Aims: Haptoglobin (HP) 2-2 phenotype has been suggested as a risk factor for cardiovascular disease (CVD) and to modulate fenofibrate benefit on CVD risk in Type 2 diabetes. However, little is known as to whether HP levels modulate CVD risk and fenofibrate response. Methods and results: Haptoglobin phenotype and levels were determined in 8047 Fenofibrate Intervention and Event Lowering in Diabetes trial participants at baseline and randomization (after a 16 week run-in period, including a 6 week fenofibrate therapy) and their association with new on-trial total CVD events over 5 years was assessed. Higher baseline HP levels were associated with total CVD events in the placebo group {n = 4030, hazard ratio [95% confidence interval (CI)] = 1.30 [1.02–1.66] for HP level Tertile 3 vs. Tertile 1, P = 0.035}. This was driven by participants with HP 1-1 phenotype (P for interaction = 0.011). Participants with the lowest baseline HP level tertile and HP 1-1 phenotype tended to have the lowest CVD risk, whereas CVD risk was similar in other participants, regardless of HP phenotype and levels. Fenofibrate benefit on total CVD events did not differ significantly by HP phenotypes, baseline HP level tertiles, or tertiles of change in HP levels by fenofibrate during active run-in. Conclusion: Higher baseline HP levels were associated with a higher CVD risk, especially in participants with HP 1-1 phenotype. A lower CVD risk is found only in Type 2 diabetes participants with both the HP 1-1 phenotype and low baseline HP levels. Fenofibrate benefits on CVD risk reduction did not differ by HP levels or phenotype. Lay summary: We evaluated the relationship of different forms or phenotypes of the blood protein, haptoglobin, and its circulating levels with the risk of developing CVD and fenofibrate benefit in patients with Type 2 diabetes, and showed that both HP phenotype and levels are important to assess CVD risk in patients with Type 2 diabetes, although fenofibrate did not modulate CVD risk via HP phenotype or level.Higher baseline HP levels were associated with higher CVD risk, especially in participants with HP 1-1 phenotype.Fenofibrate benefit on CVD did not differ by HP phenotype and baseline or change in HP levels.

Aims: The aim of the study is to integrate targeted transcriptomic analyses of previously identified biomarker proteins (proteomic findings) to better understand vascular complications (Cx) in Type 2 diabetes (T2D). Methods: Total RNA was extracted from baseline citrate plasma samples of 543 individuals with T2D from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial. Among these, 224 participants had microvascular Cx, 142 had macrovascular Cx (51 had both types of Cx) and 228 had no Cx (control group). mRNA expression was quantified using the OpenArray platform and group differences were analysed using ΔΔ ct values. Neutrophil elastase (NE) protein levels were measured in baseline plasma by ELISA. Results: Eleven genes were retained for focused analysis. For microCx, the largest gene expression differences were observed for clusterin (~2‐fold upregulation) and integrin alpha‐IIb (~50% downregulation), compared with the control group. For macroCx, clusterin exhibited the strongest upregulation (~2.5‐fold), whereas apolipoprotein F showed the greatest downregulation (~20%). Comparative analysis of proteomic and transcriptomic data across study groups revealed that only 32% of gene expression differences were mirrored at the protein level. NE levels were highest in the microCx group and were significantly elevated versus control only in that group; NE levels also correlated inversely with circulating actin protein expression ( R ² = 0.92). Conclusion: Combining proteomic and targeted plasma transcriptomic data provides exploratory insights into biological processes associated with vascular complications in T2D and highlights NE as a candidate component of a proteolytic pathway for further investigation.

Familial Hypercholesterolaemia (FH) is characterised by high cholesterol and premature cardiovascular disease. While hypercholesterolaemia and inflammation are both key drivers in the formation of atherosclerotic plaques, inflammation remains understudied in FH. Inflammatory (M1) macrophages contribute to plaque destabilisation and macrophage precursors, monocytes, can be skewed towards an inflammatory state. Aims: Determine; whether monocytes of FH individuals are inflammatory, if they readily form inflammatory macrophages, and whether this remains so in statin-treated individuals. Blood samples were collected from people with FH (statin-treated and untreated) and healthy controls. Lipid profile was obtained and monocyte inflammatory marker expression was determined by whole blood flow cytometry. Monocytes were cultured with autologous serum and resultant macrophage profile determined by flow cytometry. Total cholesterol and low-density lipoprotein cholesterol (LDL-C) were higher in the Untreated-FH group compared to the Treated-FH group and controls. In both Treated-FH and Untreated-FH groups, monocytes were inflammatory with high CD86 (M1). The ratio of inflammatory/anti-inflammatory markers (CD86/CD163) significantly correlated with LDL-C and ApoB/ApoA1 ratio across the cohort, indicating the high LDL-C of FH may promote an inflammatory monocyte profile. Monocyte-derived-macrophages from (Treated) FH individuals also had a more inflammatory profile (CD86 and CD86/CD163). Overall, monocytes show inflammatory skewing in FH individuals, even those with moderately-reduced cholesterol levels. These monocytes readily become inflammatory macrophages. This, along with subsequent inflammatory macrophage formation, could contribute to plaque destabilisation and downstream clinical events. This supports inflammatory monocyte targeting as a potential approach to reduce residual risk in FH individuals.

Background: Reliable qPCR analysis depends on stable endogenous controls, particularly in high-throughput pre-amplification workflows where technical bias may arise. The suitability of highly abundant 18 S rRNA as a reference gene in multiplex OpenArray ^® platforms remains debated. This study evaluated the stability of 18 S rRNA, its impact on co-amplified targets, and comparability between archived and newly manufactured primer pools. Methods: Plasma RNA from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial was analysed using TaqMan OpenArray ^® following reverse transcription and pre-amplification. Paired samples ( n = 23) were pre-amplified with primer pools with and without 18 S rRNA and compared across four target genes. Stability of 18 S rRNA was assessed in 789 samples across 17 runs. Agreement between archived and new primer pools was evaluated in 774 paired samples using Wilcoxon signed-rank and Bland–Altman analyses. Results: 18 S rRNA showed stable detection (median Ct 14.5, IQR 13.4–16.3) with low inter-run variability (CV 3.9%). Inclusion of 18 S rRNA during pre-amplification did not significantly alter Ct values of co-amplified targets (median differences 0.07–0.52 cycles; p > 0.05), with minimal overall bias (-0.18 Ct). Archived and newly manufactured primer pools showed a small but significant Ct shift, with lower values in the new pool (bias 0.53 Ct; p < 0.0001), although variability between paired measurements was wide. Conclusion: 18 S rRNA is a stable technical control in plasma OpenArray ^® workflows and did not measurably bias co-amplified targets during pre-amplification. Archived and new primer pools showed only minor systematic differences and remained broadly comparable at the group level.