Despite the extensive efforts of scientists, the genetic background of diabetic nephropathy (DN) has not yet been clarified. To elucidate the genetic variants that predispose to the development of DN, we conducted a systematic review and meta-analysis of all available genetic association studies (GAS) of DN. We searched in the Human Genome Epidemiology Navigator (HuGE Navigator) and PubMed for available GAS of DN. The threshold for meta-analysis was three studies per genetic variant. The association between genotype distribution and DN was examined using the generalized linear odds ratio (OR_G). For variants with available allele frequencies, the examined model was the allele contrast. The pooled OR was estimated using the DerSimonian and Laird random effects model. The publication bias was assessed with Egger’s test. We performed pathway analysis of significant genes with DAVID 6.7. Genetic data of 606 variants located in 228 genes were retrieved from 360 GASs and were synthesized with meta-analytic methods. ACACB, angiotensin I-converting enzyme (ACE), ADIPOQ, AGT, AGTR1, AKR1B1, APOC1, APOE, ATP1B2, ATP2A3, CARS, CCR5, CGNL1, Carnosine dipeptidase 1 (CNDP1), CYGB-PRCD, EDN1, Engulfment and cell motility 1 (ELMO1), ENPP1, EPO, FLT4, FTO, GLO1, HMGA2, IGF2/INS/TH cluster, interleukin 1B (IL1B), IL8, IL10, KCNQ1, KNG, LOC101927627, Methylenetetrahydrofolate reductase, nitric oxide synthase 3 (NOS3), SET domain containing seven, histone lysine methyltransferase (SETD7), Sirtuin 1 (SIRT1), SLC2A1, SLC2A2, SLC12A3, SLC19A3, TCF7L2, TGFB1, TIMP1, TTC39C, UNC13B, VEGFA, WTAPP1, WWC1 as well as XYLT1 and three intergenic polymorphisms showed significant association with DN. Pathway analysis revealed the overrepresentation of six signalling pathways. The significant findings provide further evidence for genetic factors implication in DN offering new perspectives in discovery of new therapies.

Background: Despite the certain contribution of metabolic and haemodynamic factors in diabetic nephropathy (DN), many lines of evidence highlight the role of immunologic and inflammatory mechanisms. To elucidate the contribution of the immune system in the development of DN, we explored the contribution of gene variants (polymorphisms) in relevant pathophysiologic pathways. Methods: We selected six major pathways related to immune response from the Kyoto Encyclopaedia of Genes and Genomes database and thereafter we traced all available genetic association studies (GASs) involving gene variants in these pathways from PubMed and HuGE Navigator. Finally, we used meta-analytic methods for synthesizing the results of the GASs. Results: One hundred three GASs were retrieved that included 443 variants from 75 genes. Of those variants, 138 were meta-analysed and 61 produced significant results; seven variants were investigated in single GASs and showed significant association. Variants in CCL2, CCR5, IL6, IL8, EPO, IL1A, IL1B, IL100, IL1RN, GHRL, MMP9, TGFB1, VEGFA, MMP3, MMP12, IL12RB1, PRKCE, TNF and TNFRSF19 genes were associated with an increased risk of DN. Conclusions: There is evidence that variants related with immunologic response affect the course of DN. However, the present results should be interpreted with caution since the current number of available GASs is limited.

Renal fibrosis (RF) constitutes the common end-point of all kinds of chronic kidney disease (CKD), regardless of the initial cause of disease. The aim of the present study was to identify the key players of fibrosis in the context of diabetic nephropathy (DN). A systematic review and meta-analysis of all available genetic association studies regarding the genes that are included in signaling pathways related to RF were performed. The evaluated studies were published in English and they were included in PubMed and the GWAS Catalog. After an extensive literature review and search of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, eight signaling pathways related to RF were selected and all available genetic association studies of these genes were meta-analyzed. ACE, AGT, EDN1, EPO, FLT4, GREM1, IL1B, IL6, IL10, IL12RB1, NOS3, TGFB1, IGF2/INS/TH cluster, and VEGFA were highlighted as the key genetic components driving the fibrosis process in DN. The present systematic review and meta-analysis indicate, as key players of fibrosis in DN, sixteen genes. However, the results should be interpreted with caution because the number of studies was relatively small.

An association study was conducted to investigate the relation between 14 variants of glucose transporter 1 gene (SLC2A1) and the risk of type 2 diabetes (T2DM) leading to nephropathy. We also performed a meta-analysis of 11 studies investigating association between diabetic nephropathy (DN) and SLC2A1 variants. The cohort included 197 cases (T2DM with nephropathy), 155 diseased controls (T2DM without nephropathy) and 246 healthy controls. The association of variants with disease progression was tested using generalized odds ratio (ORG). The risk of type 2 diabetes leading to nephropathy was estimated by the OR of additive and co-dominant models. The mode of inheritance was assessed using the degree of dominance index (h-index). We synthesized results of 11 studies examining association between 5 SLC2A1 variants and DN. ORG was used to assess the association between variants and DN using random effects models. Significant results were derived for co-dominant model of rs12407920 [OR = 2.01 (1.17-3.45)], rs841847 [OR = 1.73 (1.17-2.56)] and rs841853 [OR = 1.74 (1.18-2.55)] and for additive model of rs3729548 [OR = 0.52 (0.29-0.90)]. The mode of inheritance for rs12407920, rs841847 and rs841853 was 'dominance of each minor allele' and for rs3729548 'non-dominance'. Frequency of one haplotype (C-G-G-A-T-C-C-T-G-T-C-C-A-G) differed significantly between cases and healthy controls [p = .014]. Regarding meta-analysis, rs841853 contributed to an increased risk of DN [(ORG = 1.43 (1.09-1.88); ORG = 1.58 (1.01-2.48)] between diseased controls versus cases and healthy controls versus cases, respectively. Further studies confirm the association of rs12407920, rs841847, rs841853, as well as rs3729548 and the risk of T2DM leading to nephropathy.

Heart failure (HF) and chronic kidney disease (CKD) are associated with high mortality. In both disorders, impaired iron homeostasis, mostly in the form of a functional iron deficiency, is a frequent co-morbidity. In HF, functional iron deficiency and management by i.v. iron supplementation have been proven to affect both prognosis and functional capacity. In the same context, iron supplementation is routine for the adequate management of renal anemia in CKD. In numerous recent studies in HF and in CKD, sodium–glucose transporter 2 (SGLT2) inhibitor treatment has been proven to significantly reduce mortality. Furthermore, the same trials showed that these drugs alleviate iron deficiency and anemia. These effects of SGLT2 inhibitors may be due to an amelioration of inflammation with reduced interleukin-6 (IL-6) and to an enhancement of autophagy with increased sirtuin 1 (SIRT1), both associated with modified production of hepcidin and enhanced ferritinophagy. However, the exact pathogenic basis of the beneficial SGLT2 inhibitor action is not fully elucidated. Nevertheless, effects on iron homeostasis might be a potential explanatory mechanism for the powerful SGLT2 inhibitors’ cardiovascular and renal outcome benefits. In addition, the interaction between iron supplementation and SGLT2 inhibitors and its potential impact on prognosis remains to be clarified by future studies. This review represents a significant effort to explore the complex relationships involved, seeking to elucidate the intricate mechanisms by which SGLT2 inhibitors influence iron homeostasis.

COVID‐19 and ME/CFS present with some similar symptoms, especially physical and mental fatigue. In order to understand the basis of these similarities and the possibility of underlying common genetic components, we performed a systematic review of all published genetic association and cohort studies regarding COVID‐19 and ME/CFS and extracted the genes along with the genetic variants investigated. We then performed gene ontology and pathway analysis of those genes that gave significant results in the individual studies to yield functional annotations of the studied genes using protein analysis through evolutionary relationships (PANTHER) VERSION 17.0 software. Finally, we identified the common genetic components of these two conditions. Seventy‐one studies for COVID‐19 and 26 studies for ME/CFS were included in the systematic review in which the expression of 97 genes for COVID‐19 and 429 genes for ME/CFS were significantly affected. We found that ACE, HLA‐A, HLA‐C, HLA‐DQA1, HLA‐DRB1, and TYK2 are the common genes that gave significant results. The findings of the pathway analysis highlight the contribution of inflammation mediated by chemokine and cytokine signaling pathways, and the T cell activation and Toll receptor signaling pathways. Protein class analysis revealed the contribution of defense/immunity proteins, as well as protein‐modifying enzymes. Our results suggest that the pathogenesis of both syndromes could involve some immune dysfunction.