Publications

BACKGROUND AND OBJECTIVES

The natural history of kidney disease among blacks who carry the high-risk variants varies, with only a subgroup progressing to ESRD. We aimed to determine whether the risk variants are associated with incident proteinuria in the context of hypertension-attributed CKD, and whether subsequent kidney function decline after the onset of proteinuria differs by risk status.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Using Cox models, we studied the association between risk status and incident proteinuria (defined as a doubling of urine protein-to-creatinine ratio to a level ≥0.22 g/g creatinine) among African-American Study of Kidney Disease and Hypertension (AASK) trial participants with genotyping and without proteinuria at baseline.

RESULTS

Of the 480 participants in our study, 82 (17%) had the high-risk genotypes (2 alleles), and 254 (53%) developed proteinuria over a median follow-up of 6.8 years. At baseline, mean eGFR was lower in the high-risk group compared with the low-risk group (0 or 1 allele; 49.6 versus 53.2 ml/min per 1.73 m, respectively; =0.02), but median proteinuria was similar (0.04 g/g creatinine for both groups; =0.43). Individuals with the high-risk genotypes were 1.72-fold more likely to develop incident proteinuria compared with those with the low-risk genotypes (95% confidence interval, 1.27 to 2.32), independent of age, sex, ancestry, baseline eGFR, baseline systolic BP, and randomized treatment groups. Although eGFR declined faster after the onset of proteinuria, this rate did not differ significantly by risk status.

CONCLUSIONS

Among blacks with established moderate CKD, the high-risk variants are associated with greater risk of incident proteinuria. After proteinuria onset, kidney function declines more rapidly but does not differ by risk status. This suggests that factors that lead to proteinuria, beyond , may additionally drive CKD progression.

Cytokine-producing CD4 T cells have important roles in immunity against malaria. However, the factors influencing functional differentiation of specific CD4 T cells in naturally exposed children are not well understood. Moreover, it is not known which CD4 T-cell cytokine-producing subsets are most critical for protection. We measured specific IFNγ-, IL10-, and TNFα-producing CD4 T-cell responses by multi-parametric flow cytometry in 265 children aged 6 months to 10 years enrolled in a longitudinal observational cohort in a high malaria transmission site in Uganda. We found that both age and parasite burden were independently associated with cytokine production by CD4 T cells. IL10 production by IFNγ CD4 T cells was higher in younger children and in those with high-parasite burden during recent infection. To investigate the role of CD4 T cells in immunity to malaria, we measured associations of -specific CD4 cytokine-producing cells with the prospective risk of infection and clinical malaria, adjusting for household exposure to -infected mosquitos. Overall, the prospective risk of infection was not associated with the total frequency of specific CD4 T cells, nor of any cytokine-producing CD4 subset. However, the frequency of CD4 cells producing IL10 but not inflammatory cytokines (IFNγ and TNFα) was associated with a decreased risk of clinical malaria once infected. These data suggest that functional polarization of the CD4 T-cell response may modulate the clinical manifestations of malaria and play a role in naturally acquired immunity.

Over the past decade, genetic studies have recognized hundreds of polymorphic DNA loci called response QTLs (reQTLs) as potential contributors to interindividual variation in transcriptional responses to stimulations. Such reQTLs commonly affect the transduction of signals along the regulatory network that controls gene transcription. Identifying the pathways through which reQTLs perturb the underlying network has been a major challenge. Here, we present GEVIN ("Genome-wide Embedding of Variation In Networks"), a methodology that simultaneously identifies a reQTL and the particular pathway in which the reQTL affects downstream signal transduction along the network. Using synthetic data, we show that this algorithm outperforms existing pathway identification and reQTL identification methods. We applied GEVIN to the analysis of murine and human dendritic cells in response to pathogenic components. These analyses revealed significant reQTLs together with their perturbed Toll-like receptor signaling pathways. GEVIN thus offers a powerful framework that renders a comprehensive picture of disease-related DNA loci and their molecular functions within regulatory networks.