KDIGO executive conclusions www.kidney-international.org Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes OPEN (KDIGO) Controversies Conference KDIGO Conference Participants1 C Numerous genes for monogenic kidney diseases with hronic kidney disease (CKD) affects approximately classical patterns of inheritance, as well as genes for 10% of the global adult population.1 Multiple genetic complex kidney diseases that manifest in combination with and environmental risk factors contribute to kidney environmental factors, have been discovered. Genetic diseases, making identification of the underlying pathophys- findings are increasingly used to inform clinical iologic mechanisms difficult. However, the advent of high- management of nephropathies, and have led to improved throughput genotyping and massively parallel sequencing, diagnostics, disease surveillance, choice of therapy, and combined with the availability of large datasets of genomic family counseling. All of these steps rely on accurate and health information, has led to rapid advances in our interpretation of genetic data, which can be outpaced by understanding of the genetic basis of kidney function and current rates of data collection. In March of 2021, Kidney disease. Diseases: Improving Global Outcomes (KDIGO) held a To date, more than 600 genes have been implicated in Controversies Conference on “Genetics in Chronic Kidney monogenic kidney diseases,2 and known single-gene disorders Disease (CKD)” to review the current state of understanding account for up to 50% of nondiabetic CKD in pediatric of monogenic and complex (polygenic) kidney diseases, cohorts, and 30% in adult cohorts.3–10 In addition, genetic processes for applying genetic findings in clinical medicine, variation plays an important role for kidney function in the and use of genomics for defining and stratifying CKD. Given normal range,11–16 and common genetic variants account for the important contribution of genetic variants to CKD, approximately 20% of the estimated genetic heritability of practitioners with CKD patients are advised to “think estimated glomerular filtration rate (eGFR).13 Common genetic,” which specifically involves obtaining a family genetic variants also have been shown to contribute to disorders, history, collecting detailed information on age of CKD such as IgA nephropathy,17,18 membranous nephropathy,19,20 onset, performing clinical examination for extrarenal and nephrotic syndrome.21–23 Hence, the pathogenesis model symptoms, and considering genetic testing. To improve the for many kidney diseases has expanded to include multiple use of genetics in nephrology, meeting participants genetic and environmental factors that together contribute to the advised developing an advanced training or subspecialty pathology, commonly referred to as “complex disease.” track for nephrologists, crafting guidelines for testing and Genetic findings increasingly are used to inform clinical treatment, and educating patients, students, and management of many nephropathies, enabling more precise practitioners. Key areas of future research, including clinical diagnostics, targeted disease surveillance, and better-informed interpretation of genome variation, electronic choices for therapy and family counseling.24 Clinical man- phenotyping, global representation, kidney-specific agement relies on accurate interpretation of genomic data, a molecular data, polygenic scores, translational labor-intensive process that can be outpaced by the speed of epidemiology, and open data resources, were also discovery.25 To realize the promises of genomic medicine for identified. kidney disease, many technical, logistical, ethical, and scien- Kidney International (2022) 101, 1126–1141; https://doi.org/10.1016/ tific questions must be addressed.24 In March of 2021, Kidney j.kint.2022.03.019 Diseases: Improving Global Outcomes (KDIGO) held a KEYWORDS: genetic kidney disease; genetic testing; genome-wide associ- Controversies Conference on the topic of “Genetics in CKD” ation studies; monogenic; polygenic; single-nucleotide polymorphism to review the current state of understanding of monogenic Copyright ª 2022, Kidney Disease: Improving Global Outcomes (KDIGO). and complex kidney diseases, processes for applying genetic Published by Elsevier Inc. on behalf of the International Society of findings in clinical medicine, and use of genomics for defining Nephrology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). and stratifying CKD. Participants identified areas of consensus, gaps in knowledge, and priorities for research Correspondence: Anna Köttgen, Institute of Genetic Epidemiology, Faculty (Table 1). The conference agenda, discussion questions, and of Medicine and Medical Center, University of Freiburg, Hugstetter Str. 49, plenary session presentations are available on the KDIGO 79106 Freiburg, Germany. E-mail: anna.koettgen@uniklinik-freiburg.de; or Ali website: https://kdigo.org/conferences/genetics-in-ckd/. G. Gharavi, Division of Nephrology, Department of Medicine, Columbia Uni- versity Irving Medical Center, Russ Berrie Pavilion, 1150 St Nicholas Avenue, New York, New York 10032, USA. E-mail: ag2239@cumc.columbia.edu Definitions and epidemiology of genetic kidney diseases 1 The KDIGO Conference Participants are listed in the Appendix. The familial aggregation and substantial heritability of CKD Received 13 January 2022; revised 16 March 2022; accepted 29 March are well described across the world. Recent large-scale ana- 2022; published online 20 April 2022 lyses of electronic medical records estimated observational 1126 Kidney International (2022) 101, 1126–1141 Genetics in CKD Conference Participants: A KDIGO report KDIGO executive conclusions Table 1 | Summary points from the Genetics in CKD Controversies Conference Consensus  Monogenic and complex kidney diseases exist on a continuum, but dichotomous categories are useful for practical distinction.  There is no upper age-limit for monogenic CKD.  Actionable genes in kidney diseases refers to genes in which the identification of pathogenic variants can lead to specific clinical actions for treatment or prevention, following recommendations based on evidence.  There is a need for development of a reference kidney disease gene list and standardization of gene/variant reporting for kidney diseases.  A larger workforce with expertise in kidney genetics, genomics, and computational research is needed.  Education of the workforce is necessary for successful implementation of genetic testing in clinical nephrology.  More studies are needed that include diverse populations worldwide to ensure equitable and generalizable implementation of genetic testing, obtain evidence of causality, establish global prevalence, and facilitate variant discovery.  Interdisciplinary expert boards (including nephrologists, clinical geneticists, molecular biologists, genetic counselors) should be assembled to discuss potential genetic diagnostic findings and counsel primary and secondary care centers.  Genomics should be integrated into clinical trials on kidney diseases.  Estimates of the prevalence of monogenic CKD are important, but they are currently imprecise due to selection bias. Ongoing controversies Definitions/terminology  Two-part names (clinical condition PLUS gene name) are preferred for more-precise disease terminology.  The term CKD of unknown etiology is not clear and is in need of consensus.  There is no clear consensus on which VUS are to be reported in the framework of diagnostic testing. Processes for improving data capture and analysis  Improve phenotyping, including methods for electronic phenotyping.  Improve the quality of genomic studies, including analytical and computational methods.  Improve data access while protecting the privacy of research participants.  Create processes for transferring genetic information obtained through clinical testing to research.  Study health–economic impacts of genetic testing in nephrology.  Establish a process for periodic reanalysis of unsolved cases with kidney disease.  Implement high-throughput techniques for in silico and in vitro variant characterization.  Identify and characterize rare variants, structural variants, and functional variants using functional genomic, epigenetic, and other multi-omic approaches.  Employ new approaches to identify more homogeneous CKD phenotypes and subclassifications for genetic studies, such as using nontraditional omics biomarkers, electronic health record data, imaging, or machine learning.  Assemble larger cohorts with genetically defined kidney disease for both research and clinical trials; collaborate internationally if possible.  Reduce measurement errors in eGFR, and misclassification in the resulting CKD definition; for example, reassess coefficients based on race, sex, and chronological age in eGFR equations.  Conduct large-scale genetic studies on specific kidney sub-phenotypes, such as CKD progression, acute kidney injury, cause-specific disease severity, and manifestations.  Integrate genetic studies with biomarker and multi-omic profiling to leverage findings and increase power for both variant and pathway identification.  Generate comprehensive molecular maps of kidney tissue/cells as well as in vitro and animal models to enable mechanistic studies of genes identified in GWAS of kidney traits.  Encourage broad data sharing (FAIR principles; findable, accessible, interoperable, reusable) and transparent protocols for data generation, quality control, and analyses.  Use federated networks to standardize key data elements across platforms and countries.  Use portals (cloud-based) to “safely” share individual data and allow for democratization and a broader scale of integrative in silico analyses.  Extend discovery analyses to nonadditive genetic models (e.g., recessive) and include nonautosomal regions (e.g., chromosome X, mitochondrial).  Improve imputation reference panels.  Apply and develop approaches specific to admixed populations.  Conduct Mendelian randomization analysis to elucidate causal mechanisms. Priorities for Implementation  Increase genetic and genomic resources in underrepresented populations with kidney disease.  Investigate the use of polygenic scores in clinical settings.  Develop guidelines for nephrologist to establish core competencies in genetics, develop evaluations to test them, and identify the educational gaps of general nephrologists (some need to be country-specific).  Develop and test the impact of dissemination tools to spread the basic knowledge required for all nephrologists.  Measure the quality of existing or to-be-established genetic subspecialty training for nephrologists as well as training in nephrology for genetic counselors and molecular geneticists (variant interpretation side).  Develop guidelines for the referral of nephrology patients to genetic counseling/genetic testing/reproductive counseling.  Analyze the impact of genetic testing on clinical outcomes of nephrology patients.  Analyze the cost-effectiveness and longitudinal clinical utility of genetic testing.  Analyze the impact of centers of expertise on quality of care and patient outcomes. CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; GWAS, genome-wide association studies; VUS, variants of uncertain significance. Kidney International (2022) 101, 1126–1141 1127 KDIGO executive conclusions Genetics in CKD Conference Participants: A KDIGO report Table 2 | Characteristics of monogenic versus complex genetic diseases Monogenic (Mendelian) Polygenic (complex) Allele/variant frequency Rare Can be common Effect size of major Large Small driving gene Penetrance High Low Role of environment Limited Strong Inheritance model Mendelian None apparent heritability of CKD to be in the range of 25%–44%, with higher estimates for patients of African ancestry.26 These es- timates are generally consistent with traditional family-based heritability studies of CKD and glomerular filtration rate.27–29 The relatively high heritability of CKD is likely attributable to both monogenic causes as well as complex or polygenic factors. Monogenic (also termed “Mendelian”) CKD generally re- fers to diseases caused by rare, pathogenic variants in a single gene (Table 2); the genotype-to-phenotype relationship is Figure 1 | Common variant contributions to kidney diseases and traits.13,14,17,19,31 *For binary outcomes, the proportions of strong, and environmental factors have limited influence. phenotypic variance explained by loci from genome-wide Oligogenic disorders are determined by rare variants in a few association studies (GWAS) were estimated from Nagelkerke’s or genes. Complex or polygenic diseases lack simple patterns of McKelvey & Zavoina’s pseudo R2. eGFR, estimated glomerular inheritance (e.g., dominant, recessive, or sex-linked) and filtration rate; IgA, immunoglobulin A; SNP, single-nucleotide polymorphism. instead are influenced by the aggregate effect of many com- mon genetic variants in multiple genomic regions, as well as environmental factors.30 Such aggregate effects of common genome-wide association studies (GWAS) and exome- or variants (or single-nucleotide polymorphisms [SNPs]) can be genome-sequencing studies of large population samples— quantified by SNP-based heritability, which has been esti- usually of European or East Asian ancestry mated for various types of kidney disorders to range from (Figure 2).13,14,17,19,31,39–41 The largest number of loci— 14% for renal cancer among individuals of European ancestry genomic regions containing associated SNPs—were discov- to 43% for membranous nephropathy among individuals of ered for the continuous kidney function measure eGFR, East Asian ancestry. The proportions of variance explained by with studies based on data from >1 million individuals known loci of these diseases are smaller, ranging from <1% reporting more than 250 such loci.12–14,17,19,22,23,31,40,42–66 for urinary albumin-to-creatinine ratio to 32% for mem- Although the distinction of monogenic versus polygenic branous nephropathy among individuals of East Asian diseases provides a useful practical framework, genetic risk ancestry (Figure 1).13,14,17,19,31 However, common genetic variants for kidney diseases occur on a spectrum from rare factors also may influence the age of onset, severity, rate of variants with large effects to common variants with small progression, and associated extrarenal complications of effects, and many diseases do not fit neatly into either monogenic diseases, which often have variable expres- category. For example, apolipoprotein L1 (APOL1)– sion.32,33 In addition to CKD attributed to specific etiologies, associated kidney risk variants are common among some genetic studies also use phenotypic readouts, such as mea- populations of African ancestry and impart a relatively high sures of kidney function or damage (e.g., eGFR, albumin- risk under a recessive mode of inheritance, but these var- uria), kidney histology classification, and molecular injury iants are not considered monogenic. The magnitude of the markers to define CKD (Table 3).34,35 risk associated with APOL1 variants varies significantly for Monogenic variants account for approximately 30%–50% different forms of nephropathy. For example, Black South of cases of CKD stages G3b–G5 in children,3–5,36,37 and Africans with untreated human immunodeficiency virus 10%–30% in adults.3–10 Diagnostic yields vary between 12% (HIV) and 2 APOL1 risk alleles have been reported to have and 65% among studies, with selection bias likely contrib- a more than 80-fold increased risk of developing HIV- uting to the variability. However, prevalence estimations for associated nephropathy, but the magnitude of the risk genetic diseases are likely to change over time as genetics- conferred by the same risk alleles ranged between 1.2 and 2 first approaches to diagnosis (in which sequence data are for CKD or nondiabetic kidney failure (Figure 3).67–85 obtained first, followed by characterization of associated Similarly, the combination of 2 common variants in the phenotypes) become more common.38 Many common var- HLA-DR and PLA2R1 loci imparts a high risk of the iants associated with specific kidney function measures or complex disease membranous nephropathy, defying the complex kidney diseases have been identified through common variant/small effect paradigm.20 1128 Kidney International (2022) 101, 1126–1141 Genetics in CKD Conference Participants: A KDIGO report KDIGO executive conclusions Table 3 | Disease definitions for genetic studies based on kidney function, kidney histology, and molecular markers: advantages and disadvantages Advantages Disadvantages Kidney function markers (e.g., eGFR, albuminuria)  Readily attainable and standardized information in low-  Descriptive nature of disease categorization and high-income settings  Agnostic to underlying kidney pathology and pathophysiology and  Deployed routinely in clinical care and interventional trials disease heterogeneity  Allows the identification of genetic determinants of  Urinary albumin excretion is underutilized kidney function and factors impacting the progression  Current markers identify genetic variants related to marker meta- of kidney disease bolism but not filtration  Relatively inexpensive  Repeated measures often readily available to assess trajectory Kidney histology  Allows for classification based on structural patterns of  Often aggregates a diverse set of underlying disease-initiating events damage under a common histological damage pattern (e.g., FSGS), thereby  Standardized classification scheme for most glomerular potentially introducing functional and genetic heterogeneity diseases  Limited accessibility in resource-constrained settings  Current reference standard for clinical management with established clinical workflow  Histology classifications may reflect a more homoge- nous pathophysiology than kidney-function markers Nontraditional molecular markers (e.g., markers quantified with high-throughput omics technologies)  Can segregate kidney-disease populations into more-  Emerging technologies with limited accessibility in resource- homogenous subgroups and thereby facilitate the constrained settings need to establish cost-effective readouts identification of underlying disease causes and drivers readily attainable in low- and middle-income countries  Enables systems genetics analysis of kidney disease  Access to large biobanks required for disease subtyping  Comprehensive multi-omics profiling possible (e.g.,  Some marker levels may vary by kidney function metabolomics, proteomics, exposomics) eGFR, estimated glomerular filtration rate; FSGS, focal segmental glomerulosclerosis. Considerations for genetic testing benefit from developing guidelines based on best evidence and A positive family history, early age of onset, and presence of practices in clinical genetics. Overall, guidance should take into extrarenal symptoms are associated with a higher probability of account the potential benefit of a genetic diagnosis for specific monogenic disease. In addition, the clinical diagnosis is highly patients and their families (e.g., treatment changes, family predictive of diagnostic yield and will guide the choice of genetic planning, ending a diagnostic odyssey) and balance the risk of tests, motivating a thorough clinical workup prior to genetic false-positive results that could engender unnecessary clinical testing. For example, glomerular and tubulointerstitial disorders workup for patients and their families. A position paper by the are associated with a higher diagnostic yield than diabetic kidney European Renal Association–European Dialysis and Trans- disease. In general, because of the genetic heterogeneity of most plant Association (ERA-EDTA) Working Group for Inherited forms of nephropathy, genetic testing with phenotype-driven Kidney Diseases (WGIKD) and the Molecular Diagnostics gene panels, or exome or genome sequencing, is more effi- Taskforce of the European Rare Kidney Disease Reference cient than sequential single-gene analyses. Network (ERKNet) has been recently issued to delineate in- Genetic testing is usually performed subsequent to a clinical dications for genetic testing in CKDs.86 workup, but in some situations, early genetic testing may be Defining actionable genes in kidney diseases. Actionable advantageous. For example, prospective kidney donors related genes in kidney diseases refer to genes that, when significantly to a recipient with a known genetic condition should be tested altered, confer a high risk of serious disease that could be early during the donor-evaluation process. Other situations in prevented or mitigated if the risk were known.87 A set of 73 which early genetic testing should be considered are listed in actionable genes have been proposed by the American College Table 4. For healthy children and adults, currently, no data of Medical Genetics and Genomics (ACMG), many of which support predictive or presymptomatic genetic testing, even if a are associated with phenotypes relevant to nephrology family history is present. Nevertheless, once a pathogenic (PALB2, GLA, HNF1A, MEN1, MAX, RET, SDHAF2, SDHB, variant is identified in a proband, cascade testing of family SDHC, SDHD, VHL, TMEM127, TSC1, TSC2, WT1). members and genetic counseling in mutation carriers are the Although these genes were selected based on the possibility standard practices in clinical genetics. that targeting them may prevent overall morbidity and/or Most countries do not have guidelines to help determine mortality, one can conceive of additional, kidney-specific which nephrology patients should be referred to genetic testing actionable genes, nominated based on availability of in- and counseling. Nephrology communities would therefore terventions, that could prevent renal morbidity (Figure 4). Kidney International (2022) 101, 1126–1141 1129 KDIGO executive conclusions Genetics in CKD Conference Participants: A KDIGO report Figure 2 | Genome-wide association studies (GWAS), exome- or genome-sequencing studies of kidney function markers and kidney diseases.13,14,17,19,31,39–41 *The largest study focused on urinary albumin-to-creatinine ratio. Several included serum albumin studies. **Pediatric population. ***For case–control studies, the total sample sizes were plotted. CKD, chronic kidney disease; eGFRcr, estimated glomerular filtration rate from serum creatinine; FSGS, focal segmental glomerulosclerosis; IgAN, IgA nephropathy; KF, kidney failure; LN, lupus nephritis; MCD, minimal change disease; MN, membranous nephropathy; Scr, serum creatinine; SRNS and SSNS, steroid-resistant and steroid-sensitive nephrotic syndrome; T1DN and T2DN, type 1 and type 2 diabetic nephropathy; WES, whole-exome sequencing; WGS, whole- genome sequencing. Examples include the following: early initiation of general primary hyperoxaluria). ClinGen, an international initiative renoprotective therapies (e.g., renin-angiotensin blockade for to define robust disease-gene associations and curate path- carriers of pathogenic variants in type IV collagen genes); ogenic variants,87 now has a kidney expert work group that initiation of targeted therapies (e.g., enzyme therapy for Fabry is developing a stable list of nephropathy-associated genes disease or CoQ10 supplementation for nephrotic syndrome and variants. This group is also expected to provide guid- due to CoQ10 deficiency); avoidance of treatment that ance for actionability for kidney genes and nominate them would be futile and perhaps even deleterious (e.g., pro- for the ACMG list. Awareness of the ClinGen Initiative longed immunosuppressive therapies for genetic podocyto- should be promoted in the kidney community, along with pathies); and surveillance for recurrence of disease after messaging regarding the importance of variant submission kidney transplantation (e.g., atypical hemolytic uremic to public databases such as ClinVar and the value of creating syndrome/thrombotic microangiopathy [aHUS/TMA], interdisciplinary expert boards to discuss controversial LN Africa. nondiabetic* G2G2, or G1G2. date. White patients. Figure 3 | Associations of APOL1 high-risk genotype and various kidney diseases or their progression.67–83 APOL1 high-risk genotype: G1G1, G2G2, or G1G2. Studies were ordered by PubMed identifier (PMID), a proxy for publication date. *Compared with White patients. APOL1, apolipoprotein L1; CKD, chronic kidney disease; DRC, Democratic Republic of Congo; FSGS, focal segmental glomerulosclerosis; HIVAN, human immunodeficiency virus–associated nephropathy; HTN, hypertension; KF, kidney failure; LN, lupus nephritis. 1130 Kidney International (2022) 101, 1126–1141 Genetics in CKD Conference Participants: A KDIGO report KDIGO executive conclusions Table 4 | Potential indications for genetic testing for monogenic forms of CKD  The clinical work indicates the possibility of a genetic disease, such as—  high prevalence of monogenic subtypes within the clinical category (e.g., congenital/cystic nephropathies or steroid-resistant nephrotic syndrome)  positive family history of kidney disease  early age of onset (pediatric CKD)  syndromic/multisystem features  consanguinity  possibility of identifying a condition amenable to targeted treatment (e.g., enzyme replacement therapy for Fabry disease)  The individual is an at-risk relative of a patient with a known monogenic disease, especially when the individual is a potential kidney donor  As an alternative to kidney biopsy in patients at high risk of biopsy-related complications, especially when there is a high pre-test probability of finding a genetic variant based on family or clinical history  CKD or kidney failure of unknown etiology when kidney biopsy would not be informative due to advanced disease, and other features suggestive of hereditary disease are present  Information to guide continuation of immunosuppressive therapy (e.g., in steroid-resistant or partially responsive nephrotic syndrome)  Genetic testing can provide prognostic information (e.g., ADPKD or Alport Syndrome, age at kidney failure)  Diagnosis of diseases with risk of recurrence in kidney allografts (e.g., aHUS/TMA, primary hyperoxaluria) ADPKD, autosomal dominant polycystic kidney disease; aHUS, atypical hemolytic uremic syndrome; CKD, chronic kidney disease; TMA, thrombotic microangiopathy. variants of uncertain significance (VUS) and discussing the APOL1 presents a special case in clinical nephrology because most complex cases. Additional efforts to harmonize gene biallelic inheritance of 2 common variants in this gene, which and gene-panel curation, such as the Genomics England present at high frequency in some populations of African panel app (https://panelapp.genomicsengland.co.uk) are lis- ancestry, increases risk for several kidney disorders.89,90 Po- ted in Supplementary Table S1. tential benefits for APOL1 screening include improved risk In addition to rare pathogenic variants, common genetic stratification and opportunities for education. However, only a variants or polygenic scores may become appropriate for minority of patients with APOL1 risk genotypes develop ne- clinical reporting if they are shown to alter patient manage- phropathy, and currently no data support early intervention in ment, indicate need for surveillance for progression or asso- asymptomatic individuals to reduce future risk of disease. ciated comorbidities, or inform familial screening.88 In Potential drawbacks to screening include potential for anxiety, complex diseases, the current best candidates for reporting stigma, or apathy, and the lack of evidence-based in- include APOL1 risk alleles,89,90 genetic risk score for mem- terventions.92,93 Combined, these drawbacks could lead to branous nephropathy based on PLA2R1, NFKB1, IRF4, and misunderstanding among patients, mistrust of the medical HLA risk alleles,19 extremes of a polygenic risk score for system, and perceived or real racial bias, given that APOL1 risk eGFR,91 and pharmacogenetic variants that are informative variants are found predominantly in those with African about risk of adverse events, pharmacokinetics, and phar- ancestry. On the other hand, the failure to offer a test that could macodynamics for specific drugs, some of which may be be most informative in a specific ancestry group also could be especially relevant to CKD patients (for example, azathio- perceived as bias. For transplant patients, APOL1 screening prine, tacrolimus, warfarin, clopidogrel, simvastatin, vor- could prevent harm to living donors and satisfy recipients’ right iconazole, and allopurinol). However, we currently lack to know, but screening could also reduce rates of living dona- evidence for actionability for polygenic scores—that is, evi- tion, waste deceased donor kidneys, and exacerbate organ dence that reporting can improve clinical outcomes. shortage. The APOL1 Long-term Kidney Transplantation Conditions amenable Conditions amenable Avoidance of Conditions at risk for Conditions amenable Conditions for which to specific disease- to nonspecific prolonged recurrence after to specific screening genetic testing is modifying therapies renoprotective immunosuppressive kidney transplantation for extrarenal relevant for reproductive strategies therapies manifestations counseling Examples: Example: Example: Examples: Examples: Example: • GLA (Fabry) • COL4A3/4/5 (Alport) • Glomerular disease • (CFH/CFI/C3..): aHUS • HNF1B: diabetes • Prenatal/preimplantation • AGXT (primary and RAAS blockade due to mutations in • (AGXT, GRHPR, • PKD1/PKD2 diagnosis hyperoxaluria [PH]) Alport genes HOGA): primary (ADPKD): intracranial • CoQ10 genes (SRNS) (COL4A3/4/5) hyperoxaluria (PH) aneurysms • CTNS (cystinosis) • Adenine phosphoribo- • FLCN: renal cell • Tubulopathies syltransferase carcinoma, etc. (Na+, K+, etc.) deficiency (APRT) Figure 4 | Actionable genes in kidney diseases. Actionability refers to the potential for genetic test results to lead to specific clinical actions for prevention or treatment of a condition, supported by recommendations based on evidence. ADPKD, autosomal dominant polycystic kidney disease; aHUS, atypical hemolytic uremic syndrome; RAAS, renin–angiotensin–aldosterone system; SRNS, steroid-resistant nephrotic syndrome. Kidney International (2022) 101, 1126–1141 1131 KDIGO executive conclusions Genetics in CKD Conference Participants: A KDIGO report status for autosomal recessive inheritance is not routinely Clinical name Gene name reported in standard diagnostic reports. Guidelines for sys- ADTKD UMOD ADPKD PKD1 tematic reporting of these variants should be developed. • Helps to trigger a clinical • Precision diagnosis Heterozygosity associated with a mild phenotype is increas- understanding of the disease • Can convey prognostic information ingly recognized in human genetics, for example, for • Important prior to identification (e.g. PKD1 vs. PKD2) of the gene involved • Can justify specific follow-up/treatment COL4A3/COL4A4 variants.97 Unified disease terminology. The consensus among con- Figure 5 | Unified disease terminology. Two-part (“dyadic”) ference participants was that establishing a unified disease naming comprises both the clinical condition and the gene name. terminology that takes into account genetic disease nomen- An example is autosomal dominant tubulointerstitial kidney disease (ADTKD), with ADTKD followed by reference to the underlying clature is an important goal for the community. In support of genetic defect, as in ADTKD-UMOD. ADPKD, autosomal dominant unified, precise disease terminology, a suggested approach is polycystic kidney disease. 2-part (“dyadic”) naming, comprising both the clinical con- dition and the gene name (Figure 5), although some con- troversy regarding this approach remains.98,99 An important Outcomes Network (APOLLO) study, which is in progress and example is adoption of 2-part naming in autosomal dominant expected to end in 2023, is prospectively evaluating the impact tubulointerstitial kidney disease (ADTKD), in which ADTKD of APOL1 risk alleles on donor and recipient outcomes.94 is followed by reference to the underlying genetic defect, such Moreover, the initiation of genotype-driven clinical trials may as in ADTKD-UMOD and ADTKD-MUC1.100 Two-part change the approach to diagnostic testing for APOL1 and other names provide flexibility, in that some users (patients/clini- genetic disorders. These considerations emphasize the impor- cians) can use the first part only (ADTKD), and others (pa- tance of further research into the usefulness of APOL1 testing. tients/clinicians/researchers) can use the whole name (ADTKD-UMOD). When clinical presentation is unspecific, Reporting and terminology standards or very heterogeneous, use of the gene name followed by Differences in how diagnostic laboratories evaluate and report “kidney disease” (e.g., PAX2-kidney disease) is encouraged. variants pose a significant challenge in molecular diagnosis. Potential limits to this approach include the possibility of Therefore, standardization of evaluation and reporting among classifying a patient with a benign prognosis as having a different laboratories and countries is an agreed-on key pri- potentially progressive disorder, as well as the challenge of ority. The determination regarding pathogenicity is a semi- adding a second or gene name to conditions already described quantitative process that takes into account variant allele in International Classification of Disease codes. In this regard, frequency, predicted impact on protein function, and prior participants of this KDIGO Controversies Conference did not reports of occurrence with disease. The ACMG and the As- reach consensus regarding renaming of traditional disease sociation for Molecular Pathology (AMP) published stan- terms, such as Alport Syndrome. dards and guidelines for the interpretation of sequence variants.95 These guidelines are reviewed periodically and refined by the ClinGen Initiative to reduce discrepancies in Genomic discovery and implications for chronic kidney variant interpretation among laboratories and clinicians. diseases The ACMG criteria classify variants into 1 of 5 tiers, with As demonstrated by the first GWAS for eGFR, common ge- tiers 4 and 5 (i.e., likely pathogenic and pathogenic) classified netic variants that are associated with complex kidney traits as diagnostic variants.95 All variant classes can be later usually have small effects and therefore require very large upgraded or downgraded based on novel information or sample sizes for discovery.101 Accordingly, success has been interpretation, perhaps necessitating periodic review of clin- limited in identifying common kidney disease susceptibility ical genetic reports. However, the abundance of class 3 VUS variants in individual observational studies of adult102–105 and has created a particular challenge and urgency for improving pediatric106–108 CKD. Conference participants therefore evaluation and reporting. The definition and relevance of recognized the importance of collaborative consortia, such as VUS may be unclear to physicians or patients, causing the Chronic Kidney Disease Genetics Consortium incorrect assignment of diagnoses and/or psychological (CKDGen),11,109 Cohorts for Heart and Aging Research in distress to patients and families. This situation necessitates Genomic Epidemiology (CHARGE) Consortium,66,110 Inter- proper communication with patients to inform and educate national Genetics & Translational Research in Transplantation them about the possibility of VUS, in which case familial Network (iGeneTRAiN),111 and Continental Origins and segregation analysis might be recommended. Additionally, Genetic Epidemiology Network (COGENT) Kidney Con- VUS should be reported only after interdisciplinary contact sortium,112,113 that aggregate and harmonize genetic and between the clinician and geneticist has occurred.96 Future phenotypic data across multiple studies for combined genetic reinterpretation of variants can be facilitated by diagnostic discovery. In addition to enlarging sample size and providing reports that provide detailed description of ACMG classifi- a platform for replication studies, expanding consortia to cation criteria that were applied at the time of reporting. international sites can enable studies of more ancestrally and Although no guidelines exist currently, incidental carrier geographically diverse populations. For more specific but less 1132 Kidney International (2022) 101, 1126–1141 Genetics in CKD Conference Participants: A KDIGO report KDIGO executive conclusions frequent primary kidney disorders, such as IgA nephropathy, of EHR and genetic data also can be used to investigate membranous nephropathy, and steroid-sensitive nephrotic pleiotropic associations of genetic variants originally discov- syndrome, aggregating multiple international case–control ered for a specific condition (e.g., APOL1 or UMOD) with cohorts is even more important to assure adequate power. additional traits captured in medical records using phenome- Additionally, more diverse ancestral composition of analyzed wide association approaches.14,26,42,130 Such studies can be cohorts facilitates fine-mapping of GWAS loci, enables dis- further complemented with Mendelian randomization covery of ancestry-specific effects, and assures broader methods to clarify associations between genetic variants, generalizability of genetic findings. biomarkers, and phenotypes.131 The identification of causal genes and variants underlying Despite the large size of consortia and EHR-linked studies, GWAS associations and definition of their pleiotropic effects certain groups of patients are still underrepresented in genetic are recognized as important challenges in the field. Examples research. For instance, the paucity of pediatric patients with such as UMOD, the locus with the strongest common variant genetic information has limited both longitudinal phenotype association with CKD,66 support the existence of a spectrum analyses from childhood to adulthood and the ability to of risk variants, from monogenic to complex. No examples identify genetic drivers of kidney diseases or traits of child- currently exist of successful translation of insights from hood. Also, there is urgent need to expand ancestral diversity GWAS in CKD to new therapies, but the discovery of the of participants in genetic studies, specifically aiming to in- MYH9 locus,114,115 followed by the identification of APOL1 as crease the representation of non-European populations.132 the causal gene,69 refinement of nephrotoxic mechanisms of Additional challenges include harmonizing data for rare APOL1 risk variants,89 and an ongoing phase IIa study of a kidney conditions that necessitate aggregating cases from small molecule APOL1 inhibitors (ClinicalTrials.gov identifier across several biobanks and EHRs; identifying ancestry- NCT04340362) represent promising steps toward that end. matched controls for case–control analyses; handling of Conference participants recognized the emerging impor- missing data; and harmonizing genotypes in the presence of tance of electronic health record (EHR)-based genetic different types of available genetic data.133,134 research for linking genetic information with a wide range of Partnerships between academic labs and industry allow laboratory parameters and medical conditions. EHR-linkage efficient exchange of ideas and resources to promote inves- is possible in various settings, ranging from existing bio- tigation of disease mechanisms, biomarkers, and therapeutic banks in research settings, hospitals, or healthcare systems to targets. Such partnerships can enable academic labs, bio- entire countries, such as Iceland, Estonia, and Finland. Ex- banks, and institutions and healthcare systems to conduct amples of EHR-linked biobanks, institutions, healthcare sys- large-scale multi-omic studies that would not be feasible with tems, and country-wide efforts are UK Biobank,116 Million only support from internal funds or extramural grants, and Veteran Program (MVP),117 HUNT Biobank,118 deCODE,119 facilitate follow-up studies to “functionalize” key genes or FinnGen,60 BioBank Japan (BBJ),120 Vanderbilt University genetic variants. Successful partnerships must achieve a bal- biobank (BioVU),121 Michigan Genomics Initiative (MGI),122 ance between companies’ incentive to invest and academics’ Electronic Medical Records and Genomics (eMERGE) freedom in research and publishing. Key principles and Network,123 and the National Institutes of Health All of Us processes, such as intellectual property, publications, and data Research Program.124 The development of standardized, sharing and access, also must be aligned. These partnerships scalable, and portable computable phenotypes is time have been particularly valuable for generating functional consuming and represents many challenges,125 but it can genomic data from primary kidney tissues and allow for rapid empower future genetic studies by automated identification of implementation of new methods.135–138 Generation of addi- kidney-disease patients in large EHR databases.26,126 Notably, tional such data from primary kidney tissue and cell types just as important as accurately defining those with a disease is should continue to be a research priority because the kidney defining those without to serve as healthy controls in genetic is underrepresented in many existing public databases, studies, which is often harder. We envision that computable including the Encyclopedia of DNA Elements (ENCODE),139 phenotyping can be used to find patients with or without Roadmap Epigenomics,140 and the Genotype-Tissue Expres- CKD, hypertension, kidney stones, and glomerular disease, as sion (GTEx) project.141 The Kidney Precision Medicine well as patients who have received a kidney biopsy or kidney Project (KPMP)142 and similar new initiatives aim to address transplant. In nephrology, computable phenotyping is un- some of these important gaps by generating and harmonizing derway,26,127–129 with CKD phenotyping perhaps best posi- new multidimensional molecular data for human kidney tioned for widespread implementation, given the availability tissue in health and disease. of new algorithms based on International Classification of Polygenic scores. Polygenic scores (PGSs) are based on Diseases codes and laboratory values that are routinely the results of GWAS and aggregate the effects of trait- or measured in clinical practice.26,126 disease-associated variants across the genome. PGSs capture In addition to genomic discovery, EHR-linked genetic a greater proportion of genetic variance compared to indi- research may allow for recontacting of patients with a specific vidual SNPs and potentially may be useful to risk-stratify genotype for detailed clinical and molecular studies. Linking populations, enhance screening, and ultimately inform Kidney International (2022) 101, 1126–1141 1133 KDIGO executive conclusions Genetics in CKD Conference Participants: A KDIGO report diagnosis, prognosis, and/or treatment. PGSs have been indeed, fellows report lacking competency in genetic renal shown to modify the penetrance of monogenic variants for disease.148 Similarly, in Australia, less than half of ne- hypercholesterolemia, hereditary breast and colon cancer, phrologists feel confident in using results of genomic and obesity,32,33 although this effect has not yet been testing in clinical practice.149 No genetics core competency examined for kidney diseases. PGSs for kidney disease can be guidelines are in place for nephrologists, nor are guide- constructed using a smaller set of genome-wide significant lines for evaluating competencies for clinical genetic SNPs only, such as a 147-SNP score for eGFR (odds ratio of consent and return of results. Based on published data w2 for individuals in the highest 10% of the score)13 or a 5- and information,150 a compiled list of core competencies SNP score for membranous nephropathy (odds ratio of >20 expected from nephrologists at different levels of expertise for those in the highest 10% of the score),19 or by using can be found in Supplementary Table S2. These gaps can genome-wide scores with hundreds of thousands of variants, be remedied by including more robust genetics curricula such as the UK Biobank score for CKD.91 Currently, most in medical school, residency, and fellowship training. Ed- scores are derived from European populations and do not ucation for current practicing nephrologists can be ach- include rare or population-specific variation, potentially ieved via workshops at national and international societies, creating a new health disparity between individuals of Eu- continuing medical education, review papers in ropean descent and others.132 Given that scores are con- nephrology journals, and introduction of clinical genetic structed from GWAS for complex traits and diseases, they questions to relicensing tests.151 One can also envision an may reflect heterogeneous mechanisms and therefore may advanced training or subspecialty track in genetic not necessarily point to targeted interventions. nephrology, similar to transplant, oncology, or glomerular Conference participants agreed that before applying PGSs diseases subspecialization. Supplementary Table S1 pro- in clinical nephrology, more research is needed to derive the vides an overview of clinical genetics web resources to aid most accurate and cosmopolitan scores for kidney disease. nephrologists. Also necessary are the following: proof of clinical utility in Clinical practice. Centers of expertise are sites where surveillance, diagnosis, prognosis, or treatment of kidney patients can receive comprehensive, coordinated care from disease; a better understanding of dependence on the clinical a multidisciplinary team that includes a relatively small context, including disease stage, ancestry, sex, or de- number of nephrologists with a high skill set for genetic mographics143; and cost-effectiveness and added value beyond diagnosis (Figure 6). These centers also play an important standard clinical risk factors. PGS computation needs to be role in training and research. Centers of expertise, or robust, open-source, and able to be incorporated into points reference, are concentrated in Europe, with ERKNet of care. Quality standards for PGSs have recently been defined constituting a consortium of more than 30 centers in 12 by ClinGen,144–146 providing a framework for evaluating countries, supported by the European Union. In most clinical translation and utility. regions of the globe, including the US, no centralized accreditation mechanisms are in place for developing Achieving implementation in clinical medicine centers of expertise or reference. The establishment of Clinical knowledge. Often, insufficient experience and such centers can facilitate standardized variant interpre- knowledge are major barriers for implementing genetic tation, identify “actionable” genes associated with kidney evaluation in nephrology practice. To ensure equitable ac- diseases, train the future generation of physicians with cess to genetic testing, all nephrologists should have a dual expertise in genetics and nephrology, develop sufficient knowledge base for discerning which patients guidelines for referral and testing of patients with kidney would benefit from genetic testing, and at minimum, be diseases, disseminate implementation knowledge, and able to collect personal and family histories. Although develop collaborative research projects and clinical trials optimally all nephrologists would be able to recommend for rare disorders. screening for at-risk family members if applicable, would Cost and access. Often, genetic testing is not affordable conceptually understand types of genetic tests, including for either patients or healthcare systems. In regions with cost their risks and benefits, and would remain aware of local coverage or reimbursement, access can still be unequal, as regulations around genetic testing, those who lack experi- genetic testing is based on clinical presentation, and obtaining ence in these domains should collaborate with a clinical coverage is often easier in children than in adults. Many geneticist and/or a genetic counselor. In addition, reporting countries do have genetic protection acts, laws, or regulations of positive genetic results to patients necessitates individual to ensure equitable access to genetic testing without fear of and family counseling and referrals. Hence, a multidisci- discrimination. However, legislation alone is not always suf- plinary approach is key for successfully implementing use ficient for allaying patient concerns about the potential for of genetics in the clinic. prejudice. Conference participants recognized workforce education Logistically, remote sample collection and telemedicine as a critical need. Genetics is currently not part of the have potential for increasing access to genetic counseling. nephrology fellowship curriculum in the US,147 and However, adequate physical evaluation and identification of 1134 Kidney International (2022) 101, 1126–1141 Genetics in CKD Conference Participants: A KDIGO report KDIGO executive conclusions Clinic type Number of nephrologists Knowledge level Source of knowledge Centers of expertise Few High Advanced training and (multidisciplinary teams) subspecialties and extensive clinical experience Connections with geneticists As many CME courses, workshops Medium and genetic counselors as possible and heuristically based All nephrology Medical school/ clinics All Basic fellowships/licensing Figure 6 | Proposed organization for implementing genetics in nephrology. Within a health system, multiple center types, provider specialties, and education strategies are needed for optimal implementation of genetics in nephrology. A 3-tiered organization model includes the following: (i) a basic, common level of knowledge in genetics among all nephrologists; (ii) clinical connections between nephrologists and geneticists and genetic counselors; and (iii) centers of expertise where nephrologists with genetic expertise collaborate with geneticists and genetic counselors. CME, continuing medical education. extrarenal manifestations can be more complicated or on long-term outcomes and health economics. A compar- impossible with telemedicine. In addition, although the ison of the cost-effectiveness of genetic testing in severe acute respiratory syndrome coronavirus-2 (SARS- nephrology across different healthcare coverage systems CoV-2) pandemic has accelerated the deployment of tele- could provide key insights and an evidence base for medicine across many health systems, not all patients and expanding testing. physicians are comfortable with remote, video-based Patient voice. Patient engagement is vital for successful communications. treatment and advances in research. To advocate for their own For most genetic conditions, we lack large-scale cost- genetic testing, patients need to have an awareness of and effectiveness analyses to demonstrate the benefits of genetic education regarding genetics and kidney disease and the testing. Recent data suggest that genetic testing has a high relative benefits and risks of genetic testing.152 The complex diagnostic yield in patients with CKD of unknown etiology ethical, psychosocial, and familial implications for genetic and may reduce costly diagnostic workups, hopefully testing, including presymptomatic testing, can make decision- increasing the coverage of genetic testing for those pa- making challenging and require an understanding of patient tients.3,8 Also important is the demonstration of the clinical values, goals, and priorities.153 To engage and activate patients value of genetic testing beyond diagnosis, such as its impact and patient communities, educational content needs to be Table 5 | Recommended practices for value-based measures of implementation and quality assurance of clinical genetics in nephrology Measure nephrologist adoption of genetic testing and appropriate referral to genetic testing Measure nephrologist utilization of genetic results (to determine if appropriate changes in diagnosis and care have occurred) Define disease-specific outcomes that can be measured  Development of kidney failure  Rate of kidney disease progression  Change in treatment  Access to genetically stratified clinical trials  Donor risk evaluation, or deceased-donor organ evaluation  Recipient risk evaluation (e.g., improved matching, customized immunosuppression, etc.)  Utilization of information for family planning  Patient-reported outcome (quality of life, etc.)  Hospitalization, cardiovascular outcomes, mortality  Diagnosis of at-risk family members Define and measure potential harmful impacts of genetic testing (e.g., wrongful impact on change of treatment) Define audits/assessments for centers that offer genetic testing in nephrology as quality-assurance activity Potentially apply USPSTF and EGAPP methods to analyze the implementation of genetic testing for kidney diseases USPSTF, United States Preventive Services Task Force; EGAPP, Evaluation of Genomic Applications in Practice and Prevention. Kidney International (2022) 101, 1126–1141 1135 KDIGO executive conclusions Genetics in CKD Conference Participants: A KDIGO report accessible and sensitive to patients in terms of culture, lan- Goldstein36,37, Morgan E. Grams38, Anna Greka14,15, Oliver Gross39, Lisa M. Guay-Woodford40, Peter C. Harris41, Julia Hoefele42, Adriana M. Hung43, guage, and literacy, as well as be shared across multiple Nine V.A.M. Knoers44, Jeffrey B. Kopp45, Matthias Kretzler46,47, Matthew platforms.154 B. Lanktree48,49, Beata S. Lipska-Ziętkiewicz50, Kathleen Nicholls51, Kandai The topics of race and ancestry have been widely debated Nozu52, Akinlolu Ojo53, Afshin Parsa54,55, Cristian Pattaro56, York Pei57, Martin R. Pollak58, Eugene P. Rhee59, Simone Sanna-Cherchi60, Judy Savige61, John A. in genetics, as well as nephrology.155–158 In specific terms, race Sayer62,63,64, Francesco Scolari65,66, John R. Sedor67,68,69, Xueling Sim70, Stefan is a social, categorical construct, whereas ancestry is based on Somlo71,72, Katalin Susztak73,74, Bamidele O. Tayo75, Roser Torra76, Albertien M. inherited genetic variants without categorization. In principle, van Eerde77, André Weinstock78, Cheryl A. Winkler79, Matthias Wuttke1, Hong Zhang80,81, Jennifer M. King82, Michael Cheung83, Michel Jadoul84, Wolfgang C. genetics research is agnostic to race,157 and identifying Winkelmayer85 and Ali G. Gharavi5 disease-causing variants could obviate reliance on race or 1 Institute of Genetic Epidemiology, Faculty of Medicine and Medical ancestry as a proxy for probability of carrying a risk Center, University of Freiburg, Freiburg, Germany; 2Univ Brest, INSERM UMR 1078, GGB, CHU Brest, Brest, France; 3Division of Nephrology, Department of allele.132,158 Internal Medicine, University Hospital Leipzig, Leipzig, Germany; 4Department Within nephrology, patient-reported outcome measures of Nephrology and Medical Intensive Care, Charité—Universitätsmedizin Berlin, can provide doctors, investigators, and policymakers with Berlin, Germany; 5Division of Nephrology and Center for Precision Medicine and Genomics, Department of Medicine, Columbia University Irving Medical important insights into patient symptoms and experiences Center, New York, New York, USA; 6Institute for Molecular Bioscience (IMB), The that cannot be identified through laboratory or imaging University of Queensland, Brisbane, Queensland, Australia; 7Department of studies alone.159 Research communities that engage with pa- Nephrology, Townsville University Hospital, Townsville, Queensland, Australia; 8 College of Medicine, James Cook University, Townsville, Queensland, Australia; tients and include the patient voice can better advocate for 9 KidGen Collaborative, Australian Genomics Health Alliance, Melbourne, more research and development in rare kidney diseases. Victoria, Australia; 10Division of Nephrology, Department of Pediatrics and Research in implementation. Evidence-based frameworks Medicine, Hospital for Sick Children, University Health Network, University of Toronto, Toronto, Ontario, Canada; 11Division of Nephrology, Women’s College for evaluating quality of care in genetic testing have been put Hospital, Toronto, Ontario, Canada; 12Dalla Lana School of Public Health, and forth by ACMG,160 ERKNet, and others.161,162 These frame- Health Policy, Management and Evaluation, University of Toronto, Toronto, works cover different methods for evaluating the analytic and Ontario, Canada; 13Division of Nephrology, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA; 14Kidney Disease clinical validity, as well as the clinical utility, of genetic tests. Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Nephrology outcomes used in clinical trials have included 15 Department of Medicine, Brigham and Women’s Hospital, Harvard Medical those that are disease-specific or represent more general School, Boston, Massachusetts, USA; 16Division of Nephrology, University of Mississippi Medical Center, Jackson, Mississippi, USA; 17Laboratory of longer-term outcomes, such as kidney failure, cardiovascular Hereditary Kidney Disease, Imagine Institute, INSERM U1163, Université de death, or mortality, which require large datasets. Yet this space Paris, Paris, France; 18Department of Genetics, Necker Hospital, APHP, Paris, is evolving, as demonstrated by development of novel trial France; 19Molecular Biology Laboratory, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB-Sant Pau), Universitat Autònoma de designs using Bayesian methodology, inclusion of patient- Barcelona, Barcelona, Catalonia, Spain; 20Medizinische Genetik Mainz, Limbach reported outcomes, and additional economic evaluation of Genetics, Mainz, Germany; 21Department of Nephrology, Faculty of Medicine genetic risk. Steps for expanding measures to best inform and Medical Center, University of Freiburg, Freiburg, Germany; 22Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina, value-based implementation and quality assurance of clinical USA; 23Renal Unit, Great Ormond Street Hospital for Children, NHS Foundation genetics in nephrology are listed in Table 5. This large and Trust, London, UK; 24Department of Renal Medicine, University College London, critical space underpins clinical translation and mainstream- London, UK; 25Division of Nephrology, Cliniques Universitaires Saint-Luc, Brussels, Belgium; 26Institut de Recherche Expérimentale et Clinique, UCLou- ing, with much research and work anticipated in the coming vain, Brussels, Belgium; 27Department of Physiology, Mechanisms of Inherited years. Kidney Disorders Group, University of Zurich, Zurich, Switzerland; 28Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; 29Diabetes Unit and Center for Conclusions Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, This KDIGO Controversies Conference on Genetics in USA; 30Department of Medicine, Harvard Medical School, Boston, Massachu- Chronic Kidney Disease discussed many technical, logistical, setts, USA; 31The Voice of the Patient, Inc., Elmhurst, Illinois, USA; 32Department of Epidemiology, Gillings School of Global Public Health, University of North ethical, and/or research questions related to the definition and Carolina, Chapel Hill, North Carolina, USA; 33Division of Nephrology, Endocri- epidemiology of monogenic and complex kidney diseases, nology and Metabolism, Tokai University School of Medicine, Isehara, Japan; 34 applications of genetic findings in clinical medicine, and Rare Renal Disease Registry, UK Renal Registry, Bristol, UK; 35Department of Pediatrics, Division of Nephrology, Duke University Medical Center, Durham, utilization of genomics for defining and stratifying CKD. North Carolina, USA; 36Institute for Genomic Medicine, Columbia University, Identified areas of consensus and future research priorities New York, New York, USA; 37Department of Genetics and Development, provide a roadmap toward realizing the promises of genomic Columbia University, New York, New York, USA; 38Department of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; medicine for nephrology. 39 Clinic for Nephrology and Rheumatology, University Medical Center Göttin- gen, Göttingen, Germany; 40Center for Translational Science, Children’s Na- tional Health System, Washington, DC, USA; 41Division of Nephrology and APPENDIX Hypertension, Mayo Clinic, Rochester, Minnesota, USA; 42Institute of Human KDIGO Conference Participants Genetics, Klinikum rechts der Isar, Technical University of Munich, School of Anna Köttgen1, Emilie Cornec-Le Gall2, Jan Halbritter3,4, Krzysztof Kiryluk5, Medicine, Munich, Germany; 43VA Tennessee Valley Healthcare System, Divi- Andrew J. Mallett6,7,8,9, Rulan S. Parekh10,11,12, Hila Milo Rasouly5, Matthew G. sion of Nephrology and Hypertension, Department of Medicine, Vanderbilt Sampson13,14,15, Adrienne Tin16, Corinne Antignac17,18, Elisabet Ars19, Carsten Center for Kidney Disease, Vanderbilt Precision Nephrology Program, Vander- Bergmann20,21, Anthony J. Bleyer22, Detlef Bockenhauer23,24, Olivier bilt University Medical Center, Nashville, Tennessee, USA; 44Department of Devuyst25,26,27, Jose C. Florez28,29,30, Kevin J. Fowler31, Nora Franceschini32, Genetics, University Medical Center Groningen, Groningen, The Netherlands; 45 Masafumi Fukagawa33, Daniel P. Gale24,34, Rasheed A. Gbadegesin35, David B. Kidney Disease Section, National Institute of Diabetes and Digestive and 1136 Kidney International (2022) 101, 1126–1141 Genetics in CKD Conference Participants: A KDIGO report KDIGO executive conclusions Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, Mary- fees for expert testimony from Alexion, Kyowa Kirin, PTC, and Sanofi; research land, USA; 46Department of Internal Medicine, Division of Nephrology, Uni- support from Limbach Gruppe University of Freiburg; fees for speakers bureaus versity of Michigan, Ann Arbor, Michigan, USA; 47Department of Computational from Alexion, Kyowa Kirin, PTC, and Sanofi; fees for manuscript preparation Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, from PTC; and fees for the development of education presentations from USA; 48Division of Nephrology, St. Joseph’s Healthcare Hamilton, Hamilton, Alexion, Kyowa Kirin, PTC, and Sanofi. AJB has declared receiving consultant Ontario, Canada; 49Department of Medicine, McMaster University, Hamilton, fees from Horizon and fees for speakers bureaus from Natera. DB has declared Ontario, Canada; 50Rare Diseases Centre and Clinical Genetics Unit, Department receiving consultant fees from Avrobio and fees for speakers bureaus from of Biology and Medical Genetics, Medical University of Gdansk, Gdansk, Poland; Advicenne and Recordati. JCF has declared receiving consultant fees from 51 Department of Nephrology, Royal Melbourne Hospital, University of Mel- AstraZeneca; research support from NovoNordisk; and fees for speakers bourne, Parkville, Victoria, Australia; 52Department of Pediatrics, Kobe Univer- bureaus from AstraZeneca, Merck, and NovoNordisk. KJF has declared sity Graduate School of Medicine, Kobe, Japan; 53University of Kansas School of receiving consultant fees from Akebia, Bayer, eGenesis, Gilead, Hansa Medicine, Kansas City, Kansas, USA; 54Division of Kidney, Urologic and Hema- BioPharma, Natera, Palladio Biosciences, Responsum CKD, Talaris Therapeutics, tologic Diseases, National Institute of Diabetes and Digestive and Kidney Dis- Travere Therapeutics, and Veloxis. NF has declared receiving research support eases, National Institutes of Health, Bethesda, Maryland, USA; 55Department of from the NIH. MF has declared receiving research support from Kyowa Kirin Medicine, University of Maryland School of Medicine, Baltimore, Maryland, and fees for speakers bureaus from AstraZeneca and Kyowa Kirin. DPG has USA; 56Eurac Research, Institute for Biomedicine (affiliated with the University declared receiving consultant fees from Alexion, Atlas Venture, Judo Bio, and of Lübeck), Bolzano, Italy; 57Division of Nephrology, University Health Network, Reata; fees for speakers bureaus from Travere Therapeutics; and being a Toronto, Ontario, Canada; 58Division of Nephrology, Beth Israel Deaconess trustee for AlportUK. RAG has declared receiving consultant fees and research Medical Center, Harvard Medical School, Boston, Massachusetts, USA; 59Divi- support from Reata and Travere Therapeutics. DBG has declared receiving sion of Nephrology, Department of Medicine, Massachusetts General Hospital, consultant fees from AstraZeneca, Gilead Sciences, Goldfinch Bio, and Boston, Massachusetts, USA; 60Division of Nephrology, Department of Medi- Gossamer Bio; employment from Actio Biosciences; and stock from Actio cine, Columbia University, New York, New York, USA; 61Department of Medi- Biosciences, Apostle Inc., Praxis Therapeutics, and Q-State Biosciences. AG has cine, Melbourne and Northern Health, The University of Melbourne, Parkville, declared receiving consultant fees from Atlas Venture, Biogen, Blackstone, Victoria, Australia; 62Translational and Clinical Research Institute, Faculty of Bristol Myers Squibb, Cyclerion, Goldfinch Bio, Kyn Therapeutics, Lycia Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; 63The Therapeutics, Maze, MPM, Novartis, Ono Pharmaceutical, Q32 Bio, and Patient Newcastle upon Tyne NHS Hospitals Foundation Trust, Newcastle upon Tyne, Square Capital. OG has declared receiving consultant fees from Bayer AG, UK; 64NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne, UK; Boehringer Ingelheim, Codon-X Therapeutics Inc., Galapagos, Novartis, Ono 65 Division of Nephrology, ASST Spedali Civili di Brescia, Brescia, Italy; Pharmaceutical Co. Ltd., Reata, Roche, and Sanofi US Services Inc./Genzyme/ 66 Department of Medical and Surgical Specialties, University of Brescia, Brescia, Regulus Therapeutics; research support from Bayer AG (Germany), Boehringer Italy; 67Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA; Ingelheim (Germany), German Ministry of Education and Research, and 68 Glickman Urological & Kidney Institute, Cleveland Clinic, Cleveland, Ohio, German Research Foundation; and travel expenses from AstraZeneca. LMG-W USA; 69Department of Physiology and Biophysics, Case Western Reserve Uni- has declared receiving consultant fees from Natera and Otsuka. PCH has versity, Cleveland, Ohio, USA; 70Saw Swee Hock School of Public Health, Na- declared receiving consultant fees from Mitobridge, Otsuka, Regulus, and tional University of Singapore and National University Health System, Vertex; and research support from Acceleron, Jemincare, Navitor, and Otsuka. Singapore, Singapore; 71Department of Internal Medicine, Yale University, New AMH has declared being a board member for Vertex and research support Haven, Connecticut, USA; 72Department of Genetics, Yale University, New Ha- from Veterans Health CSR&D Merit Grant CX001897. NVAMK has declared ven, Connecticut, USA; 73Department of Medicine, Perelman School of Medi- receiving research support from Health Holland. JBK has declared receiving cine, University of Pennsylvania, Philadelphia, Pennsylvania, USA; research support from the NIH Intramural Research Program. MK has declared 74 Department of Genetics, Perelman School of Medicine, University of Penn- receiving consultant fees from Astellas, Janssen, and Poxel; and research sylvania, Philadelphia, Pennsylvania, USA; 75Department of Public Health Sci- support from amfAR, Angion Pharmaceuticals, AstraZeneca, Boehringer ences, Loyola University Chicago, Maywood, Illinois, USA; 76Inherited Kidney Ingelheim, Certa, the Chan Zuckerberg Initiative, Chinook, Eli Lilly, European Disorders, Nephrology Department, Fundació Puigvert, IIB-Sant Pau, Universitat Union Innovative Medicine Initiative, Gilead, Goldfinch Bio, Ionis Autónoma de Barcelona, Barcelona, Spain; 77Department of Genetics, Univer- Pharmaceuticals, Janssen, JDRF, Moderna, NovoNordisk, Regeneron, sity Medical Center Utrecht, Utrecht, The Netherlands; 78Alport Syndrome RenalytixAI, and Travere Therapeutics. MBL has declared receiving consultant Foundation, Phoenix, Arizona, USA; 79Basic Research Laboratory, Molecular fees from Bayer, Otsuka, Reata, and Sanofi Genzyme; and fees for speakers Genetic Epidemiology Section, Frederick National Laboratory for Cancer bureaus from Bayer, Otsuka, Reata, and Sanofi Genzyme. BSL-Z has declared Research, National Cancer Institute, Frederick, Maryland, USA; 80Renal Division, receiving fees for speakers bureaus from Takeda Pharma PL and fees for the Peking University First Hospital, Beijing, China; 81Key Laboratory of Renal Dis- development of educational presentations from Takeda Pharma PL. KNi has ease, Ministry of Health of China, Beijing, China; 82August Editorial, Durham, declared being a board member for Amicus Australian, Sanofi Genzyme, and North Carolina, USA; 83KDIGO, Brussels, Belgium; 84Cliniques Universitaires Takeda; receiving research support from Genzyme and Takeda; and fees for the Saint Luc, Université Catholique de Louvain, Brussels, Belgium; 85Selzman development of educational presentations from Takeda. KNo has declared Institute for Kidney Health, Section of Nephrology, Department of Medicine, receiving fees for speakers bureaus from Daiichi Sankyo, Kyowa Kirin, and Baylor College of Medicine, Houston, Texas, USA Sumitomo Dainippon Pharma. AO has declared receiving consultant fees from Conference Co-Chairs: Anna Köttgen, Ali G. Gharavi Vertex. YP has declared receiving consultant fees from Maze, Otsuka, Reata, and Sanofi; and fees for the development of educational presentations from Steering Committee Members: Emilie Cornec-Le Gall, Jan Halbritter, Otsuka. MRP has declared being a board member for Vertex; receiving Krzysztof Kiryluk, Andrew J. Mallett, Rulan S. Parekh, Hila Milo Rasouly, Matthew consultant fees from InxMed and Vertex, and research support from Vertex; G. Sampson, Adrienne Tin and stock/stock options from Apolo1Bio LLC. SS-C has declared receiving fees for speakers bureaus from Travere Therapeutics. JRS has declared being a DISCLOSURE board member for Kidney X Innovation Accelerator; receiving consultant fees AK has declared receiving research support from the German Research from Boehringer Ingelheim and Maze; and research support from Calliditas, Foundation (DFG) Project-ID 431984000 - SFB 1453. EC-LG has declared Novartis, and Vertex. SS has declared receiving consultant fees from Goldfinch receiving research support from Agence Nationale de la Recherche and Filière Bio and Vertex. KS has declared being a board member for Jnana; receiving Maladies Rares Rénales. RSP has declared receiving research support from the consultant fees from AstraZeneca, Bayer, GSK, Jnana, Maze, Otsuka, Pfizer, and Canadian Institutes of Health Research, National Institutes of Health (NIH), and Ventus; and research support from Bayer, Boehringer Ingelheim, Gilead, GSK, Ontario Ministry. MGS has declared being a board member for Natera; Jnana, Maze, NIH, Novartis, Novo Nordisk, and Regeneron. RT has declared receiving consultant fees from Janssen and Maze; and research support from receiving fees for speakers bureaus from Amicus, Otsuka, Sanofi, and Takeda. the NIH. AT has declared receiving fees for speakers bureaus from the AMvE has declared receiving research support from the Dutch Kidney University of Virginia, Division of Nephrology Grand Round. CA has declared Foundation (#18OKG19) and VriendenWKZ and being on Work Groups for having a patent on the NPHS2 gene encoding podocin (USOO7388O86B2) ERKNet (project ID No 739532) and ERA-EDTA. CAW has declared receiving licensed to Athena Diagnostics Inc (USA). CB has declared being a board federal funds from the National Cancer Institute, NIH, under contract member for Medizinische Genetik Mainz and Limbach Genetics GmbH; 75N91019D00024; and support in part by the Intramural Research Program of receiving consultant fees from Alexion, Kyowa Kirin, PTC, and Sanofi; the NIH, National Cancer Institute, Center for Cancer Research. JMK has employment from Medizinische Genetik Mainz and Limbach Genetics GmbH; declared receiving fees for manuscript preparation Bayer Pharmaceuticals, Kidney International (2022) 101, 1126–1141 1137 KDIGO executive conclusions Genetics in CKD Conference Participants: A KDIGO report Emergent Biosciences, and Gilead Sciences. MJ declared receiving consultant 7. Snoek R, van Jaarsveld RH, Nguyen TQ, et al. Genetics-first approach fees from Astellas, AstraZeneca, Boehringer Ingelheim, Fresenius Medical Care improves diagnostics of ESKD patients <50 years old. Nephrol Dial Asia Pacific, Mundipharma, and Vifor Fresenius Medical Care; fees for speakers Transplant. 2020;37:349–357. bureaus from Astellas, AstraZeneca, Mundipharma, and Vifor Fresenius Medical 8. Ottlewski I, Munch J, Wagner T, et al. Value of renal gene panel Care; research support from Amgen; and future research support from diagnostics in adults waiting for kidney transplantation due to AstraZeneca. WCW declared receiving consultant fees from Akebia/Otsuka, undetermined end-stage renal disease. Kidney Int. 2019;96:222–230. AstraZeneca, Bayer, Janssen, Merck, Reata, and Relypsa; future consultant fees 9. Connaughton DM, Kennedy C, Shril S, et al. Monogenic causes of from Boehringer Ingelheim; and research support from the NIH. AGG has chronic kidney disease in adults. Kidney Int. 2019;95:914–928. declared receiving consultant fees from Actio Biosciences, Natera, Novartis, 10. Snoek R, van Setten J, Keating BJ, et al. NPHP1 (Nephrocystin-1) gene and Travere; research support from Natera and the Renal Research Institute; deletions cause adult-onset ESRD. J Am Soc Nephrol. 2018;29:1772–1779. and fees for the development of educational presentations from Fresenius and 11. Kottgen A, Pattaro C, Boger CA, et al. New loci associated with kidney Sanofi Genzyme. Several authors of this paper are members of the European function and chronic kidney disease. Nat Genet. 2010;42:376–384. Rare Kidney Disease Reference Network (ERKNet)—project ID No 739532. All 12. Kanai M, Akiyama M, Takahashi A, et al. Genetic analysis of quantitative the other authors declared no competing interests. traits in the Japanese population links cell types to complex human diseases. Nat Genet. 2018;50:390–400. ACKNOWLEDGMENTS 13. Wuttke M, Li Y, Li M, et al. A catalog of genetic loci associated with This conference was sponsored by KDIGO and supported in part by kidney function from analyses of a million individuals. Nat Genet. unrestricted educational grants from American Kidney Fund, 2019;51:957–972. AstraZeneca, Chinook Therapeutics, Natera, Otsuka, Reata 14. Teumer A, Li Y, Ghasemi S, et al. Genome-wide association meta- Pharmaceuticals, and Sanofi. The content of this publication does not analyses and fine-mapping elucidate pathways influencing necessarily reflect the views or policies of the Department of Health albuminuria. Nat Commun. 2019;10:4130. and Human Services, nor does mention of trade names, commercial 15. Okada Y, Terao C, Ikari K, et al. Meta-analysis identifies nine new loci associated with rheumatoid arthritis in the Japanese population. Nat products, or organizations imply endorsement by the US Genet. 2012;44:511–516. government. 16. Morris AP, Le TH, Wu H, et al. Trans-ethnic kidney function association study reveals putative causal genes and effects on kidney-specific AUTHOR CONTRIBUTIONS disease aetiologies. Nat Commun. 2019;10:29. All Steering Committee Members contributed equally. The 17. Kiryluk K, Li Y, Scolari F, et al. Discovery of new risk loci for IgA conference planning and the drafting and critical revision of this nephropathy implicates genes involved in immunity against intestinal manuscript were performed by the Steering Committee Members, pathogens. Nat Genet. 2014;46:1187–1196. the Conference Co-Chairs, and Jennifer King, with important 18. Gharavi AG, Kiryluk K, Choi M, et al. Genome-wide association study identifies susceptibility loci for IgA nephropathy. Nat Genet. 2011;43: intellectual content contributions provided by the remaining 321–327. authors. 19. Xie J, Liu L, Mladkova N, et al. The genetic architecture of membranous nephropathy and its potential to improve non-invasive diagnosis. Nat SUPPLEMENTARY MATERIAL Commun. 2020;11:1600. Supplementary File (PDF) 20. Stanescu HC, Arcos-Burgos M, Medlar A, et al. Risk HLA-DQA1 and Table S1. Online clinical genetics resources to aid nephrologists. PLA(2)R1 alleles in idiopathic membranous nephropathy. N Engl J Med. Adapted with permission from Annals of Internal Medicine, Milo 2011;364:616–626. Rasouly H, Aggarwal V, Bier L, Goldstein DB, Gharavi AG. Cases in 21. Gbadegesin RA, Adeyemo A, Webb NJ, et al. HLA-DQA1 and PLCG2 are precision medicine: genetic testing to predict future risk for disease in candidate risk loci for childhood-onset steroid-sensitive nephrotic syndrome. J Am Soc Nephrol. 2015;26:1701–1710. a healthy patient, volume 174, issue 4, pages 540–547, Copyright ª 22. Dufek S, Cheshire C, Levine AP, et al. Genetic identification of two novel 2021 American College of Physicians. All Rights Reserved. Reprinted loci associated with steroid-sensitive nephrotic syndrome. J Am Soc with the permission of American College of Physicians, Inc.151 Nephrol. 2019;30:1375–1384. Table S2. Recommended competencies in genetic nephrology. 23. Jia X, Yamamura T, Gbadegesin R, et al. Common risk variants in NPHS1 Adapted from Tognetto A, Michelazzo MB, Ricciardi W, et al. Core and TNFSF15 are associated with childhood steroid-sensitive nephrotic competencies in genetics for healthcare professionals: results from a syndrome. Kidney Int. 2020;98:1308–1322. literature review and a Delphi method. BMC Med Educ. 2019;19:19150 24. Groopman EE, Rasouly HM, Gharavi AG. Genomic medicine for kidney disease. Nat Rev Nephrol. 2018;14:83–104. under the terms of the Creative Commons Attribution 4.0 25. Gale DP, Mallett A, Patel C, et al. Diagnoses of uncertain significance: International License (http://creativecommons.org/licenses/by/4.0/). kidney genetics in the 21st century. Nat Rev Nephrol. 2020;16:616–618. ª The Author(s) 2019. 26. Shang N, Khan A, Polubriaginof F, et al. Medical records-based chronic kidney disease phenotype for clinical care and “big data” observational REFERENCES and genetic studies. NPJ Digit Med. 2021;4:70. 1. GBD Chronic Kidney Disease Collaboration. Global, regional, and 27. Fox CS, Yang Q, Cupples LA, et al. Genomewide linkage analysis to national burden of chronic kidney disease, 1990-2017: a systematic serum creatinine, GFR, and creatinine clearance in a community-based analysis for the Global Burden of Disease Study 2017. Lancet. 2020;395: population: the Framingham Heart Study. J Am Soc Nephrol. 2004;15: 709–733. 2457–2461. 2. Rasouly HM, Groopman EE, Heyman-Kantor R, et al. The burden of 28. Mottl AK, Vupputuri S, Cole SA, et al. Linkage analysis of glomerular candidate pathogenic variants for kidney and genitourinary disorders filtration rate in American Indians. Kidney Int. 2008;74:1185–1191. emerging from exome sequencing. Ann Intern Med. 2019;170:11–21. 29. Langefeld CD, Beck SR, Bowden DW, et al. Heritability of GFR and 3. Groopman EE, Marasa M, Cameron-Christie S, et al. Diagnostic utility of albuminuria in Caucasians with type 2 diabetes mellitus. Am J Kidney exome sequencing for kidney disease. N Engl J Med. 2019;380:142–151. Dis. 2004;43:796–800. 4. Domingo-Gallego A, Pybus M, Bullich G, et al. Clinical utility of genetic 30. Ghosh S, Collins FS. The geneticist’s approach to complex disease. Annu testing in early-onset kidney disease: seven genes are the main players. Rev Med. 1996;47:333–353. Nephrol Dial Transplant. 2022;37:687–696. 31. Salem RM, Todd JN, Sandholm N, et al. Genome-wide association 5. Bullich G, Domingo-Gallego A, Vargas I, et al. A kidney-disease gene study of diabetic kidney disease highlights biology involved in panel allows a comprehensive genetic diagnosis of cystic and glomerular basement membrane collagen. J Am Soc Nephrol. glomerular inherited kidney diseases. Kidney Int. 2018;94:363–371. 2019;30:2000–2016. 6. Mallett A, Patel C, Salisbury A, et al. The prevalence and epidemiology 32. Akbari P, Gilani A, Sosina O, et al. Sequencing of 640,000 exomes of genetic renal disease amongst adults with chronic kidney disease in identifies GPR75 variants associated with protection from obesity. Australia. Orphanet J Rare Dis. 2014;9:98. Science. 2021;373:eabf8683. 1138 Kidney International (2022) 101, 1126–1141 Genetics in CKD Conference Participants: A KDIGO report KDIGO executive conclusions 33. Fahed AC, Wang M, Homburger JR, et al. Polygenic background 56. Stafford-Smith M, Li YJ, Mathew JP, et al. Genome-wide association modifies penetrance of monogenic variants for tier 1 genomic study of acute kidney injury after coronary bypass graft surgery conditions. Nat Commun. 2020;11:3635. identifies susceptibility loci. Kidney Int. 2015;88:823–832. 34. Levey AS, de Jong PE, Coresh J, et al. The definition, classification, and 57. Purdue MP, Ye Y, Wang Z, et al. A genome-wide association study of prognosis of chronic kidney disease: a KDIGO Controversies Conference renal cell carcinoma among African Americans. Cancer Epidemiol report. Kidney Int. 2011;80:17–28. Biomarkers Prev. 2014;23:209–214. 35. Kidney Disease: Improving Global Outcomes. KDIGO 2012 clinical 58. Hernandez-Fuentes MP, Franklin C, Rebollo-Mesa I, et al. Long- and practice guideline for the evaluation and management of chronic short-term outcomes in renal allografts with deceased donors: a large kidney disease. Kidney Int Suppl. 2013;3:1–150. recipient and donor genome-wide association study. Am J Transplant. 36. Mann N, Braun DA, Amann K, et al. Whole-exome sequencing enables a 2018;18:1370–1379. precision medicine approach for kidney transplant recipients. J Am Soc 59. Stapleton CP, Heinzel A, Guan W, et al. The impact of donor and Nephrol. 2019;30:201–215. recipient common clinical and genetic variation on estimated 37. van der Ven AT, Connaughton DM, Ityel H, et al. Whole-exome glomerular filtration rate in a European renal transplant population. Am sequencing identifies causative mutations in families with congenital J Transplant. 2019;19:2262–2273. anomalies of the kidney and urinary tract. J Am Soc Nephrol. 2018;29: 60. Locke AE, Steinberg KM, Chiang CWK, et al. Exome sequencing of 2348–2361. Finnish isolates enhances rare-variant association power. Nature. 38. Stessman HA, Bernier R, Eichler EE. A genotype-first approach to 2019;572:323–328. defining the subtypes of a complex disease. Cell. 2014;156:872– 61. Nanayakkara S, Senevirathna ST, Parahitiyawa NB, et al. Whole-exome 877. sequencing reveals genetic variants associated with chronic kidney 39. Sandholm N, Van Zuydam N, Ahlqvist E, et al. The genetic landscape of disease characterized by tubulointerstitial damages in North Central renal complications in type 1 diabetes. J Am Soc Nephrol. 2017;28: Region, Sri Lanka. Environ Health Prev Med. 2015;20:354–359. 557–574. 62. Weng PL, Majmundar AJ, Khan K, et al. De novo TRIM8 variants impair 40. Verbitsky M, Krithivasan P, Batourina E, et al. Copy number variant its protein localization to nuclear bodies and cause developmental analysis and genome-wide association study identify loci with large delay, epilepsy, and focal segmental glomerulosclerosis. Am J Hum effect for vesicoureteral reflux. J Am Soc Nephrol. 2021;32:805–820. Genet. 2021;108:357–367. 41. Scelo G, Purdue MP, Brown KM, et al. Genome-wide association study 63. Lin BM, Grinde KE, Brody JA, et al. Whole genome sequence analyses of identifies multiple risk loci for renal cell carcinoma. Nat Commun. eGFR in 23,732 people representing multiple ancestries in the NHLBI 2017;8:15724. trans-omics for precision medicine (TOPMed) consortium. EBioMedicine. 42. Hellwege JN, Velez Edwards DR, Giri A, et al. Mapping eGFR loci to the 2021;63:103157. renal transcriptome and phenome in the VA Million Veteran Program. 64. Benonisdottir S, Kristjansson RP, Oddsson A, et al. Sequence variants Nat Commun. 2019;10:3842. associating with urinary biomarkers. Hum Mol Genet. 2019;28: 43. Qian H, Kowalski MH, Kramer HJ, et al. Genome-wide association of 1199–1211. kidney traits in Hispanics/Latinos using dense imputed whole-genome 65. Guo J, Rackham OJL, Sandholm N, et al. Whole-genome sequencing of sequencing data: The Hispanic Community Health Study/Study of Finnish type 1 diabetic siblings discordant for kidney disease reveals Latinos. Circ Genom Precis Med. 2020;13:e002891. DNA variants associated with diabetic nephropathy. J Am Soc Nephrol. 44. Okuda H, Okamoto K, Abe M, et al. Genome-wide association study 2020;31:309–323. identifies new loci for albuminuria in the Japanese population. Clin Exp 66. Kottgen A, Glazer NL, Dehghan A, et al. Multiple loci associated with Nephrol. 2020;24:1–9. indices of renal function and chronic kidney disease. Nat Genet. 45. Gorski M, Tin A, Garnaas M, et al. Genome-wide association study of 2009;41:712–717. kidney function decline in individuals of European descent. Kidney Int. 67. Kasembeli AN, Duarte R, Ramsay M, et al. APOL1 risk variants are 2015;87:1017–1029. strongly associated with HIV-associated nephropathy in black South 46. Yun S, Han M, Kim HJ, et al. Genetic risk score raises the risk of Africans. J Am Soc Nephrol. 2015;26:2882–2890. incidence of chronic kidney disease in Korean general population- 68. Kopp JB, Nelson GW, Sampath K, et al. APOL1 genetic variants in focal based cohort. Clin Exp Nephrol. 2019;23:995–1003. segmental glomerulosclerosis and HIV-associated nephropathy. J Am 47. Langefeld CD, Comeau ME, Ng MCY, et al. Genome-wide association Soc Nephrol. 2011;22:2129–2137. studies suggest that APOL1-environment interactions more likely 69. Genovese G, Friedman DJ, Ross MD, et al. Association of trypanolytic trigger kidney disease in African Americans with nondiabetic ApoL1 variants with kidney disease in African Americans. Science. nephropathy than strong APOL1-second gene interactions. Kidney Int. 2010;329:841–845. 2018;94:599–607. 70. Riella C, Siemens TA, Wang M, et al. APOL1-associated kidney disease in 48. Parsa A, Kanetsky PA, Xiao R, et al. Genome-wide association of CKD Brazil. Kidney Int Rep. 2019;4:923–929. progression: The Chronic Renal Insufficiency Cohort Study. J Am Soc 71. Freedman BI, Langefeld CD, Andringa KK, et al. End-stage renal disease Nephrol. 2017;28:923–934. in African Americans with lupus nephritis is associated with APOL1. 49. Li M, Foo JN, Wang JQ, et al. Identification of new susceptibility loci for Arthritis Rheumatol. 2014;66:390–396. IgA nephropathy in Han Chinese. Nat Commun. 2015;6:7270. 72. Larsen CP, Beggs ML, Saeed M, et al. Apolipoprotein L1 risk variants 50. Genovese G, Tonna SJ, Knob AU, et al. A risk allele for focal segmental associate with systemic lupus erythematosus-associated collapsing glomerulosclerosis in African Americans is located within a region glomerulopathy. J Am Soc Nephrol. 2013;24:722–725. containing APOL1 and MYH9. Kidney Int. 2010;78:698–704. 73. Ekulu PM, Nkoy AB, Betukumesu DK, et al. APOL1 risk genotypes are 51. Iyengar SK, Sedor JR, Freedman BI, et al. Genome-wide association and associated with early kidney damage in children in Sub-Saharan Africa. trans-ethnic meta-analysis for advanced diabetic kidney disease: Family Kidney Int Rep. 2019;4:930–938. Investigation of Nephropathy and Diabetes (FIND). PLoS Genet. 2015;11: 74. Ekrikpo UE, Mnika K, Effa EE, et al. Association of genetic e1005352. polymorphisms of TGF-beta1, HMOX1, and APOL1 with CKD in Nigerian 52. Taira M, Imamura M, Takahashi A, et al. A variant within the FTO confers patients with and without HIV. Am J Kidney Dis. 2020;76:100–108. susceptibility to diabetic nephropathy in Japanese patients with type 2 75. Naik RP, Irvin MR, Judd S, et al. Sickle cell trait and the risk of ESRD in diabetes. PLoS One. 2018;13:e0208654. Blacks. J Am Soc Nephrol. 2017;28:2180–2187. 53. Guan M, Keaton JM, Dimitrov L, et al. Genome-wide association study 76. Mukamal KJ, Tremaglio J, Friedman DJ, et al. APOL1 genotype, kidney identifies novel loci for type 2 diabetes-attributed end-stage kidney and cardiovascular disease, and death in older adults. Arterioscler disease in African Americans. Hum Genomics. 2019;13:21. Thromb Vasc Biol. 2016;36:398–403. 54. Chung SA, Brown EE, Williams AH, et al. Lupus nephritis susceptibility 77. Tayo BO, Kramer H, Salako BL, et al. Genetic variation in APOL1 and loci in women with systemic lupus erythematosus. J Am Soc Nephrol. MYH9 genes is associated with chronic kidney disease among 2014;25:2859–2870. Nigerians. Int Urol Nephrol. 2013;45:485–494. 55. Howles SA, Wiberg A, Goldsworthy M, et al. Genetic variants of calcium 78. Foster MC, Coresh J, Fornage M, et al. APOL1 variants associate with and vitamin D metabolism in kidney stone disease. Nat Commun. increased risk of CKD among African Americans. J Am Soc Nephrol. 2019;10:5175. 2013;24:1484–1491. Kidney International (2022) 101, 1126–1141 1139 KDIGO executive conclusions Genetics in CKD Conference Participants: A KDIGO report 79. Grams ME, Rebholz CM, Chen Y, et al. Race, APOL1 risk, and eGFR 104. Klahr S. The modification of diet in renal disease study. N Engl J Med. decline in the general population. J Am Soc Nephrol. 2016;27: 1989;320:864–866. 2842–2850. 105. Eckardt KU, Barthlein B, Baid-Agrawal S, et al. The German Chronic 80. Chen TK, Coresh J, Daya N, et al. Race, APOL1 risk variants, and clinical Kidney Disease (GCKD) Study: design and methods. Nephrol Dial outcomes among older adults: the ARIC Study. J Am Geriatr Soc. Transplant. 2012;27:1454–1460. 2021;69:155–163. 106. Furth SL, Cole SR, Moxey-Mims M, et al. Design and methods of the 81. Peralta CA, Bibbins-Domingo K, Vittinghoff E, et al. APOL1 genotype Chronic Kidney Disease in Children (CKiD) prospective cohort study. and race differences in incident albuminuria and renal function decline. Clin J Am Soc Nephrol. 2006;1:1006–1015. J Am Soc Nephrol. 2016;27:887–893. 107. Querfeld U, Anarat A, Bayazit AK, et al. The Cardiovascular Comorbidity 82. Parsa A, Kao WH, Xie D, et al. APOL1 risk variants, race, and progression in Children with Chronic Kidney Disease (4C) Study: objectives, design, of chronic kidney disease. N Engl J Med. 2013;369:2183–2196. and methodology. Clin J Am Soc Nephrol. 2010;5:1642–1648. 83. Chen TK, Tin A, Peralta CA, et al. APOL1 risk variants, incident 108. ESCAPE Trial Group, Wuhl E, Trivelli A, et al. Strict blood-pressure proteinuria, and subsequent eGFR decline in Blacks with hypertension- control and progression of renal failure in children. N Engl J Med. attributed CKD. Clin J Am Soc Nephrol. 2017;12:1771–1777. 2009;361:1639–1650. 84. Friedman DJ, Pollak MR. Genetics of kidney failure and the evolving 109. Kottgen A, Pattaro C. The CKDGen Consortium: ten years of insights story of APOL1. J Clin Invest. 2011;121:3367–3374. into the genetic basis of kidney function. Kidney Int. 2020;97: 85. Watanabe A, Guaragna MS, Belangero VMS, et al. APOL1 in an ethnically 236–242. diverse pediatric population with nephrotic syndrome: implications in 110. Psaty BM, O’Donnell CJ, Gudnason V, et al. Cohorts for Heart and Aging focal segmental glomerulosclerosis and other diagnoses. Pediatr Research in Genomic Epidemiology (CHARGE) Consortium: design of Nephrol. 2021;36:2327–2336. prospective meta-analyses of genome-wide association studies from 5 86. Knoers N, Antignac C, Bergmann C, et al. Genetic testing in the cohorts. Circ Cardiovasc Genet. 2009;2:73–80. diagnosis of chronic kidney disease: recommendations for clinical 111. Fishman CE, Mohebnasab M, van Setten J, et al. Genome-wide practice. Nephrol Dial Transplant. 2022;37:239–254. study updates in the International Genetics and Translational 87. Rehm HL, Berg JS, Brooks LD, et al. ClinGen—the clinical genome Research in Transplantation Network (iGeneTRAiN). Front Genet. resource. N Engl J Med. 2015;372:2235–2242. 2019;10:1084. 88. ClinGen–Clinical Genome Resource. ClinGen complex disease PRS 112. Magi R, Horikoshi M, Sofer T, et al. Trans-ethnic meta-regression of reporting standards. Accessed April 21, 2021. https://clinicalgenome. genome-wide association studies accounting for ancestry increases org/docs/clingen-complex-disease-prs-reporting-standards/ power for discovery and improves fine-mapping resolution. Hum Mol 89. Friedman DJ, Pollak MR. APOL1 nephropathy: from genetics to clinical Genet. 2017;26:3639–3650. applications. Clin J Am Soc Nephrol. 2021;16:294–303. 113. Franceschini N, Morris AP. Genetics of kidney traits in worldwide 90. Surapaneni AL, Ballew SH, Coresh J, et al. APOL1 risk alleles, cardiac populations: the Continental Origins and Genetic Epidemiology markers, and risk of ESKD in African Americans: the Atherosclerosis Risk Network (COGENT) Kidney Consortium. Kidney Int. 2020;98:35–41. in Communities Study. Kidney Med. 2020;2:502–504. 114. Kao WH, Klag MJ, Meoni LA, et al. MYH9 is associated with nondiabetic 91. Sinnott-Armstrong N, Tanigawa Y, Amar D, et al. Genetics of 35 blood end-stage renal disease in African Americans. Nat Genet. 2008;40:1185– and urine biomarkers in the UK Biobank. Nat Genet. 2021;53:185–194. 1192. 92. Gordon EJ, Amomicronrtegui D, Blancas I, et al. African American living 115. Kopp JB, Smith MW, Nelson GW, et al. MYH9 is a major-effect risk donors’ attitudes about APOL1 genetic testing: a mixed methods study. gene for focal segmental glomerulosclerosis. Nat Genet. 2008;40: Am J Kidney Dis. 2018;72:819–833. 1175–1184. 93. Freedman BI, Burke W, Divers J, et al. Diagnosis, education, and care of 116. Sudlow C, Gallacher J, Allen N, et al. UK Biobank: an open access patients with APOL1-associated nephropathy: a Delphi consensus and resource for identifying the causes of a wide range of complex diseases systematic review. J Am Soc Nephrol. 2021;32:1765–1778. of middle and old age. PLoS Med. 2015;12:e1001779. 94. Fuentes F, Kopp JB. Launching APOLLO: the role of APOL1 genetic 117. Gaziano JM, Concato J, Brophy M, et al. Million Veteran Program: a variants in live- and deceased-donor kidney transplantation. Kidney Int mega-biobank to study genetic influences on health and disease. J Clin Rep. 2020;5:252–254. Epidemiol. 2016;70:214–223. 95. Richards S, Aziz N, Bale S, et al. Standards and guidelines for the 118. Krokstad S, Langhammer A, Hveem K, et al. Cohort profile: the HUNT interpretation of sequence variants: a joint consensus recommendation Study, Norway. Int J Epidemiol. 2013;42:968–977. of the American College of Medical Genetics and Genomics and the 119. Jonsson H, Sulem P, Kehr B, et al. Whole genome characterization of Association for Molecular Pathology. Genet Med. 2015:17405–17424. sequence diversity of 15,220 Icelanders. Sci Data. 2017;4:170115. 96. Ellard S, Baple EL, Callaway A, et al. Association for Clinical Genomic 120. Nagai A, Hirata M, Kamatani Y, et al. Overview of the BioBank Japan Science best practices guidelines for variant classification in rare Project: study design and profile. J Epidemiol. 2017;27:S2–S8. disease 2020. Accessed April 21, 2021. https://www.acgs.uk.com/ 121. Roden DM, Pulley JM, Basford MA, et al. Development of a large-scale media/11631/uk-practice-guidelines-for-variant-classification-v4-01-2020. de-identified DNA biobank to enable personalized medicine. Clin pdf Pharmacol Ther. 2008;84:362–369. 97. Furlano M, Martinez V, Pybus M, et al. Clinical and genetic features of 122. Graham SE, Nielsen JB, Zawistowski M, et al. Sex-specific and pleiotropic autosomal dominant Alport Syndrome: a cohort study. Am J Kidney Dis. effects underlying kidney function identified from GWAS meta-analysis. 2021;78:560–570.e1. Nat Commun. 2019;10:1847. 98. Biesecker LG, Adam MP, Alkuraya FS, et al. A dyadic approach to the 123. eMERGE Consortium. Lessons learned from the eMERGE Network: delineation of diagnostic entities in clinical genomics. Am J Hum Genet. balancing genomics in discovery and practice. HGG Adv. 2021;2:100018. 2021;108:8–15. 124. All of Us Research Program Investigators, Denny JC, Rutter JL, et al. The 99. Hamosh A, Amberger JS, Bocchini CA, et al. Response to Biesecker et al. “All of Us” Research Program. N Engl J Med. 2019;381:668–676. Am J Hum Genet. 2021;108:1807–1808. 125. Shang N, Liu C, Rasmussen LV, et al. Making work visible for electronic 100. Eckardt KU, Alper SL, Antignac C, et al. Autosomal dominant phenotype implementation: lessons learned from the eMERGE network. tubulointerstitial kidney disease: diagnosis, classification, and J Biomed Inform. 2019;99:103293. management—a KDIGO consensus report. Kidney Int. 2015;88:676–683. 126. Norton JM, Ali K, Jurkovitz CT, et al. Development and validation of a 101. Kottgen A, Kao WH, Hwang SJ, et al. Genome-wide association study for pragmatic electronic phenotype for CKD. Clin J Am Soc Nephrol. renal traits in the Framingham Heart and Atherosclerosis Risk in 2019;14:1306–1314. Communities Studies. BMC Med Genet. 2008;9:49. 127. Denburg MR, Razzaghi H, Bailey LC, et al. Using electronic health record 102. Feldman HI, Appel LJ, Chertow GM, et al. The Chronic Renal data to rapidly identify children with glomerular disease for clinical Insufficiency Cohort (CRIC) Study: design and methods. J Am Soc research. J Am Soc Nephrol. 2019;30:2427–2435. Nephrol. 2003;14(7 Suppl 2):S148–S153. 128. Chan L, Beers K, Yau AA, et al. Natural language processing of electronic 103. Appel LJ, Middleton J, Miller ER 3rd, et al. The rationale and design of health records is superior to billing codes to identify symptom burden the AASK cohort study. J Am Soc Nephrol. 2003;14:S166–S172. in hemodialysis patients. Kidney Int. 2020;97:383–392. 1140 Kidney International (2022) 101, 1126–1141 Genetics in CKD Conference Participants: A KDIGO report KDIGO executive conclusions 129. Zheng NS, Feng Q, Kerchberger VE, et al. PheMap: a multi-resource 148. Berns JS. A survey-based evaluation of self-perceived competency knowledge base for high-throughput phenotyping within electronic after nephrology fellowship training. Clin J Am Soc Nephrol. 2010;5: health records. J Am Med Inform Assoc. 2020;27:1675–1687. 490–496. 130. Bajaj A, Ihegword A, Qiu C, et al. Phenome-wide association analysis 149. Jayasinghe K, Quinlan C, Mallett AJ, et al. Attitudes and practices of suggests the APOL1 linked disease spectrum primarily drives kidney- Australian nephrologists toward implementation of clinical genomics. specific pathways. Kidney Int. 2020;97:1032–1041. Kidney Int Rep. 2021;6:272–283. 131. Tin A, Kottgen A. Mendelian randomization analysis as a tool to gain 150. Tognetto A, Michelazzo MB, Ricciardi W, et al. Core competencies in insights into causes of diseases: a primer. J Am Soc Nephrol. 2021;32: genetics for healthcare professionals: results from a literature review 2400–2407. and a Delphi method. BMC Med Educ. 2019;19:19. 132. Martin AR, Kanai M, Kamatani Y, et al. Clinical use of current polygenic risk 151. Milo Rasouly H, Aggarwal V, Bier L, et al. Cases in precision medicine: scores may exacerbate health disparities. Nat Genet. 2019;51:584–591. genetic testing to predict future risk for disease in a healthy patient. 133. Zhang Z, Hernandez K, Savage J, et al. Uniform genomic data analysis in Ann Intern Med. 2021;174:540–547. the NCI Genomic Data Commons. Nat Commun. 2021;12:1226. 152. Chen J, Fowler KJ, Grams ME. Knowledge is power: patient education as 134. eMERGE Consortium. Harmonizing clinical sequencing and a tool for patient activation. Am J Kidney Dis. 2020;76:163–165. interpretation for the eMERGE III Network. Am J Hum Genet. 2019;105: 153. Logeman C, Cho Y, Sautenet B, et al. ‘A sword of Damocles’: patient and 588–605. caregiver beliefs, attitudes and perspectives on presymptomatic testing 135. Eales JM, Jiang X, Xu X, et al. Uncovering genetic mechanisms of for autosomal dominant polycystic kidney disease: a focus group study. hypertension through multi-omic analysis of the kidney. Nat Genet. BMJ Open. 2020;10:e038005. 2021;53:630–637. 154. Waterman AD, Gleason J, Lerminiaux L, et al. Amplifying the patient 136. Gillies CE, Putler R, Menon R, et al. An eQTL landscape of kidney tissue voice: key priorities and opportunities for improved transplant and in human nephrotic syndrome. Am J Hum Genet. 2018;103:232–244. living donor advocacy and outcomes during COVID-19 and beyond. 137. Townsend RR, Guarnieri P, Argyropoulos C, et al. Rationale and design Curr Transplant Rep. 2020;7:301–310. of the Transformative Research in Diabetic Nephropathy (TRIDENT) 155. Vyas DA, Eisenstein LG, Jones DS. Hidden in plain sight—reconsidering Study. Kidney Int. 2020;97:10–13. the use of race correction in clinical algorithms. N Engl J Med. 2020;383: 138. Abedini A, Zhu YO, Chatterjee S, et al. Urinary single-cell profiling 874–882. captures the cellular diversity of the kidney. J Am Soc Nephrol. 2021;32: 156. Borrell LN, Elhawary JR, Fuentes-Afflick E, et al. Race and genetic 614–627. ancestry in medicine—a time for reckoning with racism. N Engl J Med. 139. ENCODE Project Consortium. The ENCODE (ENCyclopedia Of DNA 2021;384:474–480. Elements) Project. Science. 2004;306:636–640. 157. Oni-Orisan A, Mavura Y, Banda Y, et al. Embracing genetic diversity to 140. Roadmap Epigenomics Consortium, Kundaje A, Meuleman W, et al. improve Black health. N Engl J Med. 2021;384:1163–1167. Integrative analysis of 111 reference human epigenomes. Nature. 158. Race, Ethnicity, and Genetics Working Group. The use of racial, ethnic, 2015;518:317–330. and ancestral categories in human genetics research. Am J Hum Genet. 141. GTEx Consortium. Erratum: Genetic effects on gene expression across 2005;77:519–532. human tissues. Nature. 2018;553:530. 159. Nair D, Wilson FP. Patient-reported outcome measures for adults with 142. de Boer IH, Alpers CE, Azeloglu EU, et al. Rationale and design of the kidney disease: current measures, ongoing initiatives, and future Kidney Precision Medicine Project. Kidney Int. 2021;99:498–510. opportunities for incorporation into patient-centered kidney care. Am J 143. Mostafavi H, Harpak A, Agarwal I, et al. Variable prediction accuracy of Kidney Dis. 2019;74:791–802. polygenic scores within an ancestry group. Elife. 2020;9:e48376. 160. ACMG Board of Directors. Clinical utility of genetic and genomic 144. Wand H, Lambert SA, Tamburro C, et al. Improving reporting standards services: a position statement of the American College of Medical for polygenic scores in risk prediction studies. Nature. 2021;591: Genetics and Genomics. Genet Med. 2015;17:505–507. 211–219. 161. Sun F, Bruening W, Erinoff E, Schoelles KM. Addressing Challenges in 145. Buniello A, MacArthur JAL, Cerezo M, et al. The NHGRI-EBI GWAS Genetic Test Evaluation. Evaluation Frameworks and Assessment of Catalog of published genome-wide association studies, targeted arrays Analytic Validity. Methods Research Report (Prepared by the ECRI and summary statistics 2019. Nucleic Acids Res. 2019;47:D1005–D1012. Institute Evidence-based Practice Center under Contract No. HHSA 290- 146. Lambert SA, Gil L, Jupp S, et al. The Polygenic Score Catalog as an open 2007-10063-I.) AHRQ Publication No. 11-EHC048-EF. Rockville, MD: database for reproducibility and systematic evaluation. Nat Genet. Agency for Healthcare Research and Quality. June 2011. 2021;53:420–425. 162. Giacomini M, Miller F, Browman G. Confronting the “gray zones” of 147. Shaikh A, Patel N, Nair D, et al. Current paradigms and emerging technology assessment: evaluating genetic testing services for public opportunities in nephrology training. Adv Chronic Kidney Dis. 2020;27: insurance coverage in Canada. Int J Technol Assess Health Care. 2003;19: 291–296.e1. 301–316. Kidney International (2022) 101, 1126–1141 1141