cocchi E, Caridi G, Gucev Z, Lozanovski VJ, Pisani I, Izzi C, Savoldi G, Gnutti B, Capone VP, Morello W, Guarino S, Esposito P, Lambert S, Radhakrishnan J, Appel GB, Uy NS, Rao MK, Canetta PA, Bomback AS, Nestor JG, Hays T, Cohen DJ, Finale C, van Wijk JA, La Scola C, Baraldi O, Tondolo F, Di Renzo D, Jamry-Dziurla A, Pezzutto A, Manca V, Mitrotti A, Santoro D, Conti G, Martino M, Giordano M, Gesualdo L, Zibar L, Masnata G, Bonomini M, Alberti D, La Manna G, Caliskan Y, Ranghino A, Marzuillo P, Kiryluk K, Krzemień G, Miklaszewska M, Lin F, Montini G, Scolari F, Fiaccadori E, Arapović A, Saraga M, McKiernan J, Alam S, Zaniew M, Szczepańska M, Szmigielska A, Sikora P, Drożdż D, Mizerska-Wasiak M, Mane S, Lifton RP, Tasic V, Latos-Bielenska A, Gharavi AG, Ghiggeri GM, Materna-Kiryluk A, Westland R, Sanna-Cherchi S. Rare Single Nucleotide and Copy Number Variants and the Etiology of Congenital Obstructive Uropathy: Implications for Genetic Diagnosis. J Am Soc Nephrol 2023; 34:1105-1119. [PMID: 36995132 PMCID: PMC10278788 DOI: 10.1681/asn.0000000000000132] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 01/18/2023] [Indexed: 03/31/2023] Open
Abstract
SIGNIFICANCE STATEMENT Congenital obstructive uropathy (COU) is a prevalent human developmental defect with highly heterogeneous clinical presentations and outcomes. Genetics may refine diagnosis, prognosis, and treatment, but the genomic architecture of COU is largely unknown. Comprehensive genomic screening study of 733 cases with three distinct COU subphenotypes revealed disease etiology in 10.0% of them. We detected no significant differences in the overall diagnostic yield among COU subphenotypes, with characteristic variable expressivity of several mutant genes. Our findings therefore may legitimize a genetic first diagnostic approach for COU, especially when burdening clinical and imaging characterization is not complete or available. BACKGROUND Congenital obstructive uropathy (COU) is a common cause of developmental defects of the urinary tract, with heterogeneous clinical presentation and outcome. Genetic analysis has the potential to elucidate the underlying diagnosis and help risk stratification. METHODS We performed a comprehensive genomic screen of 733 independent COU cases, which consisted of individuals with ureteropelvic junction obstruction ( n =321), ureterovesical junction obstruction/congenital megaureter ( n =178), and COU not otherwise specified (COU-NOS; n =234). RESULTS We identified pathogenic single nucleotide variants (SNVs) in 53 (7.2%) cases and genomic disorders (GDs) in 23 (3.1%) cases. We detected no significant differences in the overall diagnostic yield between COU sub-phenotypes, and pathogenic SNVs in several genes were associated to any of the three categories. Hence, although COU may appear phenotypically heterogeneous, COU phenotypes are likely to share common molecular bases. On the other hand, mutations in TNXB were more often identified in COU-NOS cases, demonstrating the diagnostic challenge in discriminating COU from hydronephrosis secondary to vesicoureteral reflux, particularly when diagnostic imaging is incomplete. Pathogenic SNVs in only six genes were found in more than one individual, supporting high genetic heterogeneity. Finally, convergence between data on SNVs and GDs suggest MYH11 as a dosage-sensitive gene possibly correlating with severity of COU. CONCLUSIONS We established a genomic diagnosis in 10.0% of COU individuals. The findings underscore the urgent need to identify novel genetic susceptibility factors to COU to better define the natural history of the remaining 90% of cases without a molecular diagnosis.
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Khan A, Shang N, Nestor JG, Weng C, Hripcsak G, Harris PC, Gharavi AG, Kiryluk K. Polygenic risk affects the penetrance of monogenic kidney disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.07.23289614. [PMID: 37214819 PMCID: PMC10197721 DOI: 10.1101/2023.05.07.23289614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Background Chronic kidney disease (CKD) is a genetically complex disease determined by an interplay of monogenic, polygenic, and environmental risks. Most forms of monogenic kidney diseases have incomplete penetrance and variable expressivity. It is presently unknown if some of the variability in penetrance can be attributed to polygenic factors. Methods Using the UK Biobank (N=469,835 participants) and the All of Us (N=98,622 participants) datasets, we examined two most common forms of monogenic kidney disorders, autosomal dominant polycystic kidney disease (ADPKD) caused by deleterious variants in the PKD1 or PKD2 genes, and COL4A-associated nephropathy (COL4A-AN caused by deleterious variants in COL4A3, COL4A4, or COL4A5 genes). We used the eMERGE-III electronic CKD phenotype to define cases (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 or kidney failure) and controls (eGFR >90 mL/min/1.73m2 in the absence of kidney disease diagnoses). The effects of the genome-wide polygenic score (GPS) for CKD were tested in monogenic variant carriers and non-carriers using logistic regression controlling for age, sex, diabetes, and genetic ancestry. Results As expected, the carriers of known pathogenic and rare predicted loss-of-function variants in PKD1 or PKD2 had a high risk of CKD (ORmeta=17.1, 95% CI: 11.1-26.4, P=1.8E-37). The GPS was comparably predictive of CKD in both ADPKD variant carriers (ORmeta=2.28 per SD, 95%CI: 1.55-3.37, P=2.6E-05) and non-carriers (ORmeta=1.72 per SD, 95% CI=1.69-1.76, P< E-300) independent of age, sex, diabetes, and genetic ancestry. Compared to the middle tertile of the GPS distribution for non-carriers, ADPKD variant carriers in the top tertile had a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile had only a 3-fold increased risk of CKD. Similarly, the GPS was predictive of CKD in both COL4-AN variant carriers (ORmeta=1.78, 95% CI=1.22-2.58, P=2.38E-03) and non-carriers (ORmeta=1.70, 95%CI: 1.68-1.73 P Conclusions Variable penetrance of kidney disease in ADPKD and COL4-AN is partially explained by differences in polygenic risk profiles. Accounting for polygenic factors has the potential to improve risk stratification in monogenic kidney disease and may have implications for genetic counseling.
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Elliott MD, Marasa M, Cocchi E, Vena N, Zhang JY, Khan A, Krishna Murthy S, Bheda S, Milo Rasouly H, Povysil G, Kiryluk K, Gharavi AG. Clinical and Genetic Characteristics of CKD Patients with High-Risk APOL1 Genotypes. J Am Soc Nephrol 2023; 34:909-919. [PMID: 36758113 PMCID: PMC10125632 DOI: 10.1681/asn.0000000000000094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/04/2023] [Indexed: 02/11/2023] Open
Abstract
SIGNIFICANCE STATEMENT APOL1 high-risk genotypes confer a significant risk of kidney disease, but variability in patient outcomes suggests the presence of modifiers of the APOL1 effect. We show that a diverse population of CKD patients with high-risk APOL1 genotypes have an increased lifetime risk of kidney failure and higher eGFR decline rates, with a graded risk among specific high-risk genotypes. CKD patients with high-risk APOL1 genotypes have a lower diagnostic yield for monogenic kidney disease. Exome sequencing revealed enrichment of rare missense variants within the inflammasome pathway modifying the effect of APOL1 risk genotypes, which may explain some clinical heterogeneity. BACKGROUND APOL1 genotype has significant effects on kidney disease development and progression that vary among specific causes of kidney disease, suggesting the presence of effect modifiers. METHODS We assessed the risk of kidney failure and the eGFR decline rate in patients with CKD carrying high-risk ( N =239) and genetically matched low-risk ( N =1187) APOL1 genotypes. Exome sequencing revealed monogenic kidney diseases. Exome-wide association studies and gene-based and gene set-based collapsing analyses evaluated genetic modifiers of the effect of APOL1 genotype on CKD. RESULTS Compared with genetic ancestry-matched patients with CKD with low-risk APOL1 genotypes, those with high-risk APOL1 genotypes had a higher risk of kidney failure (Hazard Ratio [HR]=1.58), a higher decline in eGFR (6.55 versus 3.63 ml/min/1.73 m 2 /yr), and were younger at time of kidney failure (45.1 versus 53.6 years), with the G1/G1 genotype demonstrating the highest risk. The rate for monogenic kidney disorders was lower among patients with CKD with high-risk APOL1 genotypes (2.5%) compared with those with low-risk genotypes (6.7%). Gene set analysis identified an enrichment of rare missense variants in the inflammasome pathway in individuals with high-risk APOL1 genotypes and CKD (odds ratio=1.90). CONCLUSIONS In this genetically matched cohort, high-risk APOL1 genotypes were associated with an increased risk of kidney failure and eGFR decline rate, with a graded risk between specific high-risk genotypes and a lower rate of monogenic kidney disease. Rare missense variants in the inflammasome pathway may act as genetic modifiers of APOL1 effect on kidney disease.
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Barry A, McNulty MT, Jia X, Gupta Y, Debiec H, Luo Y, Nagano C, Horinouchi T, Jung S, Colucci M, Ahram DF, Mitrotti A, Sinha A, Teeninga N, Jin G, Shril S, Caridi G, Bodria M, Lim TY, Westland R, Zanoni F, Marasa M, Turudic D, Giordano M, Gesualdo L, Magistroni R, Pisani I, Fiaccadori E, Reiterova J, Maringhini S, Morello W, Montini G, Weng PL, Scolari F, Saraga M, Tasic V, Santoro D, van Wijk JAE, Milošević D, Kawai Y, Kiryluk K, Pollak MR, Gharavi A, Lin F, Simœs E Silva AC, Loos RJF, Kenny EE, Schreuder MF, Zurowska A, Dossier C, Ariceta G, Drozynska-Duklas M, Hogan J, Jankauskiene A, Hildebrandt F, Prikhodina L, Song K, Bagga A, Cheong H, Ghiggeri GM, Vachvanichsanong P, Nozu K, Lee D, Vivarelli M, Raychaudhuri S, Tokunaga K, Sanna-Cherchi S, Ronco P, Iijima K, Sampson MG. Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome. Nat Commun 2023; 14:2481. [PMID: 37120605 PMCID: PMC10148875 DOI: 10.1038/s41467-023-37985-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 04/10/2023] [Indexed: 05/01/2023] Open
Abstract
Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional independent risk loci. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. Here, we conduct a multi-population GWAS meta-analysis in 38,463 participants (2440 cases). We then conduct conditional analyses and population specific GWAS. We discover twelve significant associations-eight from the multi-population meta-analysis (four novel), two from the multi-population conditional analysis (one novel), and two additional novel loci from the European meta-analysis. Fine-mapping implicates specific amino acid haplotypes in HLA-DQA1 and HLA-DQB1 driving the HLA Class II risk locus. Non-HLA loci colocalize with eQTLs of monocytes and numerous T-cell subsets in independent datasets. Colocalization with kidney eQTLs is lacking but overlap with kidney cell open chromatin suggests an uncharacterized disease mechanism in kidney cells. A polygenic risk score (PRS) associates with earlier disease onset. Altogether, these discoveries expand our knowledge of pSSNS genetic architecture across populations and provide cell-specific insights into its molecular drivers. Evaluating these associations in additional cohorts will refine our understanding of population specificity, heterogeneity, and clinical and molecular associations.
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Linder JE, Allworth A, Bland HT, Caraballo PJ, Chisholm RL, Clayton EW, Crosslin DR, Dikilitas O, DiVietro A, Esplin ED, Forman S, Freimuth RR, Gordon AS, Green R, Harden MV, Holm IA, Jarvik GP, Karlson EW, Labrecque S, Lennon NJ, Limdi NA, Mittendorf KF, Murphy SN, Orlando L, Prows CA, Rasmussen LV, Rasmussen-Torvik L, Rowley R, Sawicki KT, Schmidlen T, Terek S, Veenstra D, Velez Edwards DR, Absher D, Abul-Husn NS, Alsip J, Bangash H, Beasley M, Below JE, Berner ES, Booth J, Chung WK, Cimino JJ, Connolly J, Davis P, Devine B, Fullerton SM, Guiducci C, Habrat ML, Hain H, Hakonarson H, Harr M, Haverfield E, Hernandez V, Hoell C, Horike-Pyne M, Hripcsak G, Irvin MR, Kachulis C, Karavite D, Kenny EE, Khan A, Kiryluk K, Korf B, Kottyan L, Kullo IJ, Larkin K, Liu C, Malolepsza E, Manolio TA, May T, McNally EM, Mentch F, Miller A, Mooney SD, Murali P, Mutai B, Muthu N, Namjou B, Perez EF, Puckelwartz MJ, Rakhra-Burris T, Roden DM, Rosenthal EA, Saadatagah S, Sabatello M, Schaid DJ, Schultz B, Seabolt L, Shaibi GQ, Sharp RR, Shirts B, Smith ME, Smoller JW, Sterling R, Suckiel SA, Thayer J, Tiwari HK, Trinidad SB, Walunas T, Wei WQ, Wells QS, Weng C, Wiesner GL, Wiley K, Peterson JF. Returning integrated genomic risk and clinical recommendations: The eMERGE study. Genet Med 2023; 25:100006. [PMID: 36621880 PMCID: PMC10085845 DOI: 10.1016/j.gim.2023.100006] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 12/16/2022] [Accepted: 12/21/2022] [Indexed: 01/09/2023] Open
Abstract
PURPOSE Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.
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Verbitsky M, Krishnamurthy S, Krithivasan P, Hughes D, Khan A, Marasà M, Vena N, Khosla P, Zhang J, Lim TY, Glessner JT, Weng C, Shang N, Shen Y, Hripcsak G, Hakonarson H, Ionita-Laza I, Levy B, Kenny EE, Loos RJ, Kiryluk K, Sanna-Cherchi S, Crosslin DR, Furth S, Warady BA, Igo RP, Iyengar SK, Wong CS, Parsa A, Feldman HI, Gharavi AG. Genomic Disorders in CKD across the Lifespan. J Am Soc Nephrol 2023; 34:607-618. [PMID: 36302597 PMCID: PMC10103259 DOI: 10.1681/asn.2022060725] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 09/15/2022] [Indexed: 01/24/2023] Open
Abstract
SIGNIFICANCE STATEMENT Pathogenic structural genetic variants, also known as genomic disorders, have been associated with pediatric CKD. This study extends those results across the lifespan, with genomic disorders enriched in both pediatric and adult patients compared with controls. In the Chronic Renal Insufficiency Cohort study, genomic disorders were also associated with lower serum Mg, lower educational performance, and a higher risk of death. A phenome-wide association study confirmed the link between kidney disease and genomic disorders in an unbiased way. Systematic detection of genomic disorders can provide a molecular diagnosis and refine prediction of risk and prognosis. BACKGROUND Genomic disorders (GDs) are associated with many comorbid outcomes, including CKD. Identification of GDs has diagnostic utility. METHODS We examined the prevalence of GDs among participants in the Chronic Kidney Disease in Children (CKiD) cohort II ( n =248), Chronic Renal Insufficiency Cohort (CRIC) study ( n =3375), Columbia University CKD Biobank (CU-CKD; n =1986), and the Family Investigation of Nephropathy and Diabetes (FIND; n =1318) compared with 30,746 controls. We also performed a phenome-wide association analysis (PheWAS) of GDs in the electronic MEdical Records and GEnomics (eMERGE; n =11,146) cohort. RESULTS We found nine out of 248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72 out of 6679 (1.1%) adult patients with CKD in the CRIC, CU-CKD, and FIND cohorts, compared with 199 out of 30,746 (0.65%) GDs in controls (OR, 1.7; 95% CI, 1.3 to 2.2). Among adults with CKD, we found recurrent GDs at the 1q21.1, 16p11.2, 17q12, and 22q11.2 loci. The 17q12 GD (diagnostic of renal cyst and diabetes syndrome) was most frequent, present in 1:252 patients with CKD and diabetes. In the PheWAS, dialysis and neuropsychiatric phenotypes were the top associations with GDs. In CRIC participants, GDs were associated with lower serum magnesium, lower educational achievement, and higher mortality risk. CONCLUSION Undiagnosed GDs are detected both in children and adults with CKD. Identification of GDs in these patients can enable a precise genetic diagnosis, inform prognosis, and help stratify risk in clinical studies. GDs could also provide a molecular explanation for nephropathy and comorbidities, such as poorer neurocognition for a subset of patients.
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Jones AC, Patki A, Srinivasasainagendra V, Armstrong ND, Chaudhary NS, Hidalgo B, Tiwari HK, Limdi N, Arnett DK, Lange L, Lange E, Kiryluk K, Khan A, Irvin MM. Abstract MP19: An eGFR Polygenic Score Predicts Chronic Kidney Disease in African Americans. Circulation 2023. [DOI: 10.1161/circ.147.suppl_1.mp19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
Chronic kidney disease (CKD) is a risk factor for cardiovascular disease and early death. Genetic factors contribute to CKD, and recently, polygenic scores (PGS) have been developed to quantify risk for complex diseases, such as CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PGS development overall; moreover, European-ancestry derived PGSs demonstrate diminished predictive performance in African ancestry populations. This study aimed to develop a PGS for CKD using genotype and phenotype data from African American (AA) participants of observational cohort studies. We obtained score weights from a meta-analysis of genome-wide association studies (GWAS) for estimated glomerular filtration rate (eGFR) in the Million Veteran Program (MVP) and Reasons for Geographical and Racial Differences in Stroke (REGARDS) Study (total n~66,000). We then optimized the PGS in a cohort of AAs from the Hypertension Genetic Epidemiology Network (HyperGEN) Study (n~1,900) using the
PRS-CS
software and evaluated the predictive performance of the PGS at multiple global shrinkage parameters. We further adjusted the PGS for
APOL1
risk status. In HyperGEN, the eGFR-based PGS was significantly associated with the odds of prevalent CKD—defined as baseline eGFR <60 mL/min/1.73m
2
— in logistic regression models adjusted for age, sex, and population structure. Further, accounting for
APOL1
risk status—a putative variant for CKD unique to those of sub-Saharan African descent—improved the score’s accuracy, with the
APOL1
-adjusted PGS explaining 1.9% (1.1% without
APOL1
) of the variance in CKD and an area under the curve (AUC) of 58.9% [95% CI: 53.0%-64.9%] (without
APOL1
, 58.2% [95% CI: 52.3%-64.1%]). Sensitivity analyses and validation in external cohorts, as well as comparisons to previously published PGS, are ongoing. In this study, we developed a PGS that was significantly associated with CKD with improved predictive accuracy in AAs over previously published PGS.
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Ma S, Wang C, Khan A, Liu L, Dalgleish J, Kiryluk K, He Z, Ionita-Laza I. BIGKnock: fine-mapping gene-based associations via knockoff analysis of biobank-scale data. Genome Biol 2023; 24:24. [PMID: 36782330 PMCID: PMC9926792 DOI: 10.1186/s13059-023-02864-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 01/23/2023] [Indexed: 02/15/2023] Open
Abstract
We propose BIGKnock (BIobank-scale Gene-based association test via Knockoffs), a computationally efficient gene-based testing approach for biobank-scale data, that leverages long-range chromatin interaction data, and performs conditional genome-wide testing via knockoffs. BIGKnock can prioritize causal genes over proxy associations at a locus. We apply BIGKnock to the UK Biobank data with 405,296 participants for multiple binary and quantitative traits, and show that relative to conventional gene-based tests, BIGKnock produces smaller sets of significant genes that contain the causal gene(s) with high probability. We further illustrate its ability to pinpoint potential causal genes at [Formula: see text] of the associated loci.
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Liu L, Khan A, Sanchez-Rodriguez E, Zanoni F, Li Y, Steers N, Balderes O, Zhang J, Krithivasan P, LeDesma RA, Fischman C, Hebbring SJ, Harley JB, Moncrieffe H, Kottyan LC, Namjou-Khales B, Walunas TL, Knevel R, Raychaudhuri S, Karlson EW, Denny JC, Stanaway IB, Crosslin D, Rauen T, Floege J, Eitner F, Moldoveanu Z, Reily C, Knoppova B, Hall S, Sheff JT, Julian BA, Wyatt RJ, Suzuki H, Xie J, Chen N, Zhou X, Zhang H, Hammarström L, Viktorin A, Magnusson PKE, Shang N, Hripcsak G, Weng C, Rundek T, Elkind MSV, Oelsner EC, Barr RG, Ionita-Laza I, Novak J, Gharavi AG, Kiryluk K. Author Correction: Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits. Nat Commun 2023; 14:655. [PMID: 36746961 PMCID: PMC9902387 DOI: 10.1038/s41467-023-36340-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
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Pacheco JA, Rasmussen LV, Wiley K, Person TN, Cronkite DJ, Sohn S, Murphy S, Gundelach JH, Gainer V, Castro VM, Liu C, Mentch F, Lingren T, Sundaresan AS, Eickelberg G, Willis V, Furmanchuk A, Patel R, Carrell DS, Deng Y, Walton N, Satterfield BA, Kullo IJ, Dikilitas O, Smith JC, Peterson JF, Shang N, Kiryluk K, Ni Y, Li Y, Nadkarni GN, Rosenthal EA, Walunas TL, Williams MS, Karlson EW, Linder JE, Luo Y, Weng C, Wei W. Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network. Sci Rep 2023; 13:1971. [PMID: 36737471 PMCID: PMC9898520 DOI: 10.1038/s41598-023-27481-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 01/03/2023] [Indexed: 02/05/2023] Open
Abstract
The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations.
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Devuyst O, Kiryluk K. On the way to translate GWAS into kidney disease mechanisms. Kidney Int 2023; 103:16-18. [PMID: 36309125 DOI: 10.1016/j.kint.2022.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 10/19/2022] [Indexed: 11/06/2022]
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Liu L, Khan A, Sanchez-Rodriguez E, Zanoni F, Li Y, Steers N, Balderes O, Zhang J, Krithivasan P, LeDesma RA, Fischman C, Hebbring SJ, Harley JB, Moncrieffe H, Kottyan LC, Namjou-Khales B, Walunas TL, Knevel R, Raychaudhuri S, Karlson EW, Denny JC, Stanaway IB, Crosslin D, Rauen T, Floege J, Eitner F, Moldoveanu Z, Reily C, Knoppova B, Hall S, Sheff JT, Julian BA, Wyatt RJ, Suzuki H, Xie J, Chen N, Zhou X, Zhang H, Hammarström L, Viktorin A, Magnusson PKE, Shang N, Hripcsak G, Weng C, Rundek T, Elkind MSV, Oelsner EC, Barr RG, Ionita-Laza I, Novak J, Gharavi AG, Kiryluk K. Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits. Nat Commun 2022; 13:6859. [PMID: 36369178 PMCID: PMC9651905 DOI: 10.1038/s41467-022-34456-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 10/25/2022] [Indexed: 11/13/2022] Open
Abstract
Immunoglobulin A (IgA) mediates mucosal responses to food antigens and the intestinal microbiome and is involved in susceptibility to mucosal pathogens, celiac disease, inflammatory bowel disease, and IgA nephropathy. We performed a genome-wide association study of serum IgA levels in 41,263 individuals of diverse ancestries and identified 20 genome-wide significant loci, including 9 known and 11 novel loci. Co-localization analyses with expression QTLs prioritized candidate genes for 14 of 20 significant loci. Most loci encoded genes that produced immune defects and IgA abnormalities when genetically manipulated in mice. We also observed positive genetic correlations of serum IgA levels with IgA nephropathy, type 2 diabetes, and body mass index, and negative correlations with celiac disease, inflammatory bowel disease, and several infections. Mendelian randomization supported elevated serum IgA as a causal factor in IgA nephropathy. African ancestry was consistently associated with higher serum IgA levels and greater frequency of IgA-increasing alleles compared to other ancestries. Our findings provide novel insights into the genetic regulation of IgA levels and its potential role in human disease.
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Butler-Laporte G, Povysil G, Kosmicki JA, Cirulli ET, Drivas T, Furini S, Saad C, Schmidt A, Olszewski P, Korotko U, Quinodoz M, Çelik E, Kundu K, Walter K, Jung J, Stockwell AD, Sloofman LG, Jordan DM, Thompson RC, Del Valle D, Simons N, Cheng E, Sebra R, Schadt EE, Kim-Schulze S, Gnjatic S, Merad M, Buxbaum JD, Beckmann ND, Charney AW, Przychodzen B, Chang T, Pottinger TD, Shang N, Brand F, Fava F, Mari F, Chwialkowska K, Niemira M, Pula S, Baillie JK, Stuckey A, Salas A, Bello X, Pardo-Seco J, Gómez-Carballa A, Rivero-Calle I, Martinón-Torres F, Ganna A, Karczewski KJ, Veerapen K, Bourgey M, Bourque G, Eveleigh RJM, Forgetta V, Morrison D, Langlais D, Lathrop M, Mooser V, Nakanishi T, Frithiof R, Hultström M, Lipcsey M, Marincevic-Zuniga Y, Nordlund J, Schiabor Barrett KM, Lee W, Bolze A, White S, Riffle S, Tanudjaja F, Sandoval E, Neveux I, Dabe S, Casadei N, Motameny S, Alaamery M, Massadeh S, Aljawini N, Almutairi MS, Arabi YM, Alqahtani SA, Al Harthi FS, Almutairi A, Alqubaishi F, Alotaibi S, Binowayn A, Alsolm EA, El Bardisy H, Fawzy M, Cai F, Soranzo N, Butterworth A, Geschwind DH, Arteaga S, Stephens A, Butte MJ, Boutros PC, Yamaguchi TN, Tao S, Eng S, Sanders T, Tung PJ, Broudy ME, Pan Y, Gonzalez A, Chavan N, Johnson R, Pasaniuc B, Yaspan B, Smieszek S, Rivolta C, Bibert S, Bochud PY, Dabrowski M, Zawadzki P, Sypniewski M, Kaja E, Chariyavilaskul P, Nilaratanakul V, Hirankarn N, Shotelersuk V, Pongpanich M, Phokaew C, Chetruengchai W, Tokunaga K, Sugiyama M, Kawai Y, Hasegawa T, Naito T, Namkoong H, Edahiro R, Kimura A, Ogawa S, Kanai T, Fukunaga K, Okada Y, Imoto S, Miyano S, Mangul S, Abedalthagafi MS, Zeberg H, Grzymski JJ, Washington NL, Ossowski S, Ludwig KU, Schulte EC, Riess O, Moniuszko M, Kwasniewski M, Mbarek H, Ismail SI, Verma A, Goldstein DB, Kiryluk K, Renieri A, Ferreira MAR, Richards JB. Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative. PLoS Genet 2022; 18:e1010367. [PMID: 36327219 PMCID: PMC9632827 DOI: 10.1371/journal.pgen.1010367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/29/2022] [Indexed: 11/05/2022] Open
Abstract
Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.
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Grants
- U24 CA224319 NCI NIH HHS
- RG/13/13/30194 British Heart Foundation
- C18281/A29019 Cancer Research UK
- MC_PC_20004 Medical Research Council
- UL1 TR001873 NCATS NIH HHS
- RG/18/13/33946 British Heart Foundation
- CH/12/2/29428 British Heart Foundation
- CanCOGeN HostSeq
- Fonds de Recherche Québec Santé (FRQS)
- Génome Québec
- Public Health Agency of Canada
- Canadian Institutes of Health Research (CIHR)
- Lady Davis Institute of the Jewish General Hospital
- Canadian Foundation for Innovation
- NIH Foundation
- McGill Interdisciplinary Initiative in Infection and Immunity (MI4)
- Jewish General Hospital Foundation
- McGill University
- Calcul Québec and Compute Canada
- Compute Canada
- Vagelos College of Physicians & Surgeons Office for Research
- Biomedical Informatics Resource of the Columbia University Irving Institute for Clinical and Translational Research (CTSA)
- National Center for Advancing Translational Sciences, National Institutes of Health
- German Research Foundation
- NGS Competence Center Tübingen
- West German Genome Center
- Stiftung Universitätsmedizin Essen
- Technical University of Munich
- BONFOR program of the Medical Faculty, University of Bonn
- Emmy-Noether programm of the German Research Foundation
- State of Saarland
- Dr. Rolf M. Schwiete Foundation
- Munich Clinician Scientist Programm
- Netzwerk-Universitaetsmedizin-COVIM
- Federal Ministry of Education and Research
- Swiss National Science Foundation
- Leenaards Foundation
- Santos-Suarez Foundation
- Carigest
- MIUR project “Dipartimenti di Eccellenza 2018-2020”
- Bando Ricerca COVID-19 Toscana
- charity fund 2020 from Intesa San Paolo
- Italian Ministry of University and Research
- Istituto Buddista Italiano Soka Gakkai
- Instituto de Salud Carlos III
- GePEM
- DIAVIR
- Resvi-Omics
- ReSVinext
- Enterogen
- Agencia Gallega para la Gestión del Conocimiento en Salud
- BI-BACVIR
- CovidPhy
- Agencia Gallega de Innovación (GAIN):
- GEN-COVID
- Framework Partnership Agreement between the Consellería de Sanidad de la XUNTA de Galicia
- GENVIP-IDIS
- consorcio Centro de Investigación Biomédica en Red de Enfermedades Respiratorias
- F. Hoffmann-La Roche Ltd
- U.S. Department of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response, and Biomedical Advanced Research and Development Authority
- Nevada Governor's Office of Economic Development
- Renown Health and the Renown Health Foundation
- Ratchadapiseksompotch Fund, Faculty of Medicine, Chulalongkorn University
- Healthcare-associated Infection Research Group STAR (Special Task Force for Activating Research)
- Grant for Development of New Faculty Staff, Ratchadaphiseksomphot Endowment Fund
- e-ASIA Joint Research Program (National Science and Technology Development Agency)
- Health Systems Research Institute, TSRI Fund
- Thailand Research Fund
- Ratchadapiseksompotch Fund
- Ratchadapiseksompotch Fund, Faculty of Medicine,Chulalongkorn University, Bangkok, Thailand
- Health Systems Research Institute
- Ratchadapisek Sompoch Endowment Fund, Chulalongkorn University
- NHS Blood and Transplant
- National Institute for Health Research
- UK Medical Research Council
- Japan Agency for Medical Research and Development
- Japan Science and Technology Agency
- National Center for Global Health and Medicine
- Agency for Medical Research and Development
- Polish National Science Centre
- Medical Research Agency
- Perelman School of Medicine at University of Pennsylvania
- Smilow family
- National Center for Advancing Translational Sciences of the National Institutes of Health
- Polish Medical Research Agency
- Qatar Foundation for Education, Science and Community Development
- Saudi Ministry of Health
- King Abdulaziz City for Science and Technology
- European Union’s Horizon 2020 research and innovation program
- Science for Life Laboratory
- Swedish Research Council
- Knut and Alice Wallenberg Foundation
- OCRC
- Microsoft COVID Compute Funding
- Illumina
- UCLA David Geffen School of Medicine - Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research Award Program
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