Abstract P188: Association of APOL1 Nephropathy Risk Variants With Inflammatory Biomarkers in the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study
Authors: Chaudhary Ninad S , Tiwari Hemant K , Hidalgo Bertha , Limdi Nita , Reynolds Richard R , Cushman Mary , Zakai Neil , Lange Leslie , Judd Suzanne E , Safford Monika M , Winkler Cheryl , Kopp Jeffrey B , GUTIERREZ Orlando M , Irvin Marguerite R 
Published: December 2020

Introduction:
APOL1
nephropathy risk variants unique to African- ancestry (AA) populations, have an established role in ESRD and cardiovascular outcomes. Ongoing research efforts are now focused on identifying the potential mechanisms resulting in disease phenotypes. While
APOL1
is suggested to alter inflammatory pathways in vivo, few studies have assessed if
APOL1
risk variants are associated with inflammatory biomarkers in population studies.

Hypothesis:
We hypothesized that
APOL1
variants are associated with inflammatory biomarkers among AA participants from the REGARDS cohort.

Methods:
We used baseline data on 10,605 AAs aged ≥45 years from the REGARDS cohort. The primary exposure was the presence of
APOL1
genotypes assessed using additive, recessive and dominant genetic models. Inflammatory biomarkers were C-reactive protein [CRP], white blood cell count [WBC], serum albumin [sALB], and platelet count [PLT]. We categorized each biomarker into quartiles with the lowest quartile as a reference category. We also created an indicator variable (1 vs. 0) which assigned 1 point for having at least one of three inflammation biomarkers (CRP, WBC, sALB) in the high category(quartile 4[q4] for CRP and WBC, quartile 1 [q1] for sALB) indicative of an abnormal inflammatory profile(AIP). We examined the association between
APOL1
and each inflammatory biomarker using multinomial logistic regression models adjusting for age, sex, prevalent conditions (history of stroke, history of coronary heart disease, hypertension, and dyslipidemia), estimated glomerular filtration rate, and principal component of ancestry. We used logistic regression to examine the association between
APOL1
and AIP with similar adjustment for covariates. We further stratified the models by diabetes status.

Results:
Approximately 58% (6,185/10,605) of individuals had at least one
APOL1
risk variant. There were 5,916 individuals with no elevated inflammatory levels while 215 had AIP. Those with AIP were more likely to be female, current smokers, and have diabetes.
APOL1
was independently associated with PLT and sALB on adjusted associations under additive models [PLT: Odds ratio [OR] (95% confidence interval [95%CI]) = 1.12(1.00-1.28), sALB: OR (95%CI) =1.19(1.06-1.33), OR represents q4 vs q1]. Additionally,
APOL1
was associated with a lower odds of AIP (OR 0.93, 95% CI, 0.87-1.00, additive model). Among those with diabetes (N=3,097), the
APOL1
risk genotype was associated with lower odds of AIP under a recessive model (OR 0.73, 95% CI, 0.56-0.96) and an additive model (OR 0.86, 95% CI: 0.75-0.98); the results were not significant among those without diabetes.

Conclusion:
APOL1
risk genotypes are associated with inflammatory biomarkers in a community-based AA sample. These relationships are strongest among those with diabetes.