The mixed model showed that those who had DM had a significantly lower GFR at the time of death (p<0.03) compared with Non-DM that had a higher GFR. This suggests that death in the DM group may be due to the complications of DM, including DN. From the deaths recorded the majority of those with DM died from sepsis, cancer and MI and those with Non-DM died from sepsis and cancer.
3.11.1.1 GFR Outcome
GFR was seen to be lower in the DM compared with Non-DM. A significant interaction was seen in the GFR of those on immunosuppression who were male compared to females (p=0.03). Immunosuppressed males had a higher GFR compared with females in this group
113 (69ml/min/1.73msq versus 46ml/min/1.73msq, respectively), suggesting there is an added benefit on GFR if male and on immunosuppression. This effect was not seen in those without immunosuppression i.e. the DM group. The GFRs in the non-immunosuppressed group that were predominantly DM were males 32ml/min/1.73msq and females 39ml/min/1.73msq.
3.11.1.2 ACR Outcome
No significant differences were seen with baseline cytokines on ACR over time in either group. 3.11.1.3 UPCR Outcome
Baseline cytokines did not predict an effect on UPCR over time in either group. 3.11.2 Predictors
3.11.2.0 Baseline Plasma MIF
The effect of baseline plasma MIF on GFR changed over time in the DM group whilst no effect was seen in the Non-DM. Baseline plasma MIF predicted a lower GFR in DM at >18 months (p=0.03), that stopped at >3 years. Fig 3.11.2.0 illustrates the change in baseline plasma MIF in DM and Non- DM over time.
114
Figure 3.11.2.0 Predictive effect of baseline plasma MIF over time. Key: DM=1 Non-DM=0, Time 1= 18 months, Time 2= >3 years, LogBPlasmahMIF = baseline plasma MIF using logarithmic scale.
3.11.2.1 Baseline Plasma CCL18
The effect of baseline plasma CCL18 on GFR changed over time in the DM group whilst no effect was seen in the Non-DM. Baseline plasma CCL18 predicted a lower GFR in DM at >18 months (p=0.03), that stopped at >3 years (p=0.07). Figure 3.11.2.1 suggests that with an increased sample size the predictive significant effect on GFR may continue in DM at a longer time point. Further larger studies would be needed to confirm these findings. This was different from the effect seen in plasma CCL18 on GFR in univariant analysis. The model accounts for other variables and hence likely to have resulted in the difference arising between the results.
115
Figure 3.11.2.1 Predictive effect of baseline plasma CCL18 over time. Key: DM=1 Non-DM=0, Time 1= 18 months, Time 2= >3 years, BPlasma CCL18 = baseline plasma CCL18.
Summary
The predictive model shows mortality is higher in DM with low GFR. Immunosuppression preserves GFR in males and in turn this may contribute to the difference seen in cytokines. Specifically in this model, baseline plasma CCL18 and baseline plasma LogMIF were predictive of a lower GFR in DM at more than 18 months. The significance declines with time; however, the analysis suggests that baseline plasma CCL18 may continue to have its predictive effect at >3 years. Larger numbers specifically looking at this factor could help clarify this; however, it is known that DM have a higher morbidity and thus the study would need to be adequately powered. Baseline cytokines are not predictive of ACR or UPCR outcomes though the analysis is limited by the small number analysed over the follow up period.
116 3.12 Clinical correlation of serum and plasma cytokines
Literature exists that suggest the collection of cytokines is affected by the coagulation cascade and hence collecting serum samples may be more reflective of circulating cytokines compared with collection of plasma samples (Johnson, Aarden et al. 1996). My predecessor had collected plasma samples and stored these. I subsequently collected plasma samples in the prospective cohort to allow comparisons to be made. To ensure the circulating cytokines did not alter with the EDTA tubes, I simultaneously collected serum samples. Serum tubes are normally used to measure renal function thus if cytokine levels could be measured in the same sample collected by the patient to assess their renal function, this would be more practical. Spearman’s correlation was used to establish whether there are differences between the serum and plasma levels of an individual and whether these alter with cytokine analysed. The results are presented below and summarised in Table 3.16.
Serum and plasma MIF levels correlate significantly in both Non- DM and DM patients, with DM having a higher level of significance, see Figure 3.12.1. The serum levels detected were lower than cytokine in plasma samples.
Figure 3.12.1 MIF Serum and plasma levels
Serum levels of MCP-1 were higher than those detected in plasma samples see Figure 3.12.2. Both were correlated significantly with the correlation being highly significant in the DM group.
Serum and Plasma MIF levels in Non DM and DM
0 25000 50000 75000 100000 0 5000 10000 15000 Spearman's r=0.42 p<0.01** Spearman's r=0.61 p<0.0001**** Non DM DM Plasma MIF (pg/ml) S e ru m M IF (p g /m l)
Serum and Plasma MCP-1 levels in Non DM and DM
0 50 100 150 200 0 100 200 300 400 500 600 Spearman's r=0.44 p<0.001*** Spearman's r=0.64 p<0.0001**** Non DM DM Plasma MCP-1 (pg/ml) S e ru m M C P -1 (p g /m l)
117 Serum and plasma CCL18 levels were detected in similar quantities and correlated significantly in both Non-DM and DM, see Figure 3.12.3.
Figure 3.12.3 CCL18 serum and plasma levels
Table 3.15 Comparisons of plasma and serum cytokines at >3 years. Key: P prefix = plasma, S prefix = serum
Comparisons at >3 years plasma and
serum cytokines
DM Non-DM
Spearman’s r p value Spearman’s r p value PMIF vs SMIF 0.61 p<0.0001 0.42 p<0.05 PMCP-1 vs SMCP-1 0.64 p<0.0001 0.44 p<0.001 PCCL18 vs SCCL18 0.65 p<0.0001 0.74 p<0.0001
Summary
Serum and plasma levels correlate significantly in all cytokines in both DM and Non-DM groups. There is a higher level of significance with serum and plasma CCL18 in both groups. MIF and MCP-1 serum and plasma levels are slightly less significant in Non-DM patients. Serum levels of MIF were lower than plasma levels.