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BACKGROUND AND OBJECTIVES: Associations between inflammation and ESRD and death in chronic kidney disease are well established. However, the potential role of the adaptive immune system is uncertain. We aimed to prospectively study the relevance of the adaptive immune system to ESRD and mortality by measuring monoclonal and polyclonal excesses of highly sensitive serum free light chains (sFLCs). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Three hundred sixty-four patients selected from a nephrology outpatient clinic had kappa and lambda sFLCs concentrations and serum immunofixation electrophoresis measured. Cox regression was used to assess the relevance of monoclonal and polyclonal excess of sFLCs to the incidence of ESRD and death (mean follow-up for death 6.0 years). RESULTS: After adjustment for baseline eGFR, there was no significant association between monoclonal excess of sFLCs and risk of ESRD or mortality. Baseline log κ and log λ concentrations were positively associated with ESRD risk, but these associations seemed to be due to correlations with eGFR (per 1 SD higher concentration: adjusted hazard ratio 1.05 [95% confidence interval 0.88 to 1.26] and 0.99 [0.83 to 1.19], respectively). For mortality, after adjustment for eGFR plus markers of cardiac damage, there was weak evidence of an association with λ, but not κ, sFLC concentration (fully adjusted hazard ratio 1.33 [95% confidence interval 1.05 to 1.67] per 1 SD higher concentration). CONCLUSIONS: Associations between monoclonal and polyclonal excess of sFLCs and risk of ESRD are explained by the correlation between these measures and renal function. We found only weak evidence of an association between polyclonal excess of λ sFLC concentration and mortality.

Original publication




Journal article


Clin J Am Soc Nephrol

Publication Date





2829 - 2837


Adult, Aged, Chronic Disease, Female, Glomerular Filtration Rate, Humans, Immunoglobulin Light Chains, Kidney Diseases, Kidney Failure, Chronic, Male, Middle Aged, Paraproteinemias, Proportional Hazards Models, Prospective Studies, Risk Factors