Genome-wide polygenic score to predict chronic kidney disease across ancestries

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

BACKGROUND

Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations.

METHODS

We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts.

RESULTS

The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance.

CONCLUSIONS

By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Snapshots of nascent RNA reveal cell- and stimulus-specific responses to acute kidney injury

The current strategy to detect acute injury of kidney tubular cells relies on changes in serum levels of creatinine. Yet serum creatinine (sCr) is a marker of both functional and pathological processes and does not adequately assay tubular injury. In addition, sCr may require days to reach diagnostic thresholds, yet tubular cells respond with programs of damage and repair within minutes or hours. To detect acute responses to clinically relevant stimuli, we created mice expressing Rosa26-floxed-stop uracil phosphoribosyltransferase (Uprt) and inoculated 4-thiouracil (4-TU) to tag nascent RNA at selected time points. Cre-driven 4-TU-tagged RNA was isolated from intact kidneys and demonstrated that volume depletion and ischemia induced different genetic programs in collecting ducts and intercalated cells. Even lineage-related cell types expressed different genes in response to the 2 stressors. TU tagging also demonstrated the transient nature of the responses. Because we placed Uprt in the ubiquitously active Rosa26 locus, nascent RNAs from many cell types can be tagged in vivo and their roles interrogated under various conditions. In short, 4-TU labeling identifies stimulus-specific, cell-specific, and time-dependent acute responses that are otherwise difficult to detect with other technologies and are entirely obscured when sCr is the sole metric of kidney damage.

Identification of a shared genetic risk locus for Kawasaki disease and immunoglobulin A vasculitis by a cross-phenotype meta-analysis

OBJECTIVES

Combining of genomic data of different pathologies as a single phenotype has emerged as a useful strategy to identify genetic risk loci shared among immune-mediated diseases. Our study aimed to increase our knowledge of the genetic contribution to Kawasaki disease (KD) and IgA vasculitis (IgAV) by performing the first comprehensive large-scale analysis on the genetic overlap between them.

METHODS

A total of 1190 vasculitis patients and 11 302 healthy controls were analysed. First, in the discovery phase, genome-wide data of 405 KD patients and 6252 controls and 215 IgAV patients and 1324 controls, all of European origin, were combined using an inverse variance meta-analysis. Second, the top associated polymorphisms were selected for replication in additional independent cohorts (570 cases and 3726 controls). Polymorphisms with P-values ≤5 × 10-8 in the global IgAV-KD meta-analysis were considered as shared genetic risk loci.

RESULTS

A genetic variant, rs3743841, located in an intron of the NAGPA gene, reached genome-wide significance in the cross-disease meta-analysis (P = 8.06 × 10-10). Additionally, when IgAV was individually analysed, a strong association between rs3743841 and this vasculitis was also evident [P = 1.25 × 10-7; odds ratio = 1.47 (95% CI 1.27, 1.69)]. In silico functional annotation showed that this polymorphism acts as a regulatory variant modulating the expression levels of the NAGPA and SEC14L5 genes.

CONCLUSION

We identified a new risk locus with pleiotropic effects on the two childhood vasculitides analysed. This locus represents the strongest non-HLA signal described for IgAV to date.

Multi-ancestry fine mapping implicates OAS1 splicing in risk of severe COVID-19

The OAS1/2/3 cluster has been identified as a risk locus for severe COVID-19 among individuals of European ancestry, with a protective haplotype of approximately 75 kilobases (kb) derived from Neanderthals in the chromosomal region 12q24.13. This haplotype contains a splice variant of OAS1, which occurs in people of African ancestry independently of gene flow from Neanderthals. Using trans-ancestry fine-mapping approaches in 20,779 hospitalized cases, we demonstrate that this splice variant is likely to be the SNP responsible for the association at this locus, thus strongly implicating OAS1 as an effector gene influencing COVID-19 severity.

Glomerular Diseases of the Kidney Allograft: Toward a Precision Medicine Approach

The continual development of potent immunosuppressive regimens has led to a decreased incidence of acute rejection and improvement of short-term kidney allograft survival. In contrast to acute rejection, glomerular diseases of the kidney allograft are being encountered more frequently and are emerging as leading causes of late kidney allograft failure. Although data on the pathogeneses of glomerular diseases in the kidney allograft are sparse, cumulative evidence suggests that post-transplant glomerular diseases may be the result of inherited predispositions and immunologic triggers. Although studying immunologic signals and performing genome-wide association studies are ideal approaches to tackle glomerular diseases in the kidney allograft, such studies are challenging because of the lack of adequately powered cohorts. In this review, we focus on the most commonly encountered recurrent and de novo glomerular diseases in the kidney allograft. We address the important advances made in understanding the immunopathology and genetic susceptibility of glomerular diseases in the native kidney and how to benefit from such knowledge to further our knowledge of post-transplant glomerular diseases. Defining genomic and immune predictors for glomerular diseases in the kidney allograft would support novel donor-recipient matching strategies and development of targeted therapies to ultimately improve long-term kidney allograft survival.

Clinical Predictors and Prognosis of Recurrent IgA Nephropathy in the Kidney Allograft

Introduction

Although IgA nephropathy (IgAN) is the most common recurrent glomerulonephritis encountered in the kidney allograft, the clinical and immunogenetic characteristics remain poorly understood. We sought to study determinants and prognosis of recurrent IgAN with special focus on HLA antigens.

Materials and Methods

Between 2005 and 2019, we identified 282 transplanted patients with failure secondary to IgAN from two North American and one European Medical Centers, including 80 with recurrent IgAN and 202 without recurrence. Prevalence of HLA antigens was compared to external healthy controls of European ancestry (n=15,740). Graft survival was assessed by Kaplan-Meier method and log rank test. Cox proportional hazards were used for multivariable analyses.

Results

Compared to external controls of European ancestry, kidney transplant recipients of European ancestry with kidney failure secondary to IgAN had higher frequency of HLA-DQ5 (42% vs. 30%, OR=1.68, P=0.002) and lower frequency of HLA-DR15 (15% vs. 28%, OR=0.46, P<0.001) and HLA-DQ6 (32% vs. 45%, OR=0.59, P=0.003); however, the frequency of these HLA antigens were similar in recurrent versus non-recurring IgAN. Younger recipient age at transplantation was an independent predictor of recurrence. HLA-matching was an independent predictor for recurrent IgAN only in recipients of living-related but not deceased or living unrelated transplants. Recurrent IgAN was an independent predictor of allograft failure, along with acute rejection. In patients with recurrent IgAN, serum creatinine at biopsy, degree of proteinuria, and concurrent acute rejection were associated with inferior allograft survival.

Discussion/ Conclusion

Recurrent IgAN negatively affects allograft survival. Younger recipient age at transplantation is an independent predictor of recurrent IgAN, while the presence of HLA antigens associated with IgAN in the native kidney and HLA-matching in recipients of deceased or living unrelated transplants are not.

Elevated Neutrophil Gelatinase-Associated Lipocalin Is Associated With the Severity of Kidney Injury and Poor Prognosis of Patients With COVID-19

INTRODUCTION

Loss of kidney function is a common feature of COVID-19 infection, but serum creatinine (SCr) is not a sensitive or specific marker of kidney injury. We tested whether molecular biomarkers of tubular injury measured at hospital admission were associated with acute kidney injury (AKI) in those with COVID-19 infection.

METHODS

This is a prospective cohort observational study consisting of 444 consecutive patients with SARS-CoV-2 enrolled in the Columbia University emergency department (ED) at the peak of the pandemic in New York (March 2020-April 2020). Urine and blood were collected simultaneously at hospital admission (median time: day 0, interquartile range: 0-2 days), and urine biomarkers were analyzed by enzyme-linked immunosorbent assay (ELISA) and a novel dipstick. Kidney biopsies were probed for biomarker RNA and for histopathologic acute tubular injury (ATI) scores.

RESULTS

Admission urinary neutrophil gelatinase-associated lipocalin (uNGAL) level was associated with AKI diagnosis (267 ± 301 vs. 96 ± 139 ng/ml, P < 0.0001) and staging; uNGAL levels >150 ng/ml had 80% specificity and 75% sensitivity to diagnose AKI stages 2 to 3. Admission uNGAL level quantitatively associated with prolonged AKI, dialysis, shock, prolonged hospitalization, and in-hospital death, even when admission SCr level was not elevated. The risk of dialysis increased almost 4-fold per SD of uNGAL independently of baseline SCr, comorbidities, and proteinuria (odds ratio [OR] [95% CI]: 3.59 [1.83-7.45], P < 0.001). In the kidneys of those with COVID-19, NGAL mRNA expression broadened in parallel with severe histopathologic injury (ATI). Conversely, low uNGAL levels at admission ruled out stages 2 to 3 AKI (negative predictive value: 0.95, 95% CI: 0.92-0.97) and the need for dialysis (negative predictive value: 0.98, 95% CI: 0.96-0.99). Although proteinuria and urinary (u)KIM-1 were implicated in tubular injury, neither was diagnostic of AKI stages.

CONCLUSION

In the patients with COVID-19, uNGAL level was quantitatively associated with histopathologic injury (ATI), loss of kidney function (AKI), and severity of patient outcomes.

Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality

BACKGROUND

There is considerable variability in COVID-19 outcomes amongst younger adults-and some of this variation may be due to genetic predisposition.

METHODS

We combined individual level data from 13,888 COVID-19 patients (N=7,185 hospitalized) from 17 cohorts in nine countries to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications and laboratory values. We next performed meta-analyses using FinnGen and the Columbia University COVID-19 Biobank.

RESULTS

We found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (HR 1.4, 95%CI 1.2-1.7). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (OR 2.1, 95%CI 1.6-2.6), venous thromboembolism (OR 1.7, 95%CI 1.2-2.4), and hepatic injury (OR 1.5, 95%CI 1.2-2.0). Risk allele carriers ≤60 years had higher odds of death or severe respiratory failure (OR 2.7, 95%CI 1.8-3.9) compared to those >60 years (OR 1.5, 95%CI 1.2-1.8, interaction-p=0.038). Amongst individuals ≤60 years who died or experienced severe respiratory failure, 32.3% were risk variant carriers, compared to 13.9% of those not experiencing these outcomes. The genetic risk improved the prediction of death or severe respiratory failure similarly to, or better than, most established clinical risk factors.

CONCLUSIONS

The major common COVID-19 genetic risk factor is associated with increased risks of morbidity and mortality, which are more pronounced amongst individuals ≤60 years. The effect was similar in magnitude and more common than most established clinical risk factors, suggesting potential implications for future clinical risk management.

Improving Clinical Trials for Anticomplement Therapies in Complement-Mediated Glomerulopathies: Report of a Scientific Workshop Sponsored by the National Kidney Foundation

Blocking the complement system as a therapeutic strategy has been proposed for numerous glomerular diseases but presents myriad questions and challenges, not the least of which is demonstrating efficacy and safety. In light of these potential issues and because there are an increasing number of anticomplement therapy trials either planned or under way, the National Kidney Foundation facilitated an all-virtual scientific workshop entitled "Improving Clinical Trials for Anti-Complement Therapies in Complement-Mediated Glomerulopathies." Attended by patient representatives and experts in glomerular diseases, complement physiology, and clinical trial design, the aim of this workshop was to develop standards applicable for designing and conducting clinical trials for anticomplement therapies across a wide spectrum of complement-mediated glomerulopathies. Discussions focused on study design, participant risk assessment and mitigation, laboratory measurements and biomarkers to support these studies, and identification of optimal outcome measures to detect benefit, specifically for trials in complement-mediated diseases. This report summarizes the discussions from this workshop and outlines consensus recommendations.

Generalizability of Polygenic Risk Scores for Breast Cancer Among Women With European, African, and Latinx Ancestry

IMPORTANCE

Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown.

OBJECTIVE

To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm.

MAIN OUTCOMES AND MEASURES

Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components.

RESULTS

This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations.

CONCLUSIONS AND RELEVANCE

This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.

Medical Records-Based Genetic Studies of the Complement System

BACKGROUND

Genetic variants in complement genes have been associated with a wide range of human disease states, but well-powered genetic association studies of complement activation have not been performed in large multiethnic cohorts.

METHODS

We performed medical records-based genome-wide and phenome-wide association studies for plasma C3 and C4 levels among participants of the Electronic Medical Records and Genomics (eMERGE) network.

RESULTS

In a GWAS for C3 levels in 3949 individuals, we detected two genome-wide significant loci: chr.1q31.3 (CFH locus; rs3753396-A; β=0.20; 95% CI, 0.14 to 0.25; P=1.52x10-11) and chr.19p13.3 (C3 locus; rs11569470-G; β=0.19; 95% CI, 0.13 to 0.24; P=1.29x10-8). These two loci explained approximately 2% of variance in C3 levels. GWAS for C4 levels involved 3998 individuals and revealed a genome-wide significant locus at chr.6p21.32 (C4 locus; rs3135353-C; β=0.40; 95% CI, 0.34 to 0.45; P=4.58x10-35). This locus explained approximately 13% of variance in C4 levels. The multiallelic copy number variant analysis defined two structural genomic C4 variants with large effect on blood C4 levels: C4-BS (β=-0.36; 95% CI, -0.42 to -0.30; P=2.98x10-22) and C4-AL-BS (β=0.25; 95% CI, 0.21 to 0.29; P=8.11x10-23). Overall, C4 levels were strongly correlated with copy numbers of C4A and C4B genes. In comprehensive phenome-wide association studies involving 102,138 eMERGE participants, we cataloged a full spectrum of autoimmune, cardiometabolic, and kidney diseases genetically related to systemic complement activation.

CONCLUSIONS

We discovered genetic determinants of plasma C3 and C4 levels using eMERGE genomic data linked to electronic medical records. Genetic variants regulating C3 and C4 levels have large effects and multiple clinical correlations across the spectrum of complement-related diseases in humans.

Rare loss-of-function variants in type I IFN immunity genes are not associated with severe COVID-19

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks. We tested whether rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only 1 rare pLOF mutation across these genes among 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We found no evidence of association of rare LOF variants in the 13 candidate genes with severe COVID-19 outcomes.

Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

Rationale and design of the Kidney Precision Medicine Project

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

Novel EDGE encoding method enhances ability to identify genetic interactions

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)–rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Although traditional genetic encodings are widely implemented in genetics research, including in genome-wide association studies (GWAS) and epistasis, each method makes assumptions that may not reflect the underlying etiology. Here, we introduce a novel encoding method that estimates and assigns an individualized data-driven encoding for each single nucleotide polymorphism (SNP): the elastic data-driven genetic encoding (EDGE). With simulations, we demonstrate that this novel method is more accurate and robust than traditional encoding methods in estimating heterozygous genotype values, reducing the type I error, and detecting SNP-SNP interactions. We further applied the traditional encodings and EDGE to biomedical data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes, and EDGE identified a novel interaction for age-related cataract not detected by traditional methods, which replicated in data from the UK Biobank. EDGE provides an alternative approach to understanding and modeling diverse SNP models and is recommended for studying complex genetics in common human phenotypes.

Hematopoietic mosaic chromosomal alterations increase the risk for diverse types of infection

Age is the dominant risk factor for infectious diseases, but the mechanisms linking age to infectious disease risk are incompletely understood. Age-related mosaic chromosomal alterations (mCAs) detected from genotyping of blood-derived DNA, are structural somatic variants indicative of clonal hematopoiesis, and are associated with aberrant leukocyte cell counts, hematological malignancy, and mortality. Here, we show that mCAs predispose to diverse types of infections. We analyzed mCAs from 768,762 individuals without hematological cancer at the time of DNA acquisition across five biobanks. Expanded autosomal mCAs were associated with diverse incident infections (hazard ratio (HR) 1.25; 95% confidence interval (CI) = 1.15-1.36; P = 1.8 × 10-7), including sepsis (HR 2.68; 95% CI = 2.25-3.19; P = 3.1 × 10-28), pneumonia (HR 1.76; 95% CI = 1.53-2.03; P = 2.3 × 10-15), digestive system infections (HR 1.51; 95% CI = 1.32-1.73; P = 2.2 × 10-9) and genitourinary infections (HR 1.25; 95% CI = 1.11-1.41; P = 3.7 × 10-4). A genome-wide association study of expanded mCAs identified 63 loci, which were enriched at transcriptional regulatory sites for immune cells. These results suggest that mCAs are a marker of impaired immunity and confer increased predisposition to infections.

Early detection of SARS-CoV-2 and other infections in solid organ transplant recipients and household members using wearable devices

The increasing global prevalence of SARS-CoV-2 and the resulting COVID-19 disease pandemic pose significant concerns for clinical management of solid organ transplant recipients (SOTR). Wearable devices that can measure physiologic changes in biometrics including heart rate, heart rate variability, body temperature, respiratory, activity (such as steps taken per day) and sleep patterns, and blood oxygen saturation show utility for the early detection of infection before clinical presentation of symptoms. Recent algorithms developed using preliminary wearable datasets show that SARS-CoV-2 is detectable before clinical symptoms in >80% of adults. Early detection of SARS-CoV-2, influenza, and other pathogens in SOTR, and their household members, could facilitate early interventions such as self-isolation and early clinical management of relevant infection(s). Ongoing studies testing the utility of wearable devices such as smartwatches for early detection of SARS-CoV-2 and other infections in the general population are reviewed here, along with the practical challenges to implementing these processes at scale in pediatric and adult SOTR, and their household members. The resources and logistics, including transplant-specific analyses pipelines to account for confounders such as polypharmacy and comorbidities, required in studies of pediatric and adult SOTR for the robust early detection of SARS-CoV-2, and other infections are also reviewed.