As the extra-intestinal symptoms and associated disorders of IBD are getting more and more attention, we are also committed to explore the relationship between inflammatory bowel disease and diabetic nephropathy. Our study is the first to comprehensively analysis the causality between IBD (both UC and CD) and DN using GWAS data. Through MR analysis of the two samples, we discovered no support of a causal relationship between genetically calculated IBD and subtypes and the risk of diabetic nephropathy.
Renal damage in IBD patients can be classified as a secondary disease due to the coexistence of IBD, and nephrotoxicity induced by IBD therapeutic drugs[19]. The incidence of parenteral manifestations and other autoimmune-related diseases in patients with IBD seems to be significantly higher than that in the general population[20], such as type 1 diabetes mellitus, thyroid disorders and herpes-like dermatitis. Notably, compared to the remission period, patients with active inflammatory bowel disease have higher urinary albumin standard[21]. OIn histopathological examination of renal biopsy, IgA nephropathy, and tubulointerstitial nephritis are the most frequent findings in IBD patients[22]. However, there was no causal relationship between the IBD and IgA nephropathy at the genetic level[19]. Early identification and available treatment of gut related disorders may retard or even guard against the development of secondary complications and vascular injuries[23].
Recently, many IBD patients have reported kidney diseases, especially DN[11, 24, 25]. The pathological changes of intestinal microbial composition or metabolic state can increase the mucosal immune response and intestinal permeability, which further leads to insulin resistance and diabetes and its complications. The incompleteness caused by intestinal wall damage increases the irregular displacement of microorganisms and compounds with inflammatory and renal toxicity, which causes insulin resistance[26, 27]. Theoretical evidence has been indicated that rised levels of intestinal systemic bacterial endotoxins are closely related with the onset and development of DN. Zhang et al. discovered that DKD and IBD share many common related genes and pathogenic mechanisms, such as chronic inflammatory response, immune dysfunction and oxidative stress[28]. Gut microecological imbalance can excite the generation of various inflammatory factors via the LPS-CD14-TLR4 pathway, causing systemic or local chronic inflammation and thus insulin resistance[29]. In terms of the exacerbation of inflammatory state and gut microbial metabolic disorders, the progression of renal injury in DN is closely related to the gut-renal axis involving the local RAS. RAS activation is a key factor in the genesis of DN, and has long been central to the pathogenesis and progressive changes of DN[30]. It has been reported that fermentation of gut microbiota produces short-chain fatty acids (SCFAs), which could bind to receptors located in the kidney and exert vascular-related effects. This phenomenon is likely disrupts the balance between the angiotensin-converting enzyme inhibitor (ACE) and ACE2 axes of the RAS, which triggers a cascade of reactions that increase renal damage and promote the progression of DN[30]. Thus, early identification and available treatment of gut-related diseases can delay or even prevent the development of secondary complications, renal and vascular damage.
As currently reported, our study is the first to assess the causal association between IBD (including UC and CD) and DN based on MR analysis of two samples from large-scale GWAS data. MR is a causal inference from a genetic basis, which draws on an individual's genetic markers to reflect possible causality between the relevant risk factors and disease risk. Genetic variants strongly associated with risk factors are usually obtained as instrumental variables from GWAS, and then their causal relationship with disease risk is inferred. This method compensates for the shortcomings of traditional observational epidemiological researches and greatly reduces the effect of confounding factors on the outcomes.
Although MR has a wide application prospect in medical research, MR also has certain limitations: On the one hand, the difficulty in obtaining suitable genetic variants. Although a large number of genetic loci related to complex traits have been identified, there are still some interesting risk factors for which it is difficult to obtain genetic variants due to the lack of GWAS studies or publicly available data resources. Even when genetic variants are available, causation may not be effectively inferred because three key assumptions are not met. On the other hand, complex diseases or traits are usually associated with a large number of genetic loci, while GWAS studies report only a small fraction of the most significant genetic variance, which affecting causal inference in MR studies. Furthermore, the biological mechanisms underlying most of the genetic variants are unknown, which makes it difficult to interpret potential mechanisms of action in causal associations. Therefore, a larger sample size and more sophisticated methods are required to confirm the outcomes and take statistical capabilities into account.