Lipoprotein glomerulopathy (LPG) is characterized by the accumulation of lipoprotein thrombi within glomerular capillaries. This rare disorder is associated with various types of mutations in the apolipoprotein E gene (apoE). Herein, we present a case of LPG with a combination of apoE Chicago (Arg147Pro) and apoE (Glu3Lys) mutations. A 51-year-old Japanese woman presented with severe (3+) proteinuria. The initial renal biopsy showed glomerular capillary dilation and occlusion with lipid granules, a specific characteristic of LPG. Phenotype, genotype, and apoE DNA sequence analyses detected 2 mutations as described above within the same allele. Although both mutations had already been reported in 1 case of LPG each, this is the first time that the combination of the 2 mutations was identified in the same case. Familial analysis detected the same mutations in the patient’s mother. However, she has not suffered LPG thus far. In addition, a re-analysis of the previous LPG case with apoE (Glu3Lys) also identified the apoE Chicago mutation, as was observed in our case. Treatment with fenofibrate and irbesartan was initiated, and urinary protein excretion ceased within 1 year; recurrence was not observed after an additional 2 years of follow-up. A second biopsy after 2 years showed great improvement, with lipoprotein thrombi identified only in 2 of 18 glomeruli.

IntroductionSeveral anemia guidelines for hemodialysis patients have recommended a target hemoglobin (Hb) range of 10–12 g/dL. However, maintaining Hb values continuously within a narrow target has been difficult, and there has been no generally accepted anemia management algorithm for hemodialysis patients.MethodsIn our study, we created an anemia management algorithm that considers the length of erythrocyte lifetimes, focuses on the combination of erythropoiesis-stimulating agent management and iron administration, and prevents iron deficiency and overload. Our algorithm established a target Hb range of 10–12 g/dL.ResultsWe evaluated our algorithm in 49 patients for 6 months. The mean Hb values were approximately 11 g/dL during our study period. The percentage of patients in the target Hb range of 10–12 g/dL increased from 77.6% (38 of 49) at baseline to 85.7% (42 of 49) at 4–6 months. Throughout monthly regular blood tests during 1–6 months after we introduced our algorithm, Hb values remained within the target range in 55.1% (27 of 49) of patients. The standard deviation of Hb values significantly decreased at 5 and 6 months (P=0.013 and P=0.047, respectively; 1 g/dL at 0 month, 0.7 g/dL at 5 months, and 0.7 g/dL at 6 months). Our algorithm also succeeded in suppressing cumulative doses of iron (≤800 mg) and decreasing the ferritin values significantly (P=0.011). There were no significant differences in erythropoiesis-stimulating agent doses between 0 and 6 months (P=0.357).ConclusionOur anemia management algorithm successfully increased the number of patients in the target Hb range, significantly decreased the Hb standard deviation, suppressed cumulative doses of iron, and decreased ferritin values. These results suggest a better prognosis for hemodialysis patients. Further studies are required to evaluate our algorithm.

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BackgroundBiologic therapies have been bringing huge advantage in the treatment of rheumatoid arthritis, but response to the therapy is heterogeneous. The influence of the body mass index to the treatment is still controversial.ObjectivesTo identify the factors influencing in the response to biologic therapy (bio naïve).MethodsThe analysis of the patients with rheumatoid arthritis who were initiated biologics therapy (bio naïve) between January 2011 to December 2016 in the rheumatology department of a hospital in Japan, was conducted. The effects were evaluated by EULAR response criteria after 6 months of biologic therapy, and factors influencing the response were analyzed in terms of the baseline characteristics (sex, age, disease duration, body mass index, tender joint count, swollen joint count, Patient’s visual analog scale, Doctor’s visual analog scale, erythrocyte sedimentation rate, C-reactive protein, Disease Activity Score in 28 joints, Modified Health Assessment Questionnaire, Methotrexate use, Prednisolone use).Table 1Table 2ResultsThere were differences of baseline characteristics in disease duration and body mass index between the patients who achieved “Good or Moderate response” and “No response” of EULAR response criteria after 6 months of biologic therapy (table 1). The latter was more significant, and the difference was found among biologics (table 2).ConclusionBody mass index influence in the response to first biologic therapy in patients with rheumatoid arthritis.Disclosure of InterestsNone declared