AGE-RELATED PATTERNS OF KIDNEY PARENCHIMAL VOLUME IN T1D, T2D AND DIFFERENT TREATMENT GROUPS OF T2D: A CROSS-SECTIONAL STUDY OF 35,703 UK BIOBANK PARTICIPANTS

NEPHROLOGY DIALYSIS TRANSPLANTATION(2021)

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摘要
Abstract Background and Aims Kidney parenchymal volume (KPV) presents a natural variation with respect to sex, age, and body size, and is also affected by diseases such as diabetes. The UK Biobank (UKBB) is a large-scale study including clinical and MRI data. The current project investigated the association between KPV and age in UKBB participants without diabetes and with diabetes type 1 (T1D), and type 2 (T2D). In addition, the effect of different treatments for T2D on KPV was investigated. Method KPV was estimated in 35,703 UKBB participants (52% women, age = 45-82 years) with a deep-learning-based segmentation of both kidneys (Dice = 0.956, error < 4%). The cohort was classified into Control, T1D and T2D subjects using an algorithm developed on UKBB clinical data (Eastwood et al 2016). Individuals with T2D were further divided into groups related to treatment: Lifestyle (no pharmaceuticals, i.e. light treatment, mean disease duration of 6.2 years), Metformin (metformin as the only pharmaceutical, i.e. intermediate treatment, mean disease duration of 8.3 years), and Other (more potent treatment, combination of pharmaceuticals, mean disease duration of 14.1 years). KPV was studied as a function of age in the different groups, divided according to sex. The statistical difference in mean KPV between groups was tested. For each group, the association between KPV and age was assessed by linear regression. Comparison of line slopes was conducted to investigate whether age-related patterns in KPV differed statistically between groups. Results The moving average curve of KPV vs age, in controls and subjects with T1D and T2D, is shown in Fig 1A (with a 15-year sliding window). The corresponding curve for different T2D treatment groups is depicted in Fig 1B. Fig 2A-D presents results for the comparison of KPV and regression line slope between the subject groups. According to Fig 1A and 2A, KPV is usually higher in subjects with T1D and T2D than in controls. As shown in Fig 1B and 2B, T2D subjects with longer disease duration and on pharmaceutical treatment (Metformin or Other) are generally more prone to large KPV than subjects with adapted lifestyle as treatment. The decreasing KPV pattern with age is faster in T2D subjects than controls but not significantly different between T1D subjects and controls (Fig 1A and 2C). Women in group Other also show a pattern of steeper age-related decline in KPV compared to remaining women with T2D treatment (Fig 1B and 2D). Conclusion Compared to controls, T1D subjects show enlarged KPV similar to that of T2D subjects, which is in line with previous literature. Subjects with T2D show a pattern of steeper age-related decline in KPV compared to controls. Female T2D subjects with longer disease duration, usually on a more potent treatment (beyond adaption of lifestyle and metformin as the only pharmaceutical), are more prone to enlarged KPV and exhibit a pattern of steeper age-related decline in KPV. This may be due to hyperfiltration caused by diabetes, resulting in increased kidney size. The normal loss of glomeruli with age could be accelerated by diabetes, leading to a greater loss in KPV per year in diabetics. Steeper KPV decline patterns in disease could also be caused by selection bias where old subjects with large KPV and related complications are less likely to participate in the study.
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