Genome-wide Association Study for AKI

Key Points

Two genetic variants in the DISP1-TLR5 gene locus were associated with risk of AKI. DISP1 and TLR5 were differentially regulated in kidney biopsy tissue from patients with AKI compared with no AKI.

Background

Although common genetic risks for CKD are well established, genetic factors influencing risk for AKI in hospitalized patients are poorly understood.

Methods

We conducted a genome-wide association study in 1369 participants in the Assessment, Serial Evaluation, and Subsequent Sequelae of AKI Study; a multiethnic population of hospitalized participants with and without AKI matched on demographics, comorbidities, and kidney function before hospitalization. We then completed functional annotation of top-performing variants for AKI using single-cell RNA sequencing data from kidney biopsies in 12 patients with AKI and 18 healthy living donors from the Kidney Precision Medicine Project.

Results

No genome-wide significant associations with AKI risk were found in Assessment, Serial Evaluation, and Subsequent Sequelae of AKI (P < 5×10 −8 ). The top two variants with the strongest association with AKI mapped to the dispatched resistance-nodulation-division (RND) transporter family member 1 (DISP1) gene and toll-like receptor 5 (TLR5) gene locus, rs17538288 (odds ratio, 1.55; 95% confidence interval, 1.32 to 182; P = 9.47×10 −8 ) and rs7546189 (odds ratio, 1.53; 95% confidence interval, 1.30 to 1.81; P = 4.60×10 −7 ). In comparison with kidney tissue from healthy living donors, kidney biopsies in patients with AKI showed differential DISP1 expression in proximal tubular epithelial cells (adjusted P = 3.9× 10−2) and thick ascending limb of the loop of Henle (adjusted P = 8.7× 10−3) and differential TLR5 gene expression in thick ascending limb of the loop of Henle (adjusted P = 4.9× 10−30).

Conclusions

AKI is a heterogeneous clinical syndrome with various underlying risk factors, etiologies, and pathophysiology that may limit the identification of genetic variants. Although no variants reached genome-wide significance, we report two variants in the intergenic region between DISP1 and TLR5 , suggesting this region as a novel risk for AKI susceptibility.

A metadata framework for computational phenotypes

With the burgeoning development of computational phenotypes, it is increasingly difficult to identify the right phenotype for the right tasks. This study uses a mixed-methods approach to develop and evaluate a novel metadata framework for retrieval of and reusing computational phenotypes. Twenty active phenotyping researchers from 2 large research networks, Electronic Medical Records and Genomics and Observational Health Data Sciences and Informatics, were recruited to suggest metadata elements. Once consensus was reached on 39 metadata elements, 47 new researchers were surveyed to evaluate the utility of the metadata framework. The survey consisted of 5-Likert multiple-choice questions and open-ended questions. Two more researchers were asked to use the metadata framework to annotate 8 type-2 diabetes mellitus phenotypes. More than 90% of the survey respondents rated metadata elements regarding phenotype definition and validation methods and metrics positively with a score of 4 or 5. Both researchers completed annotation of each phenotype within 60 min. Our thematic analysis of the narrative feedback indicates that the metadata framework was effective in capturing rich and explicit descriptions and enabling the search for phenotypes, compliance with data standards, and comprehensive validation metrics. Current limitations were its complexity for data collection and the entailed human costs.

An atlas of healthy and injured cell states and niches in the human kidney

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for IgA nephropathy

IgA nephropathy (IgAN) is a progressive form of kidney disease defined by glomerular deposition of IgA. Here we performed a genome-wide association study of 10,146 kidney-biopsy-diagnosed IgAN cases and 28,751 controls across 17 international cohorts. We defined 30 genome-wide significant risk loci explaining 11% of disease risk. A total of 16 loci were new, including TNFSF4/TNFSF18, REL, CD28, PF4V1, LY86, LYN, ANXA3, TNFSF8/TNFSF15, REEP3, ZMIZ1, OVOL1/RELA, ETS1, IGH, IRF8, TNFRSF13B and FCAR. The risk loci were enriched in gene orthologs causing abnormal IgA levels when genetically manipulated in mice. We also observed a positive genetic correlation between IgAN and serum IgA levels. High polygenic score for IgAN was associated with earlier onset of kidney failure. In a comprehensive functional annotation analysis of candidate causal genes, we observed convergence of biological candidates on a common set of inflammatory signaling pathways and cytokine ligand-receptor pairs, prioritizing potential new drug targets.

The chromatin landscape of healthy and injured cell types in the human kidney

There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. However, comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measured dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We established a comprehensive and spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we noted distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3 , KLF6 , and KLF10 regulated the transition between health and injury, while in thick ascending limb cells this transition was regulated by NR2F1 . Further, combined perturbation of ELF3 , KLF6 , and KLF10 distinguished two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.

Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations

Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE's experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings.

CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses

Fine-mapping is commonly used to identify putative causal variants at genome-wide significant loci. Here we propose a Bayesian model for fine-mapping that has several advantages over existing methods, including flexible specification of the prior distribution of effect sizes, joint modeling of summary statistics and functional annotations and accounting for discrepancies between summary statistics and external linkage disequilibrium in meta-analyses. Using simulations, we compare performance with commonly used fine-mapping methods and show that the proposed model has higher power and lower false discovery rate (FDR) when including functional annotations, and higher power, lower FDR and higher coverage for credible sets in meta-analyses. We further illustrate our approach by applying it to a meta-analysis of Alzheimer's disease genome-wide association studies where we prioritize putatively causal variants and genes.

Rare Single Nucleotide and Copy Number Variants and the Etiology of Congenital Obstructive Uropathy: Implications for Genetic Diagnosis

SIGNIFICANCE STATEMENT

Congenital obstructive uropathy (COU) is a prevalent human developmental defect with highly heterogeneous clinical presentations and outcomes. Genetics may refine diagnosis, prognosis, and treatment, but the genomic architecture of COU is largely unknown. Comprehensive genomic screening study of 733 cases with three distinct COU subphenotypes revealed disease etiology in 10.0% of them. We detected no significant differences in the overall diagnostic yield among COU subphenotypes, with characteristic variable expressivity of several mutant genes. Our findings therefore may legitimize a genetic first diagnostic approach for COU, especially when burdening clinical and imaging characterization is not complete or available.

BACKGROUND

Congenital obstructive uropathy (COU) is a common cause of developmental defects of the urinary tract, with heterogeneous clinical presentation and outcome. Genetic analysis has the potential to elucidate the underlying diagnosis and help risk stratification.

METHODS

We performed a comprehensive genomic screen of 733 independent COU cases, which consisted of individuals with ureteropelvic junction obstruction ( n =321), ureterovesical junction obstruction/congenital megaureter ( n =178), and COU not otherwise specified (COU-NOS; n =234).

RESULTS

We identified pathogenic single nucleotide variants (SNVs) in 53 (7.2%) cases and genomic disorders (GDs) in 23 (3.1%) cases. We detected no significant differences in the overall diagnostic yield between COU sub-phenotypes, and pathogenic SNVs in several genes were associated to any of the three categories. Hence, although COU may appear phenotypically heterogeneous, COU phenotypes are likely to share common molecular bases. On the other hand, mutations in TNXB were more often identified in COU-NOS cases, demonstrating the diagnostic challenge in discriminating COU from hydronephrosis secondary to vesicoureteral reflux, particularly when diagnostic imaging is incomplete. Pathogenic SNVs in only six genes were found in more than one individual, supporting high genetic heterogeneity. Finally, convergence between data on SNVs and GDs suggest MYH11 as a dosage-sensitive gene possibly correlating with severity of COU.

CONCLUSIONS

We established a genomic diagnosis in 10.0% of COU individuals. The findings underscore the urgent need to identify novel genetic susceptibility factors to COU to better define the natural history of the remaining 90% of cases without a molecular diagnosis.

Polygenic risk affects the penetrance of monogenic kidney disease

Background

Chronic kidney disease (CKD) is a genetically complex disease determined by an interplay of monogenic, polygenic, and environmental risks. Most forms of monogenic kidney diseases have incomplete penetrance and variable expressivity. It is presently unknown if some of the variability in penetrance can be attributed to polygenic factors.

Methods

Using the UK Biobank (N=469,835 participants) and the All of Us (N=98,622 participants) datasets, we examined two most common forms of monogenic kidney disorders, autosomal dominant polycystic kidney disease (ADPKD) caused by deleterious variants in the PKD1 or PKD2 genes, and COL4A-associated nephropathy (COL4A-AN caused by deleterious variants in COL4A3, COL4A4, or COL4A5 genes). We used the eMERGE-III electronic CKD phenotype to define cases (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 or kidney failure) and controls (eGFR >90 mL/min/1.73m2 in the absence of kidney disease diagnoses). The effects of the genome-wide polygenic score (GPS) for CKD were tested in monogenic variant carriers and non-carriers using logistic regression controlling for age, sex, diabetes, and genetic ancestry.

Results

As expected, the carriers of known pathogenic and rare predicted loss-of-function variants in PKD1 or PKD2 had a high risk of CKD (ORmeta=17.1, 95% CI: 11.1-26.4, P=1.8E-37). The GPS was comparably predictive of CKD in both ADPKD variant carriers (ORmeta=2.28 per SD, 95%CI: 1.55-3.37, P=2.6E-05) and non-carriers (ORmeta=1.72 per SD, 95% CI=1.69-1.76, P< E-300) independent of age, sex, diabetes, and genetic ancestry. Compared to the middle tertile of the GPS distribution for non-carriers, ADPKD variant carriers in the top tertile had a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile had only a 3-fold increased risk of CKD. Similarly, the GPS was predictive of CKD in both COL4-AN variant carriers (ORmeta=1.78, 95% CI=1.22-2.58, P=2.38E-03) and non-carriers (ORmeta=1.70, 95%CI: 1.68-1.73 P

Conclusions

Variable penetrance of kidney disease in ADPKD and COL4-AN is partially explained by differences in polygenic risk profiles. Accounting for polygenic factors has the potential to improve risk stratification in monogenic kidney disease and may have implications for genetic counseling.

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Key Words

• APOL1
• GWAS
• chronic kidney disease (CKD)
• polygenic risk score (PRS)

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MESH Headings Collapse

Grants

• OT2 OD026556 NIH HHS
• U2C OD023196 NIH HHS
• OT2 OD026551 NIH HHS
• U24 OD023121 NIH HHS
• OT2 OD026552 NIH HHS
• OT2 OD026549 NIH HHS
• OT2 OD025337 NIH HHS
• OT2 OD025277 NIH HHS
• OT2 OD026555 NIH HHS
• OT2 OD026550 NIH HHS
• OT2 OD026553 NIH HHS
• OT2 OD023205 NIH HHS
• U01 HG008680 NHGRI NIH HHS
• OT2 OD025276 NIH HHS
• OT2 OD026557 NIH HHS
• U24 OD023163 NIH HHS
• OT2 OD023206 NIH HHS
• R01 LM013061 NLM NIH HHS
• U24 OD023176 NIH HHS
• OT2 OD026548 NIH HHS
• OT2 OD025315 NIH HHS
• K25 DK128563 NIDDK NIH HHS
• OT2 OD026554 NIH HHS
• UL1 TR001873 NCATS NIH HHS

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Clinical and Genetic Characteristics of CKD Patients with High-Risk APOL1 Genotypes

SIGNIFICANCE STATEMENT

APOL1 high-risk genotypes confer a significant risk of kidney disease, but variability in patient outcomes suggests the presence of modifiers of the APOL1 effect. We show that a diverse population of CKD patients with high-risk APOL1 genotypes have an increased lifetime risk of kidney failure and higher eGFR decline rates, with a graded risk among specific high-risk genotypes. CKD patients with high-risk APOL1 genotypes have a lower diagnostic yield for monogenic kidney disease. Exome sequencing revealed enrichment of rare missense variants within the inflammasome pathway modifying the effect of APOL1 risk genotypes, which may explain some clinical heterogeneity.

BACKGROUND

APOL1 genotype has significant effects on kidney disease development and progression that vary among specific causes of kidney disease, suggesting the presence of effect modifiers.

METHODS

We assessed the risk of kidney failure and the eGFR decline rate in patients with CKD carrying high-risk ( N =239) and genetically matched low-risk ( N =1187) APOL1 genotypes. Exome sequencing revealed monogenic kidney diseases. Exome-wide association studies and gene-based and gene set-based collapsing analyses evaluated genetic modifiers of the effect of APOL1 genotype on CKD.

RESULTS

Compared with genetic ancestry-matched patients with CKD with low-risk APOL1 genotypes, those with high-risk APOL1 genotypes had a higher risk of kidney failure (Hazard Ratio [HR]=1.58), a higher decline in eGFR (6.55 versus 3.63 ml/min/1.73 m 2 /yr), and were younger at time of kidney failure (45.1 versus 53.6 years), with the G1/G1 genotype demonstrating the highest risk. The rate for monogenic kidney disorders was lower among patients with CKD with high-risk APOL1 genotypes (2.5%) compared with those with low-risk genotypes (6.7%). Gene set analysis identified an enrichment of rare missense variants in the inflammasome pathway in individuals with high-risk APOL1 genotypes and CKD (odds ratio=1.90).

CONCLUSIONS

In this genetically matched cohort, high-risk APOL1 genotypes were associated with an increased risk of kidney failure and eGFR decline rate, with a graded risk between specific high-risk genotypes and a lower rate of monogenic kidney disease. Rare missense variants in the inflammasome pathway may act as genetic modifiers of APOL1 effect on kidney disease.

Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome

Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional independent risk loci. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. Here, we conduct a multi-population GWAS meta-analysis in 38,463 participants (2440 cases). We then conduct conditional analyses and population specific GWAS. We discover twelve significant associations-eight from the multi-population meta-analysis (four novel), two from the multi-population conditional analysis (one novel), and two additional novel loci from the European meta-analysis. Fine-mapping implicates specific amino acid haplotypes in HLA-DQA1 and HLA-DQB1 driving the HLA Class II risk locus. Non-HLA loci colocalize with eQTLs of monocytes and numerous T-cell subsets in independent datasets. Colocalization with kidney eQTLs is lacking but overlap with kidney cell open chromatin suggests an uncharacterized disease mechanism in kidney cells. A polygenic risk score (PRS) associates with earlier disease onset. Altogether, these discoveries expand our knowledge of pSSNS genetic architecture across populations and provide cell-specific insights into its molecular drivers. Evaluating these associations in additional cohorts will refine our understanding of population specificity, heterogeneity, and clinical and molecular associations.

Returning integrated genomic risk and clinical recommendations: The eMERGE study

PURPOSE

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.

METHODS

To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results.

RESULTS

GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.

CONCLUSION

Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Genomic Disorders in CKD across the Lifespan

SIGNIFICANCE STATEMENT

Pathogenic structural genetic variants, also known as genomic disorders, have been associated with pediatric CKD. This study extends those results across the lifespan, with genomic disorders enriched in both pediatric and adult patients compared with controls. In the Chronic Renal Insufficiency Cohort study, genomic disorders were also associated with lower serum Mg, lower educational performance, and a higher risk of death. A phenome-wide association study confirmed the link between kidney disease and genomic disorders in an unbiased way. Systematic detection of genomic disorders can provide a molecular diagnosis and refine prediction of risk and prognosis.

BACKGROUND

Genomic disorders (GDs) are associated with many comorbid outcomes, including CKD. Identification of GDs has diagnostic utility.

METHODS

We examined the prevalence of GDs among participants in the Chronic Kidney Disease in Children (CKiD) cohort II ( n =248), Chronic Renal Insufficiency Cohort (CRIC) study ( n =3375), Columbia University CKD Biobank (CU-CKD; n =1986), and the Family Investigation of Nephropathy and Diabetes (FIND; n =1318) compared with 30,746 controls. We also performed a phenome-wide association analysis (PheWAS) of GDs in the electronic MEdical Records and GEnomics (eMERGE; n =11,146) cohort.

RESULTS

We found nine out of 248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72 out of 6679 (1.1%) adult patients with CKD in the CRIC, CU-CKD, and FIND cohorts, compared with 199 out of 30,746 (0.65%) GDs in controls (OR, 1.7; 95% CI, 1.3 to 2.2). Among adults with CKD, we found recurrent GDs at the 1q21.1, 16p11.2, 17q12, and 22q11.2 loci. The 17q12 GD (diagnostic of renal cyst and diabetes syndrome) was most frequent, present in 1:252 patients with CKD and diabetes. In the PheWAS, dialysis and neuropsychiatric phenotypes were the top associations with GDs. In CRIC participants, GDs were associated with lower serum magnesium, lower educational achievement, and higher mortality risk.

CONCLUSION

Undiagnosed GDs are detected both in children and adults with CKD. Identification of GDs in these patients can enable a precise genetic diagnosis, inform prognosis, and help stratify risk in clinical studies. GDs could also provide a molecular explanation for nephropathy and comorbidities, such as poorer neurocognition for a subset of patients.

Abstract MP19: An eGFR Polygenic Score Predicts Chronic Kidney Disease in African Americans

Chronic kidney disease (CKD) is a risk factor for cardiovascular disease and early death. Genetic factors contribute to CKD, and recently, polygenic scores (PGS) have been developed to quantify risk for complex diseases, such as CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PGS development overall; moreover, European-ancestry derived PGSs demonstrate diminished predictive performance in African ancestry populations. This study aimed to develop a PGS for CKD using genotype and phenotype data from African American (AA) participants of observational cohort studies. We obtained score weights from a meta-analysis of genome-wide association studies (GWAS) for estimated glomerular filtration rate (eGFR) in the Million Veteran Program (MVP) and Reasons for Geographical and Racial Differences in Stroke (REGARDS) Study (total n~66,000). We then optimized the PGS in a cohort of AAs from the Hypertension Genetic Epidemiology Network (HyperGEN) Study (n~1,900) using the PRS-CS software and evaluated the predictive performance of the PGS at multiple global shrinkage parameters. We further adjusted the PGS for APOL1 risk status. In HyperGEN, the eGFR-based PGS was significantly associated with the odds of prevalent CKD—defined as baseline eGFR <60 mL/min/1.73m 2 — in logistic regression models adjusted for age, sex, and population structure. Further, accounting for APOL1 risk status—a putative variant for CKD unique to those of sub-Saharan African descent—improved the score’s accuracy, with the APOL1 -adjusted PGS explaining 1.9% (1.1% without APOL1 ) of the variance in CKD and an area under the curve (AUC) of 58.9% [95% CI: 53.0%-64.9%] (without APOL1 , 58.2% [95% CI: 52.3%-64.1%]). Sensitivity analyses and validation in external cohorts, as well as comparisons to previously published PGS, are ongoing. In this study, we developed a PGS that was significantly associated with CKD with improved predictive accuracy in AAs over previously published PGS.

BIGKnock: fine-mapping gene-based associations via knockoff analysis of biobank-scale data

We propose BIGKnock (BIobank-scale Gene-based association test via Knockoffs), a computationally efficient gene-based testing approach for biobank-scale data, that leverages long-range chromatin interaction data, and performs conditional genome-wide testing via knockoffs. BIGKnock can prioritize causal genes over proxy associations at a locus. We apply BIGKnock to the UK Biobank data with 405,296 participants for multiple binary and quantitative traits, and show that relative to conventional gene-based tests, BIGKnock produces smaller sets of significant genes that contain the causal gene(s) with high probability. We further illustrate its ability to pinpoint potential causal genes at [Formula: see text] of the associated loci.

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network

The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations.

Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits

Immunoglobulin A (IgA) mediates mucosal responses to food antigens and the intestinal microbiome and is involved in susceptibility to mucosal pathogens, celiac disease, inflammatory bowel disease, and IgA nephropathy. We performed a genome-wide association study of serum IgA levels in 41,263 individuals of diverse ancestries and identified 20 genome-wide significant loci, including 9 known and 11 novel loci. Co-localization analyses with expression QTLs prioritized candidate genes for 14 of 20 significant loci. Most loci encoded genes that produced immune defects and IgA abnormalities when genetically manipulated in mice. We also observed positive genetic correlations of serum IgA levels with IgA nephropathy, type 2 diabetes, and body mass index, and negative correlations with celiac disease, inflammatory bowel disease, and several infections. Mendelian randomization supported elevated serum IgA as a causal factor in IgA nephropathy. African ancestry was consistently associated with higher serum IgA levels and greater frequency of IgA-increasing alleles compared to other ancestries. Our findings provide novel insights into the genetic regulation of IgA levels and its potential role in human disease.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Multiancestral polygenic risk score for pediatric asthma

BACKGROUND

Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.

OBJECTIVES

This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.

METHODS

This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.

RESULTS

The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PFDR = 3.71 × 10-65) and related phenotypes.

CONCLUSIONS

A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.

Kidney disease progression and collider bias in GWAS

New genome-wide meta-analysis for longitudinal kidney function decline identified several genetic loci related to kidney disease progression. The study illustrated the complexity of modeling longitudinal traits in genome-wide association studies and highlighted the issue of a collider bias that can be introduced when a kidney disease progression phenotype is adjusted for baseline kidney function. Herein, we briefly outline the key findings of this study, their limitations, and implications for future studies.

Incorporating genetics services into adult kidney disease care

Studies have shown that as many as 1 in 10 adults with chronic kidney disease has a monogenic form of disease. However, genetic services in adult nephrology are limited. An adult Kidney Genetics Clinic was established within the nephrology division at a large urban academic medical center to increase access to genetic services and testing in adults with kidney disease. Between June 2019 and December 2021, a total of 363 patients were referred to the adult Kidney Genetics Clinic. Of those who completed genetic testing, a positive diagnostic finding was identified in 27.1%, a candidate diagnostic finding was identified in 6.7% of patients, and a nondiagnostic positive finding was identified in an additional 8.6% of patients, resulting in an overall yield of 42.4% for clinically relevant genetic findings in tested patients. A genetic diagnosis had implications for medical management, family member testing, and eligibility for clinical trials. With the utilization of telemedicine, genetic services reached a diverse geographic and patient population. Genetic education efforts were integral to the clinic's success, as they increased visibility and helped providers identify appropriate referrals. Ongoing access to genomic services will remain a fundamental component of patient care in adults with kidney disease.

Cystatin C is associated with adverse COVID-19 outcomes in diverse populations

COVID-19 has highly variable clinical courses. The search for prognostic host factors for COVID-19 outcome is a priority. We performed logistic regression for ICU admission against a polygenic score (PGS) for Cystatin C (CyC) production in patients with COVID-19. We analyzed the predictive value of longitudinal plasma CyC levels in an independent cohort of patients hospitalized with COVID-19. In four cohorts spanning European and African ancestry populations, we identified a significant association between CyC-production PGS and odds of critical illness (n cases=2,319), with the strongest association captured in the UKB cohort (OR 2.13, 95% CI 1.58-2.87, p=7.12e-7). Plasma proteomics from an independent cohort of hospitalized COVID-19 patients (n cases = 131) demonstrated that CyC production was associated with COVID-specific mortality (p=0.0007). Our findings suggest that CyC may be useful for stratification of patients and it has functional role in the host response to COVID-19.

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Cystatin C varies independently of renal function in COVID-19

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A polygenic score for cystatin C production predicts critical COVID-19 illness

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Elevated serum cystatin C is associated with COVID-19 mortality

Clinicopathologic Significance of Predominant Lambda Light Chain Deposition in IgA Nephropathy

Introduction

IgA nephropathy (IgAN) differs from other glomerular diseases by the frequently predominant lambda over kappa light chain deposition. Using the Cure Glomerulonephropathy (CureGN) IgAN cohort, we aimed to determine whether predominant lambda chain deposition is associated with worse clinical outcomes or histopathologic markers of more active disease.

Methods

Patients were categorized based on the intensity of light chain staining. The lambda dominant (LD) group was defined by a difference in intensity score of lambda minus kappa ≥ 1+ and the kappa-lambda codominant (KL) group by a difference < 1+. We compared the clinical course of patients in each category from the time of kidney biopsy and time of enrollment into CureGN to the time of remission (proteinuria < 0.3 g/g), 50% reduction in estimated glomerular filtration rate (eGFR), or progression to end-stage kidney disease (ESKD). We also analyzed differences in histopathologic characteristics between the 2 groups.

Results

Among 440 patients, we found no significant differences between groups in baseline clinical characteristics nor in rates of remission, 50% reduction in eGFR, or progression to ESKD. Patients in the LD group had a modestly greater frequency of IgG staining ≥ 1+. The biopsy results of 234 patients reviewed by CureGN pathologists revealed a greater frequency of endocapillary hypercellularity (51.1% vs. 36.3%, P = 0.04) in the LD group, but no other significant difference in histopathologic features.

Conclusion

In IgAN, we found an association between lambda predominance and increased endocapillary hypercellularity, but no association with clinical outcomes.