Sex Differences in Fecal Microbiota Correlation With Physiological and Biochemical Indices Associated With End-Stage Renal Disease Caused by Immunoglobulin a Nephropathy or Diabetes.

Peng Zhang,Lu Xu,Xingqiang Lai,Weiting Zhang,Jiao Wan,Yunyi Xiong,Luhao Liu,Rongxin Chen,Junjie Ma,Li Li,Lei Zhang,Jiali Fang,Tao Zhang,Zheng Chen,Guanghui Li,Hailin Xu

doi:10.3389/fmicb.2021.752393

Abstract

This study investigated the sex-specific differences in the correlation between intestinal microbiota and end-stage renal disease. Here, we compared the differences in the gut microbiota of male and female healthy controls (HC) and patients with end-stage renal disease (ESRD) caused by immunoglobulin A (IgA) nephropathy (ESRD-IgAN) or type-2 diabetes mellitus (ESRD-T2DM) using high-throughput sequencing of the 16S rRNA gene. We also analyzed the correlation between gut microbiota and clinical immune indicators. We assigned 8, 10, 5, 7, 11, and 20 volunteers to female HC, ESRD-IgAN, and ESRD-T2DM, and male HC, ESRD-IgAN, and ESRD-T2DM, respectively. The results showed sex-specific differences in both physiological and biochemical indices and intestinal microbiota composition, as well as the correlation between them. The correlations between physiological and biochemical indices in men were significantly lower than those in women, especially for indices related to immunity, blood glucose, and cardiac color sonography. Urine output, lymphocyte ratio, serum albumin, blood calcium, dialysis status, serum urea nitrogen, urine protein, and diabetes significantly correlated with male fecal microbiota composition, whereas only creatinine and 2-h post-prandial blood glucose significantly correlated with female fecal microbiota composition. The top 50 dominant operational taxonomic units showed a stronger correlation with physiological and biochemical indices in samples obtained from females than from males. These differences highlight sex-specific differences in the effectiveness of ESRD prevention and treatments via regulating intestinal microbiota.

Highlights

Chronic kidney disease (CKD) is a global public health problem that affects 10–16% of the adult population worldwide (Meguid El Nahas and Bello, 2005; Barsoum, 2006; Hallan et al, 2006; Coresh et al, 2007; Wen et al, 2008; Stevens et al, 2010; GBD Chronic Kidney Disease Collaboration, 2020)
The results showed that urine output (UO), lymphocyte ratio (LR), serum albumin, blood calcium (BCa), dialysis, urea nitrogen (UN), urine protein (UP), and diabetes were significantly correlated with the male fecal microbiota composition (Figure 4A), whereas only creatinine and Two-h post-prandial blood glucose (TPBG) were significantly correlated with the female fecal microbiota composition (Figure 4C)
Gut inflammation is an important factor in CKD and renal failure, and dysbiosis of the gut microbiota is the main factor leading to intestinal inflammation (Huang et al, 2017)

Summary

Introduction

Chronic kidney disease (CKD) is a global public health problem that affects 10–16% of the adult population worldwide (Meguid El Nahas and Bello, 2005; Barsoum, 2006; Hallan et al, 2006; Coresh et al, 2007; Wen et al, 2008; Stevens et al, 2010; GBD Chronic Kidney Disease Collaboration, 2020). The gut microbiota maintains a symbiotic relationship with the host under normal conditions, and it has recently been associated with several diseases, such as inflammatory bowel disease (Caruso et al, 2020), diabetes (Patterson et al, 2016), colorectal cancer (Arthur et al, 2012), and liver cancer (Hartmann and Kronenberg, 2018; Ma et al, 2018). Dysbiosis of gut microbiota contributes to systemic inflammation and accumulation of uremic toxins, which significantly influence the pathophysiology of atherosclerosis and other complications associated with CKD (Guldris et al, 2017). Colon-derived solutes that are normally excreted in the urine accumulate in the plasma when the kidneys fail and may contribute to uremic toxicity (Meyer and Hostetter, 2012). ESRD can significantly modify the composition of the gut microbiota in humans (Vaziri et al, 2013)

Methods

Results

Conclusion