Linkage analysis of glomerular filtration rate in American Indians

Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Numerous genes for monogenic kidney diseases with classical patterns of inheritance, as well as genes for complex kidney diseases that manifest in combination with environmental factors, have been discovered. Genetic findings are increasingly used to inform clinical management of nephropathies, and have led to improved diagnostics, disease surveillance, choice of therapy, and family counseling. All of these steps rely on accurate interpretation of genetic data, which can be outpaced by current rates of data collection. In March of 2021, Kidney Diseases: Improving Global Outcomes (KDIGO) held a Controversies Conference on "Genetics in Chronic Kidney Disease (CKD)" to review the current state of understanding of monogenic and complex (polygenic) kidney diseases, processes for applying genetic findings in clinical medicine, and use of genomics for defining and stratifying CKD. Given the important contribution of genetic variants to CKD, practitioners with CKD patients are advised to "think genetic," which specifically involves obtaining a family history, collecting detailed information on age of CKD onset, performing clinical examination for extrarenal symptoms, and considering genetic testing. To improve the use of genetics in nephrology, meeting participants advised developing an advanced training or subspecialty track for nephrologists, crafting guidelines for testing and treatment, and educating patients, students, and practitioners. Key areas of future research, including clinical interpretation of genome variation, electronic phenotyping, global representation, kidney-specific molecular data, polygenic scores, translational epidemiology, and open data resources, were also identified.

Characterising the relationships between physiological indicators and all-cause mortality (NHANES): a population-based cohort study

BACKGROUND

Mortality risk stratification based on dichotomising a physiological indicator with a cutoff point might not adequately capture increased mortality risk and might not account for non-linear associations. We aimed to characterise the linear and non-linear relationships of 27 physiological indicators with all-cause mortality to evaluate whether the current clinical thresholds are suitable in distinguishing patients at high risk for mortality from those at low risk.

METHODS

For this observational cohort study of the US non-institutionalised population, we used data from adults (≥18 years) included in the 1999-2014 National Health and Nutrition Examination Survey (NHANES) linked with National Death Index mortality data collected from Jan 1, 1999, up until Dec 31, 2015. We used Cox proportional hazards regression models adjusted for age, sex, and race or ethnicity to assess associations of physiological indicators with all-cause mortality. We assessed non-linear associations by discretising the physiological indicator into nine quantiles (termed novemtiles) and by using a weighted sum of cubic polynomials (spline). We used ten-fold cross validation to select the most appropriate model using the concordance index, Nagelkerke R2, and Akaike Information Criterion. We identified the level of each physiological indicator that led to a 10% increase in mortality risk to define our cutoffs used to compare with the current clinical thresholds.

FINDINGS

We included 47 266 adults of 82 091 assessed for eligibility. 25 (93%) of 27 indicators showed non-linear associations with substantial increases compared with linear models in mortality risk (1·5-2·5-times increase). Height and 60 s pulse were the only physiological indicators to show linear associations. For example, participants with an estimated glomerular filtration rate (GFR) of less than 65 mL/min per 1·73 m2 or between 90-116 mL/min per 1·73 m2 are at moderate (hazard ratio 1-2) mortality risk. Those with a GFR greater than 117 mL/min per 1·73 m2 show substantial (hazard ratio ≥2) mortality risk. Both lower and higher values of cholesterol are associated with increased mortality risk. The current clinical thresholds do not align with our mortality-based cutoffs for fat deposition indices, 60 s pulse, triglycerides, cholesterol-related indicators, alkaline phosphatase, glycohaemoglobin, homoeostatic model assessment of insulin resistance, and GFR. For these indicators, the misalignment suggests the need to consider an additional bound when only one is provided.

INTERPRETATION

Most clinical indicators were shown to have non-linear associations with all-cause mortality. Furthermore, considering these non-linear associations can help derive reliable cutoffs to complement risk stratification and help inform clinical care delivery. Given the poor alignment with our proposed cutoffs, the current clinical thresholds might not adequately capture mortality risk.

Reported sources of health inequities in Indigenous Peoples with chronic kidney disease: a systematic review of quantitative studies

BACKGROUND

To summarise the evidentiary basis related to causes of inequities in chronic kidney disease among Indigenous Peoples.

METHODS

We conducted a Kaupapa Māori meta-synthesis evaluating the epidemiology of chronic kidney diseases in Indigenous Peoples. Systematic searching of MEDLINE, Google Scholar, OVID Nursing, CENTRAL and Embase was conducted to 31 December 2019. Eligible studies were quantitative analyses (case series, case-control, cross-sectional or cohort study) including the following Indigenous Peoples: Māori, Aboriginal and Torres Strait Islander, Métis, First Nations Peoples of Canada, First Nations Peoples of the United States of America, Native Hawaiian and Indigenous Peoples of Taiwan. In the first cycle of coding, a descriptive synthesis of the study research aims, methods and outcomes was used to categorise findings inductively based on similarity in meaning using the David R Williams framework headings and subheadings. In the second cycle of analysis, the numbers of studies contributing to each category were summarised by frequency analysis. Completeness of reporting related to health research involving Indigenous Peoples was evaluated using the CONSIDER checklist.

RESULTS

Four thousand three hundred seventy-two unique study reports were screened and 180 studies proved eligible. The key finding was that epidemiological investigators most frequently reported biological processes of chronic kidney disease, particularly type 2 diabetes and cardiovascular disease as the principal causes of inequities in the burden of chronic kidney disease for colonised Indigenous Peoples. Social and basic causes of unequal health including the influences of economic, political and legal structures on chronic kidney disease burden were infrequently reported or absent in existing literature.

CONCLUSIONS

In this systematic review with meta-synthesis, a Kaupapa Māori methodology and the David R Williams framework was used to evaluate reported causes of health differences in chronic kidney disease in Indigenous Peoples. Current epidemiological practice is focussed on biological processes and surface causes of inequity, with limited reporting of the basic and social causes of disparities such as racism, economic and political/legal structures and socioeconomic status as sources of inequities.

Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies

Chronic Kidney Disease (CKD) represents a slowly progressive disorder that is typically silent until late stages, but early intervention can significantly delay its progression. We designed a portable and scalable electronic CKD phenotype to facilitate early disease recognition and empower large-scale observational and genetic studies of kidney traits. The algorithm uses a combination of rule-based and machine-learning methods to automatically place patients on the staging grid of albuminuria by glomerular filtration rate ("A-by-G" grid). We manually validated the algorithm by 451 chart reviews across three medical systems, demonstrating overall positive predictive value of 95% for CKD cases and 97% for healthy controls. Independent case-control validation using 2350 patient records demonstrated diagnostic specificity of 97% and sensitivity of 87%. Application of the phenotype to 1.3 million patients demonstrated that over 80% of CKD cases are undetected using ICD codes alone. We also demonstrated several large-scale applications of the phenotype, including identifying stage-specific kidney disease comorbidities, in silico estimation of kidney trait heritability in thousands of pedigrees reconstructed from medical records, and biobank-based multicenter genome-wide and phenome-wide association studies.

Evaluation of neurotrophic tyrosine receptor kinase 2 (NTRK2) as a positional candidate gene for variation in estimated glomerular filtration rate (eGFR) in Mexican American participants of San Antonio Family Heart study

Background

The estimated glomerular filtration rate (eGFR) is a well-known measure of kidney function and is commonly used for the diagnosis and management of patients with chronic kidney disease. The inter-individual variation in eGFR has significant genetic component. However, the identification of underlying genetic susceptibility variants has been challenging. In an attempt to identify and characterize susceptibility genetic variant(s) we previously identified the strongest evidence for linkage of eGFR occurring on chromosome 9q21 in the Mexican American participants of San Antonio Family Heart Study (SAFHS). The objective of the present study was to examine whether the common genetic variants in Neurotrophic Tyrosine Receptor Kinase 2 (NTRK2), a positional candidate gene on 9q21, contribute to variation in eGFR.

Results

Twelve tagging single nucleotide polymorphisms (SNPs) across the NTRK2 gene region were selected (r2 ≥ 0.80, minor allele frequency of ≥ 0.05) from the Hapmap database. SNPs were genotyped by TaqMan assay in the 848 Mexican American subjects participated in the SAFHS. Association analysis between the genotypes and eGFR (estimated by the Modification of Diet in Renal Disease equation) were performed by measured genotype approach as implemented in the program SOLAR. Of the 12 common genetic variants examined, the rs1036915 (located in 3′UTR) and rs1187274 (located in intron-14), present in perfect linkage disequilibrium, exhibited an association (P = 0.017) with eGFR after accounting for the effects of age, sex, diabetes, diabetes duration, systolic blood pressure and blood pressure medication. The carriers of minor allele of rs1036915 (G; 38%) had increased eGFR (104 ± 25 ml/min/1.73 m²) in comparison to the carriers of major allele A (98 ± 25 ml/min/1.73 m²).

Conclusion

Together, our results suggest for the first time that the genetic variants in NTRK2 may regulate eGFR.

A genome-wide search for linkage of estimated glomerular filtration rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND)

Objective

Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that explain a larger proportion of the heritability. This study used genome-wide linkage and association scans to identify quantitative trait loci (QTL) that influence eGFR.

Methods

Genome-wide linkage and sparse association scans of eGFR were performed in families ascertained by probands with advanced diabetic nephropathy (DN) from the multi-ethnic Family Investigation of Nephropathy and Diabetes (FIND) study. This study included 954 African Americans (AA), 781 American Indians (AI), 614 European Americans (EA) and 1,611 Mexican Americans (MA). A total of 3,960 FIND participants were genotyped for 6,000 single nucleotide polymorphisms (SNPs) using the Illumina Linkage IVb panel. GFR was estimated by the Modification of Diet in Renal Disease (MDRD) formula.

Results

The non-parametric linkage analysis, accounting for the effects of diabetes duration and BMI, identified the strongest evidence for linkage of eGFR on chromosome 20q11 (log of the odds [LOD] = 3.34; P = 4.4×10⁻⁵) in MA and chromosome 15q12 (LOD = 2.84; P = 1.5×10⁻⁴) in EA. In all subjects, the strongest linkage signal for eGFR was detected on chromosome 10p12 (P = 5.5×10⁻⁴) at 44 cM near marker rs1339048. A subsequent association scan in both ancestry-specific groups and the entire population identified several SNPs significantly associated with eGFR across the genome.

Conclusion

The present study describes the localization of QTL influencing eGFR on 20q11 in MA, 15q21 in EA and 10p12 in the combined ethnic groups participating in the FIND study. Identification of causal genes/variants influencing eGFR, within these linkage and association loci, will open new avenues for functional analyses and development of novel diagnostic markers for DN.

Generalization of associations of kidney-related genetic loci to American Indians

BACKGROUND AND OBJECTIVES

CKD disproportionally affects American Indians, who similar to other populations, show genetic susceptibility to kidney outcomes. Recent studies have identified several loci associated with kidney traits, but their relevance in American Indians is unknown.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

This study used data from a large, family-based genetic study of American Indians (the Strong Heart Family Study), which includes 94 multigenerational families enrolled from communities located in Oklahoma, the Dakotas, and Arizona. Individuals were recruited from the Strong Heart Study, a population-based study of cardiovascular disease in American Indians. This study selected 25 single nucleotide polymorphisms in 23 loci identified from recently published kidney-related genome-wide association studies in individuals of European ancestry to evaluate their associations with kidney function (estimated GFR; individuals 18 years or older, up to 3282 individuals) and albuminuria (urinary albumin to creatinine ratio; n=3552) in the Strong Heart Family Study. This study also examined the association of single nucleotide polymorphisms in the APOL1 region with estimated GFR in 1121 Strong Heart Family Study participants. GFR was estimated using the abbreviated Modification of Diet in Renal Disease Equation. Additive genetic models adjusted for age and sex were used.

RESULTS

This study identified significant associations of single nucleotide polymorphisms with estimated GFR in or nearby PRKAG2, SLC6A13, UBE2Q2, PIP5K1B, and WDR72 (P<2.1 × 10(-3) to account for multiple testing). Single nucleotide polymorphisms in these loci explained 2.2% of the estimated GFR total variance and 2.9% of its heritability. An intronic variant of BCAS3 was significantly associated with urinary albumin to creatinine ratio. APOL1 single nucleotide polymorphisms were not associated with estimated GFR in a single variant test or haplotype analyses, and the at-risk variants identified in individuals with African ancestry were not detected in DNA sequencing of American Indians.

CONCLUSION

This study extends the genetic associations of loci affecting kidney function to American Indians, a population at high risk of kidney disease, and provides additional support for a potential biologic relevance of these loci across ancestries.

A family-based association study after genome-wide linkage analysis identified two genetic loci for renal function in a Mongolian population

The estimated glomerular filtration rate is a well-known measure of renal function and is widely used to follow the course of disease. Although there have been several investigations establishing the genetic background contributing to renal function, Asian populations have rarely been used in these genome-wide studies. Here, we aimed to find candidate genetic determinants of renal function in 1007 individuals from 73 extended families of Mongolian origin. Linkage analysis found two suggestive regions near 9q21 (logarithm of odds (LOD) 2.82) and 15q15 (LOD 2.70). The subsequent family-based association study found 2 and 10 significant single-nucleotide polymorphisms (SNPs) in each region, respectively. The strongest SNPs on chromosome 9 and 15 were rs17400257 and rs1153831 with P-values of 7.21 × 10(-9) and 2.47 × 10(-11), respectively. Genes located near these SNPs are considered candidates for determining renal function and include FRMD3, GATM, and SPATA5L1. Thus, we identified possible loci that determine renal function in an isolated Asian population. Consistent with previous reports, our study found genes linked and associated with renal function in other populations.

The association of genetic variants of type 2 diabetes with kidney function

Type 2 diabetes is highly prevalent and is the major cause of progressive chronic kidney disease in American Indians. Genome-wide association studies identified several loci associated with diabetes but their impact on susceptibility to diabetic complications is unknown. We studied the association of 18 type 2 diabetes genome-wide association single-nucleotide polymorphisms (SNPs) with estimated glomerular filtration rate (eGFR; MDRD equation) and urine albumin-to-creatinine ratio in 6958 Strong Heart Study family and cohort participants. Center-specific residuals of eGFR and log urine albumin-to-creatinine ratio, obtained from linear regression models adjusted for age, sex, and body mass index, were regressed onto SNP dosage using variance component models in family data and linear regression in unrelated individuals. Estimates were then combined across centers. Four diabetic loci were associated with eGFR and one locus with urine albumin-to-creatinine ratio. A SNP in the WFS1 gene (rs10010131) was associated with higher eGFR in younger individuals and with increased albuminuria. SNPs in the FTO, KCNJ11, and TCF7L2 genes were associated with lower eGFR, but not albuminuria, and were not significant in prospective analyses. Our findings suggest a shared genetic risk for type 2 diabetes and its kidney complications, and a potential role for WFS1 in early-onset diabetic nephropathy in American Indian populations.

Identification of the nephropathy-susceptibility locus HIVAN4

HIVAN1, HIVAN2, and HIVAN3 are nephropathy-susceptibility loci previously identified in the HIV-1 transgenic mouse, a model of collapsing glomerulopathy. The HIVAN1 and HIVAN2 loci modulate expression of Nphs2, which encodes podocin and several other podocyte-expressed genes. To identify additional loci predisposing to nephropathy, we performed a genome-wide scan in 165 backcross mice generated between the nephropathy-sensitive HIV-1-transgenic FVB/NJ (TgFVB) strain and the resistant Balb/cJ (BALB) strain. We identified a major susceptibility locus (HIVAN4) on chromosome 6 G3-F3, with BALB alleles conferring a twofold reduction in severity (peak LOD score = 4.0). Similar to HIVAN1 and HIVAN2, HIVAN4 modulated expression of Nphs2, indicating a common pathway underlying these loci. We independently confirmed the HIVAN4 locus in a sister TgFVB colony that experienced a dramatic loss of nephropathy subsequent to a breeding bottleneck. In this low-penetrance line, 3% of the genome was admixed with BALB alleles, suggesting a remote contamination event. The admixture localized to discrete segments on chromosome 2 and at the HIVAN4 locus. HIVAN4 candidate genes include killer lectin-like receptor genes as well as A2m and Ptpro, whose gene products are enriched in the glomerulus and interact with HIV-1 proteins. In summary, these data identify HIVAN4 as a major quantitative trait locus for nephropathy and a transregulator of Nphs2. Furthermore, similar selective breeding strategies may help identify further susceptibility loci.

Meta-analysis of genome-wide linkage scans for renal function traits

BACKGROUND

Several genome scans have explored the linkage of chronic kidney disease phenotypes to chromosomic regions with disparate results. Genome scan meta-analysis (GSMA) is a quantitative method to synthesize linkage results from independent studies and assess their concordance.

METHODS

We searched PubMed to identify genome linkage analyses of renal function traits in humans, such as estimated glomerular filtration rate (GFR), albuminuria, serum creatinine concentration and creatinine clearance. We contacted authors for numerical data and extracted information from individual studies. We applied the GSMA nonparametric approach to combine results across 14 linkage studies for GFR, 11 linkage studies for albumin creatinine ratio, 11 linkage studies for serum creatinine and 4 linkage studies for creatinine clearance.

RESULTS

No chromosomal region reached genome-wide statistical significance in the main analysis which included all scans under each phenotype; however, regions on Chromosomes 7, 10 and 16 reached suggestive significance for linkage to two or more phenotypes. Subgroup analyses by disease status or ethnicity did not yield additional information.

CONCLUSIONS

While heterogeneity across populations, methodologies and study designs likely explain this lack of agreement, it is possible that linkage scan methodologies lack the resolution for investigating complex traits. Combining family-based linkage studies with genome-wide association studies may be a powerful approach to detect private mutations contributing to complex renal phenotypes.

Refined mapping of the renal failure RF-3 quantitative trait locus

Rf-3, a quantitative trait locus (QTL) on rat chromosome 3, affects the development of CKD in Fawn-Hooded Hypertensive (FHH) rats. This QTL spans 110 Mb and approximately 1400 genes; therefore, narrowing the position of this locus is necessary to elucidate potential candidate genes. Here, we used congenic models and comparative genomics to refine the Rf-3 candidate region. We generated congenic lines carrying smaller intervals (subcongenics) of the Rf-3 region and used these lines to reduce the Rf-3 candidate region by 94% (to 7.1 Mb). We used comparative genomics to identify QTL for both nephropathy and albuminuria in the syntenic region of this interval for both human and mouse. We also used the overlapping homologous regions to reduce the number of likely positional candidate genes to 13 known or predicted genes. By combining congenic models and cross-species studies, we narrowed the list of candidate genes to a level that we could sequence the whole interval to further identify the causative gene in future studies.

Heritability of measures of kidney disease among Zuni Indians: the Zuni Kidney Project

BACKGROUND

The long-term goal of the GKDZI (Genetics of Kidney Disease in Zuni Indians) Study is to identify genes, environmental factors, and genetic-environmental interactions that modulate susceptibility to renal disease and intermediate phenotypes.

STUDY DESIGN

A community-based participatory research approach was used to recruit family members of individuals with kidney disease.

SETTING & PARTICIPANTS

The study was conducted in the Zuni Indians, a small endogamous tribe located in rural New Mexico. We recruited members of extended families, ascertained through a proband with kidney disease and at least 1 sibling with kidney disease. 821 participants were recruited, comprising 7,702 relative pairs. PREDICTOR OUTCOMES & MEASUREMENTS: Urine albumin-creatinine ratio (UACR) and hematuria were determined in 3 urine samples and expressed as a true ratio. Glomerular filtration rate (GFR) was estimated using the Modification of Diet in Renal Disease (MDRD) Study equation modified for American Indians. Probands were considered to have kidney disease if UACR was >or=0.2 in 2 or more of 3 spot urine samples or estimated GFR was decreased according to the CRIC (Chronic Renal Insufficiency Cohort) Study criteria.

RESULTS

Kidney disease was identified in 192 participants (23.4%). There were significant heritabilities for estimated GFR, UACR, serum creatinine, serum urea nitrogen, and uric acid and a variety of phenotypes related to obesity, diabetes, and cardiovascular disease. There were significant genetic correlations of some kidney-related phenotypes with these other phenotypes.

LIMITATIONS

Limitations include absence of renal biopsy, possible misclassification bias, lack of direct GFR measurements, and failure to include all possible environmental interactions.

CONCLUSIONS

Many phenotypes related to kidney disease showed significant heritabilities in Zuni Indians, and there were significant genetic correlations with phenotypes related to obesity, diabetes, and cardiovascular disease. The study design serves as a paradigm for the conduct of research in relatively isolated, endogamous, underserved populations.

A meta-analysis of genome-wide data from five European isolates reveals an association of COL22A1, SYT1, and GABRR2 with serum creatinine level

BACKGROUND

Serum creatinine (S CR) is the most important biomarker for a quick and non-invasive assessment of kidney function in population-based surveys. A substantial proportion of the inter-individual variability in S CR level is explicable by genetic factors.

METHODS

We performed a meta-analysis of genome-wide association studies of S CR undertaken in five population isolates ('discovery cohorts'), all of which are part of the European Special Population Network (EUROSPAN) project. Genes showing the strongest evidence for an association with SCR (candidate loci) were replicated in two additional population-based samples ('replication cohorts').

RESULTS

After the discovery meta-analysis, 29 loci were selected for replication. Association between SCR level and polymorphisms in the collagen type XXII alpha 1 (COL22A1) gene, on chromosome 8, and in the synaptotagmin-1 (SYT1) gene, on chromosome 12, were successfully replicated in the replication cohorts (p value = 1.0 x 10(-6) and 1.7 x 10(-4), respectively). Evidence of association was also found for polymorphisms in a locus including the gamma-aminobutyric acid receptor rho-2 (GABRR2) gene and the ubiquitin-conjugating enzyme E2-J1 (UBE2J1) gene (replication p value = 3.6 x 10(-3)). Previously reported findings, associating glomerular filtration rate with SNPs in the uromodulin (UMOD) gene and in the schroom family member 3 (SCHROOM3) gene were also replicated.

CONCLUSIONS

While confirming earlier results, our study provides new insights in the understanding of the genetic basis of serum creatinine regulatory processes. In particular, the association with the genes SYT1 and GABRR2 corroborate previous findings that highlighted a possible role of the neurotransmitters GABAA receptors in the regulation of the glomerular basement membrane and a possible interaction between GABAA receptors and synaptotagmin-I at the podocyte level.

Unravelling the genetic basis of renal diseases; from single gene to multifactorial disorders

Chronic kidney disease is common with up to 5% of the adult population reported to have an estimated glomerular filtration rate of < 60 ml/min/1.73 m(2). A large number of pathogenic mutations have been identified that are responsible for 'single gene' renal disorders, such as autosomal dominant polycystic kidney disease and X-linked Alport syndrome. These single gene disorders account for < 15% of the burden of end-stage renal disease that requires dialysis or kidney transplantation. It has proved more difficult to identify the genetic susceptibility underlying common, complex, multifactorial kidney conditions, such as diabetic nephropathy and hypertensive nephrosclerosis. This review describes success to date and explores strategies currently employed in defining the genetic basis for a number of renal disorders. The complementary use of linkage studies, candidate gene and genome-wide association analyses are described and a collation of renal genetic resources highlighted.