Alport syndrome, a rare genetic disorder affecting around 1 in 50,000 individuals, primarily presents as microscopic hematuria and chronic kidney disease (CKD) with associated extrarenal complications. The Alport syndrome results from mutations in COL4A3, COL4A4, and COL4A5 genes, disrupting the formation of the α3–α4–α5 chain in the collagen IV network. The etiology involves X chromosome- related, autosomal dominant, autosomal recessive, and digenic inheritance patterns. The disease primarily manifests as kidney involvement, featuring persistent hematuria, proteinuria, and a progressive decline in renal function. Hearing loss, ocular abnormalities, and extrarenal manifestations further contribute to its complexity. Genotype-phenotype correlations are relatively evident, with distinct presentations in X-linked, autosomal recessive, and autosomal dominant cases. Diagnosis relies on urinalysis, histologic examination, and genetic testing with advancements in next-generation sequencing aiding identification. Although no specific treatment exists, early diagnosis improves outcomes, emphasizing the importance of genetic testing for prognosis and familial screening. The purpose of this review is to advance knowledge and enhance understanding of Alport syndrome.

Kim BJ, et al. Int J Heart Fail. 2022 Apr;4:e12. https://doi.org/10.36628/ijhf.2022.0001

The present study aimed to clinically evaluate the effect of T-cell dysfunction in hemodialysis (HD) patients with latent tuberculosis (TB) infection (LTBI) who were false-negatives in the QuantiFERON-TB Gold In-Tube (QFT-GIT) test. Whole blood samples from a total of 20 active TB patients, 83 HD patients, and 52 healthy individuals were collected, and the QFT-GIT test was used for measuring Mycobacterium tuberculosis (MTB)-specific interferon gamma (IFN-γ) level. The positive rate of the IFN-γ release assays (IGRAs) in HD patients was lower than the negative rate. The mean value of MTB-specific IFN-γ level, which determines the positive rate of the IGRA test, was highest in active TB, followed by HD patients and healthy individuals. Among HD patients, phytohemagglutinin A (PHA)-stimulated IFN-γ levels of approximately 40% were 10.00 IU/mL or less. However, there was no low level of PHA-stimulated IFN-γ in the healthy individuals. This reveals that T-cell function in HD patients was reduced compared to healthy individuals, which leads to the possibility that QFT-GIT results in HD patients are false-negative. The clinical manifestations of TB in patients on HD are quite non-specific, making timely diagnosis difficult and delaying the initiation of curative treatment, delay being a major determinant of outcome.

There have been few reports on the kinetics of hemodialyzed (HD) patients’ immune responses in latent tuberculosis infection (LTBI). Therefore, in the present study, messenger ribonucleic acid (mRNA) expression levels of nine immune markers were analyzed to discriminate between HD patients with LTBI and healthy individuals. Nine cytokines and chemokines were screened through relative mRNA expression levels in whole blood samples after stimulation with Mycobacterium tuberculosis (MTB)-specific antigens from HD patients with LTBI (HD/LTBI), HD patients without LTBI, and healthy individuals, and results were compared with the QuantiFERON-TB Gold In-Tube (QFT-GIT) test. We confirmed that the C-C motif chemokine 11 (CCL11) mRNA expression level of the HD/LTBI group was significantly higher than the other two groups. Especially, the CCL11 mRNA expression level of the >0.7 IU/mL group in the QFT-GIT test was significantly higher than the 0.7 IU/mL group. These results suggest that CCL11 mRNA expression might be an alternative biomarker for LTBI diagnosis in HD patients.

Chronic kidney disease (CKD) affects over 800 million individuals globally and demonstrates significant genetic diversity. Advances in next-generation sequencing have identified over 600 genes associated with inherited kidney disorders, with monogenic variants accounting for 10% to 20% of adult and up to 50% of pediatric CKD cases. Genetic diagnostics, including gene panels, whole-exome sequencing, and whole-genome sequencing, improve diagnostic accuracy, enhance prognostication, and support personalized care. These tools apply to inherited nephropathies such as autosomal dominant polycystic kidney disease, Alport syndrome, congenital anomalies of the kidney and urinary tract, autosomal dominant tubulointerstitial kidney disease, and monogenic nephrotic syndromes. Beyond monogenic disorders, polygenic influences have emerged through genome-wide association studies, but their clinical utility remains to be fully established. Genetic insights not only support diagnosis but also guide treatment strategies, facilitate familial risk assessment, and can eliminate the need for invasive procedures like renal biopsy. Nevertheless, challenges remain, including the interpretation of variants of uncertain significance, limited understanding of genetics among clinicians, and inadequate access to genetic counseling. Despite these obstacles, genetic testing remains essential for deepening our understanding of CKD mechanisms and advancing a personalized approach in nephrology.

We investigated the relationship between geriatric nutritional risk index (GNRI) and subpopulation lymphocyte counts (SLCs) in hemodialysis (HD) and peritoneal dialysis (PD) patients and evaluated whether they can be helpful in the diagnosis of malnutrition in these patients. We examined the GNRI and SLCs of 50 HD patients (mean: 55.8 ± 12.7 years; 28 men and 22 women) and 16 Continuous Ambulatory Peritoneal Dialysis (CAPD) patients (mean: 49.8 ± 14.5 years; 10 men and six women). The GNRI is calculated based on the serum albumin level, dry weight, and ideal body weight and uses the following equation: GNRI = [14.89 × albumin (g/dL)] + [41.7 × (weight/ideal body weight)]. SLCs were evaluated using flow cytometry. T-tests and χ² tests were performed to compare the two groups. Logistic regression analysis was performed for predicting malnutrition in dialysis patients. The average GNRI value was 100.1 ± 8.4 in HD patients and 99.2 ± 8.1 in PD patients, and no significant differences in GNRI or SLC were observed between the two groups. SLCs were higher in patients with higher GNRI (GNRI ≥ 100) although there was no statistical difference. Logistic regression for predicting malnutrition according to GNRI revealed that age, female sex, and CD19 counts predicted malnutrition in HD and PD patients. These results suggest that GNRI and SLCs (especially CD19 count) may be significant nutritional markers in these patients.