Abstract
Importance
Two risk variants in the apolipoprotein L1 gene (APOL1) have been associated with increased susceptibility to sepsis in Black patients. However, it remains unclear whether APOL1 high-risk genotypes are associated with occurrence of either sepsis or sepsis-related phenotypes in patients hospitalized with infections, independent of their association with pre-existing severe renal disease.
Objective
To examine the association between APOL1 high-risk genotypes and the risk of sepsis and sepsis-related phenotypes in patients hospitalized with infections.
Design, setting, and participants
A retrospective cohort study of 2,242 Black patients hospitalized with infections.
Exposures
Carriage of APOL1 high-risk genotypes.
Main outcomes and measures
The primary outcome was sepsis; secondary outcomes were short-term mortality and organ failure related to sepsis.
Results
Of 2,242 Black patients hospitalized with infections, 565 developed sepsis. Patients with high-risk APOL1 genotypes had a significantly increased risk of sepsis (odds ratio [OR]=1.29 [95% CI, 1.00–1.67; p=0.047]); however, this association was not significant after adjustment for pre-existing severe renal disease (OR=1.14 [95% CI, 0.88-1.48; p=0.33]), nor after exclusion of those patients with pre-existing severe renal disease (OR=0.99 [95% CI, 0.70-1.39; p=0.95]. APOL1 high-risk genotypes were significantly associated with the renal dysfunction component of the Sepsis-3 criteria (OR=1.64 [95% CI, 1.21–2.22; p=0.001], but not with other sepsis-related organ dysfunction or short-term mortality. The association between high-risk APOL1 genotypes and sepsis-related renal dysfunction was markedly attenuated by adjusting for pre-existing severe renal disease (OR=1.36 [95% CI, 1.00–1.86; p=0.05]) and was nullified after exclusion of patients with pre-existing severe renal disease (OR=1.16 [95% CI, 0.74–1.81; p=0.52]).
Conclusion and relevance
APOL1 high-risk genotypes were associated with an increased risk of sepsis; however, this increased risk was attributable predominantly to pre-existing severe renal disease.
Introduction
Sepsis is a common cause of morbidity and mortality in the United States, accounting for one in every two to three deaths that occur in hospitals.(1) The risk of sepsis and associated mortality are approximately 60% and 80% higher, respectively, for Black patients compared to White patients.(1, 2) The higher incidence of sepsis in Black individuals persists after adjustment for comorbidities and socioeconomic status, encompassing both a greater risk for developing infection, and once infected, a greater risk of organ dysfunction.(3) Recent work in the Million Veteran Program (MVP) found that variants in the apolipoprotein L1 gene (APOL1), common in people of African ancestry, are associated with sepsis incidence and severity.(4)
Two genetic variants in APOL1—termed G1 (rs73885319/rs60910145) and G2 (rs71785313)— are found almost exclusively in individuals of African ancestry and confer resistance to Trypanosoma brucei infection.(5–8) However, individuals carrying two such alleles (i.e., G1/G1, G1/G2, or G2/G2) have a marked increase in the risk of chronic renal disease; for example, among African Americans, individuals carrying two APOL1 risk alleles are 7.3 times more likely to develop hypertension-associated end-stage renal disease (ESRD) compared to those without two risk alleles.(5) Correspondingly, carriage of two risk alleles is associated with an increased prevalence of numerous renal-related disorders, including hypertension, focal segmental glomerulosclerosis, and HIV-associated nephropathy.(9–11) While these high risk alleles typically follow a pattern of recessive expression (i.e., without increased risk for individuals carrying a single allele), because their carriage rates are so high among African-Americans (10-15% of African-Americans carry two APOL1 risk alleles), a substantial portion of this population faces increased APOL1-related risk.(5)
The specific mechanisms whereby the APOL1 risk variants increase the risk for renal disease are not fully understood, but beyond their role in innate immunity and resistance to trypanosomiasis, the APOL1 risk variants are considered gain-of-injury variants,(12) intensifying autophagy, cell death, endothelial cell inflammation and dysfunction, and immune pathway activation.(4, 13, 14) However, many patients with two APOL1 risk variants never develop renal disease, leading researchers to propose a 2-hit model in which genetic susceptibility combined with an inflammatory trigger leads to disease.(12) Indeed, APOL1 expression is induced by inflammatory cytokines such as tumor necrosis factor alpha and gamma-interferon;(15, 16) thus increased transcription of the gain-of-function variant APOL1 is most likely to occur in the setting of severe infection.
Given the substantive risks and costs associated with sepsis, as well as the reported association between sepsis and the presence of two APOL1 risk alleles,(4) it is critical to better understand whether APOL1 has a direct association with sepsis. More specifically, since APOL1 is associated with renal disease(9, 17–19) and existing renal disease is associated with worse sepsis outcomes(20) (including increased kidney injury), the relationship between APOL1 and sepsis external to existing renal disease remains unclear. Further, it is important to assess whether other organ system dysfunctions typical of sepsis (i.e., hepatic, respiratory, circulatory, and hematologic dysfunction) are associated with APOL1 to appropriately define the causal pathway between APOL1 and sepsis. This determination of association could help guide the viability of implementing treatment options for sepsis using therapies that target APOL1. In particular, several inhibitors of APOL1 are in various stages of development—if APOL1 high-risk genotypes are directly associated with the pathogenesis of sepsis external to pre-existing severe renal disease or other organ system dysfunction, such drugs could be offered to high-risk patients to prevent or treat the occurrence of sepsis in scenarios of acute infection.(21)
The objective of this study was to better understand the relationship between APOL1 and sepsis, focusing on two critical points. First, whether APOL1 high-risk genotypes are associated with the risk of sepsis for patients hospitalized with an infection, particularly independent of the association between the genotypes and severe renal disease. Second, among patients carrying APOL1 high-risk genotypes, whether the risk of organ dysfunction that defines the presence of sepsis is limited to renal dysfunction or if it affects other typical organ system dysfunction components of sepsis.
Methods
Study population and design
This study used data from the Vanderbilt University Medical Center (VUMC) Synthetic Derivative, which contains a de-identified version of the electronic medical records (EHR) for VUMC patients (∼3.6 million individual records as of October 2022). These de-identified EHRs are linked to a biobank (BioVU), which has genome-wide genotyping results for ∼120,000 patients. From these genotyped patients, we constructed a cohort of Black patients admitted to the hospital with an infection to assess the association between carriage of APOL1 high-risk alleles and the occurrence of sepsis before and after consideration of pre-existing severe renal disease. Additionally, to replicate findings from a previously published MVP sepsis study,(4) we performed a restricted phenome-wide association analysis (PheWAS) in all Black patients with existing genotypes; we determined the association between carriage of APOL1 high-risk genotypes and phenotypes previously reported to be associated with sepsis, further expanding the analysis to account for pre-existing severe renal disease based upon the primary analysis of this study.(4) This study was reviewed by the VUMC Institutional Review Board; given the study’s retrospective design and use of deidentified data only, informed consent was waived.
Inclusion/Exclusion Criteria
The primary cohort included individuals with EHR-reported Black race who were admitted to the hospital with an infection between Jan 2000 and Aug 2020 and were ≥18 years old on the day of admission.(22) We selected patients with EHR-reported Black race only (i.e., as reported by the patient or, secondarily, by a provider) because APOL1 high-risk genotypes are virtually exclusive to populations of recent African ancestries,(11, 14, 23, 24) the majority of whom are identified as having Black race in our dataset (i.e., EHR-reported race is highly consistent with genetic ancestry in BioVU).(25) This restriction helps control for factors associated with socially-determined race which may affect individuals’ sepsis outcomes external to genetic ancestry (e.g., an individual with predominantly African genetic ancestry who identifies as having White race). To account for genetic ancestral diversity within the cohort, all analyses were adjusted for principal components for ancestry (see below). The day of hospital admission was designated day 0. International Classification of Disease, ninth revision, Clinical Modification (ICD-9-CM); tenth revision (ICD-10-CM); Current Procedural Terminology (CPT) codes; medications; labs; and clinical notes were used for cohort construction and covariates. Infection was defined as having a billing code indicating an infection and receiving an antibiotic within one day of hospital admission (i.e., on days −1, 0, or +1).(22, 26, 27) We used ICD-9-CM and ICD-10-CM codes for this definition of infection based on the criteria of Angus et al,(28, 29) excluding viral, mycobacterial, fungal, and spirochetal infections, as we have described in detail previously.(22, 26, 27) Only the first hospitalization for infection was included if a patient had more than one qualifying episode. We excluded individuals admitted for cardiac surgery, cardiogenic shock, and organ transplantation, as well as those with no relevant laboratory values (i.e., creatinine, bilirubin, or platelets) on days −1, 0, or +1. We also excluded patients who had a positive test or ICD-10-CM code (U07.1) for coronavirus disease (COVID-19) on days −1, 0, or +1.(22, 26, 27)
Outcomes
The primary outcome was the development of sepsis as indicated by fulfillment of the Sepsis-3 criteria (described below). Secondary outcomes were the individual organ dysfunction criteria in the Sepsis-3 definition (i.e., renal, hepatic, respiratory, circulatory, and hematologic dysfunction) as well as severe sepsis/septic shock, and short-term mortality.
Sepsis was defined by the Sepsis-3 criteria of concurrent infection and organ dysfunction (Supplementary Figure 1)(29, 30) using the EHR definition that was developed in real-world hospital settings(30, 31) and optimized, validated, and applied across EHR systems from 409 hospitals.(30) The algorithm uses billing codes and clinical criteria, with a specificity of 98.1% and a sensitivity of 69.7%.(30) We further adapted (i.e., included relevant ICD-10-CM codes) and then applied the EHR-based Sepsis-3 algorithm to the de-identified EHRs in our system, as described previously.(26, 27) Because the vast majority of community acquired sepsis cases (87%) are present on admission to hospital,(30) we studied sepsis occurring within one day of hospital admission (days −1, 0, and +1) to minimize the confounding effects of sepsis occurring secondary to procedures or events in the hospital. We previously validated this updated algorithm in our EHRs.(22, 26, 27)
In brief, individuals in the infection cohort met the definition of sepsis if they had either ICD codes for septic shock or severe sepsis (ICD-9-CM, 995.92 and 785.52; ICD-10-CM, R65.20 and R65.21) because these are highly specific (99.3%),(30) or they met any Sepsis-3 criterion for serious organ dysfunction (Supplementary Figure 1).(30) Criteria for organ system dysfunction included: (1) circulatory: a) use of a vasopressor, which we extracted as use of levophed (norepinephrine), or b) use of the vasopressors (i.e., dobutamine or dopamine) unrelated to stress echocardiography (CPT codes 78452, 93015, 93018, 93016, 93017, and 93351 within days −1, 0, and 1) and with ≥ 2 mentions of any of the keywords (i.e., “infection,” “sepsis,” or “septic”); (2) respiratory: ICD or CPT codes for ventilation and admission to an ICU; (3) renal: a doubling or greater increase of baseline creatinine (baseline creatinine was defined as the lowest creatinine between 1 year before admission and hospital discharge); (4) hepatic: a total bilirubin ≥ 34.2 umol/L (2 mg/dL) and at least double from baseline (baseline bilirubin was defined as the lowest total bilirubin occurring between 1 year before admission and hospital discharge); and (5) hematologic: a platelet count <100,000 /microL and ≥ 50% decline from a baseline that must have been ≥100,000 (the baseline value was the highest platelet count occurring between 1 year before admission and hospital discharge).(22, 26, 27) Short-term mortality was defined as patients who 1) had death recorded in the EHR within the index hospital stay or 2) were discharged to hospice.(32)
Covariates
We extracted demographic characteristics from the EHRs, including sex and age at the time of the index hospital admission, as well the types of infection at the time of hospitalization (Supplementary Table 1). Comorbidities were collected(33, 34) using relevant diagnostic codes in the year before the index hospital admission (Supplementary Table 2) grouped into the 17 Charlson/Deyo comorbidity categories.(35–37) We also identified patients with pre-existing severe renal disease (i.e., Stage 4/5 chronic kidney disease/ESRD) as evidenced by one or more of the following ICD diagnosis and procedure codes: N18.4, N18.5, N18.6, N18.9, 585.4, 585.5, 585.6, 585.9, 586, Z99.2, Z49.0, Z49.31, 39.95, V45.11, V56.0, Supplementary Table 3). Principal components (PCs) for ancestry were calculated using common variants (minor allele frequency [MAF]>1%) with a high variant call rate (>98%), excluding variants in linkage and regions known to affect PCs (i.e., the HLA region on chromosome 6, inversion on chromosome 8 [8135000-12000000], and inversion on chr 17 [40900000-45000000], GRCh37 build). We calculated 10 PCs for ancestry using SNPRelate version 1.16.0.(38)
Genotyping for APOL1
Genotyping was performed using the Illumina Infinium® Expanded Multi-Ethnic Genotyping Array (MEGAEX). We excluded DNA samples: (1) with a call rate <95%; (2) with inconsistently assigned sex; or (3) that were unexpected duplicates. We performed whole genome imputation using the Michigan Imputation Server(39) with the Haplotype Reference Consortium,(40) version r1.1,(40) (41) as reference; we then filtered variants with (1) low imputation quality (r2 <0.3), (2) MAF <0.5%, and (3) MAF absolute difference >0.3 when compared to the HRC reference panel.
Variants within APOL1 were extracted from imputed genotype data. We used rs73885319 to define G1 and rs12106505 as a proxy for the G2 allele (rs71785313).(17) Individuals who were APOL1 variant allele homozygotes or compound heterozygotes—defined as carriers of 2 copies of rs73885319 (G1/G1), 2 copies of rs12106505 (G2/G2), or 1 copy of each (G1/G2)—were considered to be high risk. Carriers of 1 or 0 APOL1 risk alleles were considered low risk (i.e., a recessive model).(5, 17)
Statistical Analysis
Primary and secondary outcomes in patients with high-risk and low-risk APOL1 genotypes were compared using logistic regression with adjustment for age at hospital admission, sex, and 3 PCs for ancestry. We performed further analyses 1) with additional adjustment for pre-existing severe renal disease (Supplementary Table 3), 2) excluding patients with pre-existing severe renal disease (n=458) from the infection cohort, and 3) including only patients with pre-existing severe renal disease.
In the replication analysis, we examined selected sepsis-related diagnoses previously reported to be associated with the APOL1 high-risk genotype in a restricted PheWAS study.(4) We used a similar approach and performed a restricted PheWAS for the selected sepsis-related phenotypes (i.e., infection of internal prosthetic device, phecode 81; septicemia, phecode 38; sepsis, phecode 994.2, systemic inflammatory response syndrome [SIRS], phecode 994.1; and septic shock, phecode 994.21) in all EHR-reported Black patients in BioVU with MEGAEX genotypes (n=14,713). We identified phenotypes using phecodes, a phenotyping system based on ICD-9-CM and ICD-10-CM diagnosis codes.(42, 43) A phecode amalgamates related ICD codes mapping to a distinct disease or trait.(42, 43) A case was defined as an individual with 2 or more occurrences of the phecode of interest in the EHR. Controls were individuals without that code. Individuals with 1 mention of the code or with related codes were excluded from the analysis to limit misclassification. We conducted logistic regressions with adjustment for age, sex, and 3PCs and, as an expansion of the original approach,(4) repeated the analysis after excluding patients whose EHR contained one or more ICD codes indicating pre-existing severe renal disease (Supplementary Table 3).
Chi-square tests were used to compare categorical characteristics and comorbidities between high- and low-risk APOL1 genotype groups. T-tests were used to compare continuous characteristics. Logistic regression results are presented as odds ratios (ORs) and 95% confidence intervals (Cis); categorical variables are shown as number and percent; continuous variables are shown as median and interquartile range. P-values<0.05 were considered statistically significant, except the restricted PheWAS for which p-values<0.01 (.05 divided by 5 phecodes [namely, infection of internal prosthetic device, septicemia, sepsis, SIRS, and septic shock]) were considered significant. All analyses were conducted using R version 4.1.0.
Results
The primary cohort included 2,242 Black patients hospitalized with an infection; 361 (16.1%) patients carried a high-risk APOL1 genotype, and 1,881 (83.9%) carried low-risk genotypes (Table 1). The baseline characteristics of patients with the high- and low-risk genotypes did not differ significantly in age, sex, and most general medical comorbidities and infection types. However, renal-related comorbidities were significantly more frequent in the high-risk genotype group (p=1.60×10−10) (Table 1).
Associations between high-risk APOL1 genotype and sepsis
Within the primary cohort of patients hospitalized with infections, 565 patients developed sepsis, including 105 (29.1%) with APOL1 high-risk genotypes and 460 (24.5%) with low-risk genotypes. The risk of sepsis was significantly increased among patients with the high-risk APOL1 genotypes (OR=1.29 [95% CI, 1.00–1.67; p=0.047]) (Figure 1). However, the association between sepsis and APOL1 high-risk genotypes was not significant after adjustment for pre-existing severe renal disease (OR=1.14 [95% CI: 0.88-1.48; p=0.33]), nor after exclusion of those patients (n=458) with severe renal disease (OR=0.99 [95% CI, 0.70-1.39; p=0.95]) (Figure 2). We also found no association between sepsis and APOL1 high-risk genotypes in analysis of patients with severe renal disease alone (OR=1.29, [95% CI, 0.84-1.98, p=0.25]).
Associations between the high-risk APOL1 genotypes and components of sepsis or short-term mortality
For secondary outcomes, among the 565 patients with sepsis, 163 (28.8%) had septic shock, 91 (16.1%) had cardiovascular dysfunction, 136 (24.1%) had respiratory dysfunction, 303 (53.6%) had renal dysfunction, 83 (14.7%) had hepatic dysfunction, 102 (18.1%) had hematologic dysfunction, and 84 (14.9%) died or were discharged to hospice. APOL1 high-risk genotypes were significantly associated with renal dysfunction component of the Sepsis-3 criteria (OR=1.64 [95% CI, 1.21–2.22; p=0.001]), but they were not significantly associated with septic shock (OR=1.30 [95% CI, 0.86–1.95; p=0.21]) nor dysfunction of other organ systems (respiratory: OR=0.57 [95% CI, 0.33–1.01; p=0.06]; hematologic: OR=0.86 [95% CI, 0.49–1.51; p=0.60]; circulatory: OR=0.89 [95% CI, 0.50–1.60; p=0.70]; hepatic: OR=1.02 [95% CI, 0.56–1.88; p=0.94]), or short-term mortality (OR=0.71 [95% CI, 0.31–1.39; p=0.31]) (Figure 1, Supplementary Table 4).
The association between high-risk APOL1 genotypes and the renal dysfunction component of the Sepsis-3 criteria was markedly attenuated by adjusting for pre-existing severe renal disease present in the year before the index hospital admission (Figure 2, OR=1.36 [95% CI, 1.00–1.86; p=0.05]) and was nullified after the exclusion of patients with pre-existing severe renal disease (Figure 2, OR=1.16 [95% CI, 0.74–1.81; p=0.52]). We also found no association between APOL1 high-risk genotypes and the renal dysfunction criterion in analysis of patients with severe renal disease alone (OR=1.43, [95% CI, 0.90-2.26, p=0.13]).
Associations between APOL1 high-risk genotype and sepsis-related phenotypes
Using a parallel methodology, the restricted PheWAS performed in Black participants in BioVU (n=14,713, Supplementary Table 5) replicated the association of APOL1 high-risk genotypes and all prespecified sepsis-related phenotypes previously identified as associated with APOL1 high-risk genotypes in an MVP cohort: infection of internal prosthetic device, OR=1.68 [95% CI, 1.32-2.13; p=2.23×10−5]; systemic inflammatory response syndrome [SIRS], OR=1.49 [95% CI, 1.10-2.01; p=9.87×10−3]; sepsis, OR=1.41 [95% CI, 1.18-1.67; p=1.30×10−4]; septic shock, OR=1.51 [95% CI, 1.14-1.99; p=3.89×10−3]; and septicemia, OR=1.30 [95% CI, 1.08-1.56; p=6.01×10−3] (Figure 3, Panel A). However, in an expansion of the original approach, the associations between APOL1 and sepsis-related phenotypes were nullified after we excluded individuals with pre-existing severe renal disease (n=2,166) and reran the analyses (n=12,547, Figure 3, Panel B).
Discussion
This retrospective cohort study found that APOL1 high-risk genotypes were significantly associated with an increased risk of sepsis in patients hospitalized with infections; however, this association was explained predominantly by the presence of pre-existing severe renal disease. Renal dysfunction was the only sepsis-associated organ dysfunction significantly associated with APOL1 high-risk genotypes, and this risk was attenuated by adjustment for pre-existing severe renal comorbidity and nullified by the exclusion of patients with pre-existing severe renal disease. Moreover, there appeared to be no increased risk of sepsis for carriage of high-risk genotypes among patients with pre-existing severe renal disease.
Our findings of an overall increased sepsis risk are consistent with a recent cohort study performed in the MVP which found that high-risk APOL1 genotypes were associated with ∼40% increased risk of sepsis compared to low-risk genotype patients, remaining significant after adjustment for age, sex, and estimated glomerular filtration rate (eGFR).(4) Additional mechanistic analysis in this study observed that APOL1 is highly expressed in the endothelium and that the high-risk variants were associated with increased inflammation, endothelial leakage, and sepsis severity.(4) These findings raised the possibility that strategies to inhibit APOL1 in patients who carry the high-risk variants may have therapeutic potential to prevent occurrence or ameliorate symptoms of sepsis.
This study extends and refines the findings of the MVP study, showing an association, if modest, between high-risk APOL1 genotypes and the occurrence of sepsis among patients admitted to the hospital with infections. However, the association between APOL1 high-risk genotypes and sepsis is driven largely by the presence of pre-existing severe renal disease—a potent risk factor for infection, sepsis, and infection-related mortality.(44, 45) When we adjusted for pre-existing renal comorbidity, the association between APOL1 high-risk genotypes and sepsis was attenuated, and when we removed patients with pre-existing severe renal disease from the analysis, the significant association was nullified. Additionally, in the restricted PheWAS of all Black participants in BioVU (a design parallel to that of the MVP study), we found that APOL1 high-risk genotypes were significantly associated with all prespecified sepsis-related phenotypes. However, those associations were not significant after excluding patients with severe renal disease.
Three differences in study design may contribute to differences in the findings of the two studies. First, the retrospective cohort approach allowed us to better define the temporal relationship between comorbidities and sepsis and its organ dysfunction criteria. Second, we adjusted for renal disease rather than eGFR, because in the setting of dialysis or renal transplantation, the GFR estimated from a creatinine measurement may not capture the increased risk of sepsis in these patients. Third, we used a validated EHR algorithm rather than phecodes to define sepsis; nevertheless, the replication analysis using phecodes was consistent with the primary analysis— APOL1 high-risk genotypes were associated with sepsis-related phecodes; however, these associations were driven by those patients with pre-existing severe renal disease, a known consequence of APOL1 high-risk genotypes.
The lack of association independent of pre-existing severe renal disease suggests that APOL1 high-risk genotypes are not acutely causal of sepsis beyond their association with renal disease and impaired renal function (which, in turn, increases susceptibility to sepsis). These findings more closely parallel those of another MVP study that excluded patients with severe pre-existing renal dysfunction and examined the effects of APOL1 genotypes on outcomes among patients hospitalized with COVID-19 infections. In that study, high-risk APOL1 genotypes were more strongly associated with acute kidney injury(49) than the need for mechanical ventilation or vasopressors. These results suggest that drug therapies in development to prevent and treat diseases associated with APOL1 high-risk genotypes might primarily affect the renal vulnerabilities that increase risk of sepsis, rather than immediate prevention of sepsis or acute treatment of sepsis once hospitalized.
The current study offers several strengths. First, we identified patients progressing from infection to sepsis using a validated EHR algorithm. This approach also allowed us to evaluate each organ dysfunction and its contribution to sepsis separately. Second, by leveraging the rich longitudinal EHRs, we were able to identify pre-existing severe renal disease and assess its effect on the risk of developing sepsis. Third, we performed analyses that included, excluded, and exclusively focused on patients with pre-existing chronic severe renal disease, allowing us to more completely define the contribution of APOL1 high-risk genotypes to the development of sepsis.
We also acknowledge the study’s limitations, primarily related to a retrospective cohort study using EHR information. First, ascertainment of comorbidities was based on ICD codes, and these may not completely reflect comorbidities. Second, there are many factors that affect health (e.g., alcohol use, diet, and lifestyle) that are not captured well in the EHR but could impact susceptibility to sepsis; however, there is no reason to expect that such factors are differentially distributed according to genotype. Third, we defined death as short-term mortality, including in-hospital death and discharge to hospice;(32) this definition may underestimate the true mortality rate due to sepsis. Fourth, we did not include patients with concurrent COVID-19 infections because their clinical manifestations and genetic predispositions might differ from that of patients who develop sepsis after presumed bacterial infection. Fifth, as we did not find an association after adjustment for pre-existing severe renal disease, we did not perform any additional functional analysis. Last, a larger cohort of Black patients with infection and sepsis could potentially provide more power such that the confidence intervals around the point estimates were smaller, more definitively excluding the possibility of clinically important differences in outcomes; a larger cohort could also provide the opportunity for additional granularity in analysis (e.g., stratified by whether patients are on dialysis).
In conclusion, in this cohort of Black participants hospitalized with infection, APOL1 high-risk genotypes were associated with an increased risk of sepsis; however, this increased risk was attributable predominantly to pre-existing severe renal disease. Further, renal dysfunction was the only sepsis-associated organ dysfunction associated with APOL1 high-risk genotypes.
Data Availability
All data produced in the present study are available upon reasonable request to the authors
Acknowledgements
The first and corresponding authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
References
- 1.The epidemiology of sepsis in the United States from 1979 through 2000N Engl J Med 348:1546–1554
- 2.Current Trends in Sepsis-Related Mortality in the United StatesCrit Care Med 49:1276–1284
- 3.Infection rate and acute organ dysfunction risk as explanations for racial differences in severe sepsisJAMA 303:2495–2503
- 4.APOL1 risk variants in individuals of African genetic ancestry drive endothelial cell defects that exacerbate sepsisImmunity 54:2632–2649
- 5.Association of trypanolytic ApoL1 variants with kidney disease in African AmericansScience 329:841–845
- 6.The Cell Biology of APOL1Semin Nephrol 37:538–545
- 7.Missense mutations in the APOL1 gene are highly associated with end stage kidney disease risk previously attributed to the MYH9 geneHum Genet 128:345–350
- 8.Apolipoprotein L1 gene variants associate with hypertension-attributed nephropathy and the rate of kidney function decline in African AmericansKidney Int 83:114–120
- 9.APOL1 variants associate with increased risk of CKD among African AmericansJ Am Soc Nephrol 24:1484–1491
- 10.APOL1-Associated Nephropathy: A Key Contributor to Racial Disparities in CKDAmerican Journal of Kidney Diseases 72:S8–S16
- 11.APOL1 genetic variants in focal segmental glomerulosclerosis and HIV-associated nephropathyJ Am Soc Nephrol 22:2129–2137
- 12.APOL1 nephropathy: from gene to mechanisms of kidney injuryNephrol Dial Transplant 31:349–358
- 13.APOL1 and Kidney Disease: From Genetics to BiologyAnnu Rev Physiol 82:323–342
- 14.The evolving story of apolipoprotein L1 nephropathy: the end of the beginningNat Rev Nephrol 18:307–320
- 15.APOL1 toxin, innate immunity, and kidney injuryKidney Int 88:28–34
- 16.Innate immunity pathways regulate the nephropathy gene Apolipoprotein L1Kidney Int 87:332–342
- 17.Phenome-wide association analysis suggests the APOL1 linked disease spectrum primarily drives kidney-specific pathwaysKidney International 97:1032–1041
- 18.: Kidney disease and APOL1Human Molecular Genetics 30:R129–R137
- 19.Race, APOL1 Risk Variants, and Clinical Outcomes among Older Adults: The ARIC StudyJ Am Geriatr Soc 69:155–163
- 20.Pre-existing Renal Disease Promotes Sepsis-induced Acute Kidney Injury and Worsens Sepsis Outcome via Multiple PathwaysKidney Int 74:1017–1025
- 21.Treatment potential in APOL1-associated nephropathyCurr Opin Nephrol Hypertens 31:442–448
- 18.The Relationship between High Density Lipoprotein Cholesterol and Sepsis: A Clinical and Genetic ApproachClin Transl Sci. Published online January 16https://doi.org/10.1111/cts.13462
- 23.APOL1 Kidney Risk Alleles: Population Genetics and Disease AssociationsAdv Chronic Kidney Dis 21:426–433
- 24.Analytical Validation of a Personalized Medicine APOL1 Genotyping Assay for Nondiabetic Chronic Kidney Disease Risk AssessmentThe Journal of Molecular Diagnostics 18:260–266
- 25.Assessing the accuracy of observer-reported ancestry in a biorepository linked to electronic medical recordsGenet Med 12:648–650
- 26.A Genetic Approach to the Association Between PCSK9 and SepsisJAMA Netw Open 2:e1911130–e1911130
- 27.Association Between Low-Density Lipoprotein Cholesterol Levels and Risk for Sepsis Among Patients Admitted to the Hospital With InfectionJAMA Netw Open 2
- 28.Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of careCrit Care Med 29:1303–1310
- 29.Application of the Third International Consensus Definitions for Sepsis (Sepsis-3) Classification: a retrospective population-based cohort study [Internet]
- 30.Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014JAMA 318:1241–1249
- 31.Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)JAMA 315:762–774
- 32.Prevalence and Outcomes of Previously Healthy Adults Among Patients Hospitalized With Community-Onset SepsisChest 162:101–110
- 33.Charlson Comorbidity Index (CCI) [Internet]. MDCalc [cited 2019 May 7] Available from: https://www.mdcalc.com/charlson-comorbidity-index-cciMDCalc
- 34.Charlson/Deyo Score | National Cancer Data Base - Data Dictionary PUF 2013 [Internet]. [cited 2020 May 6] Available from: http://ncdbpuf2013.facs.org/content/charlsondeyo-comorbidity-index
- 35.Adapting a clinical comorbidity index for use with ICD-9-CM administrative databasesJournal of Clinical Epidemiology 45:613–619
- 36.A new method of classifying prognostic comorbidity in longitudinal studies: development and validationJ Chronic Dis 40:373–383
- 37.Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative dataMed Care 43:1130–1139
- 38.A High-Performance Computing Toolset for Relatedness and Principal Component Analysis of SNP Data [Internet]Bioinformatics (Oxford, England) 28
- 39.Next-generation genotype imputation service and methodsNature Genetics 48
- 40.A reference panel of 64,976 haplotypes for genotype imputationNature Genetics 48
- 41.Common variants associated with plasma triglycerides and risk for coronary artery diseaseNat Genet 45:1345–1352
- 42.Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health recordPLoS ONE 12
- 43.Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial EvaluationJMIR Medical Informatics 7
- 44.Mortality caused by sepsis in patients with end-stage renal disease compared with the general populationKidney Int 58:1758–1764
- 45.Chronic kidney disease and risk of death from infectionAm J Nephrol 34:330–336
Article and author information
Author information
Version history
- Preprint posted:
- Sent for peer review:
- Reviewed Preprint version 1:
- Reviewed Preprint version 2:
- Version of Record published:
Copyright
© 2023, Jiang et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
- views
- 484
- downloads
- 35
- citation
- 1
Views, downloads and citations are aggregated across all versions of this paper published by eLife.