BackgroundDyslipidemia and hypertension are both important risk factors for atherosclerotic cardiovascular diseases. However, the relationship between dyslipidemia and incident hypertension remains to be elucidated comprehensively. The main purpose of this study was to construct the lipid risk score to explore the risk prediction effect of integrated lipid indices on new-onset hypertension.MethodsThis prospective cohort study with 2116 non-hypertensive subjects was conducted from 2009 to 2020. New hypertension events during the follow-up period were recorded and verified. The lipid risk score was calculated by summing coded total cholesterol, triglyceride, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol weighted with corresponding effect sizes. Cox regression analysis was used to estimate the association between the lipid risk score or lipid indices and incident hypertension in the subgroup of age (< 55 and≥ 55 years at baseline).ResultsAfter a median of 10.75-year follow-up, 637 incident hypertension cases were identified. The restricted cubic spline showed that the lipid risk score had a positive linear correlation with hypertension (P< 0.001). Among people< 55 years, with every increase of 0.94 in lipid risk score, the risk of hypertension increased by 37% (adjusted HR [95%CI]: 1.369 [1.164-1.610]). This association was not modified by overweight or obesity.ConclusionsThe integrated lipid risk score, independent of traditional risk factors, has a significantly predictive effect on hypertension in people younger than 55 years. This finding may aid in identifying high-risk individuals for hypertension, as well as facilitating early intervention and management to reduce adverse cardiovascular events. Comprehensive lipid management should be attached importance in the prevention and control of hypertension.

BackgroundDyslipidemia and hypertension are two important independent risk factors for ischemic stroke (IS); however, their combined effect on IS remains uncertain.ObjectivesThis present study aimed to evaluate the interaction effect of hypertension and abnormal lipid indices on IS in a 10-year prospective cohort in Chinese adults.MethodsThe cohort study of 4,128 participants was conducted in May 2009 and was followed up to July 2020. All qualified participants received a questionnaire survey, physical examination, and blood sample detection. Cox regression was used to evaluate the association of dyslipidemia and hypertension with IS, and calculate the hazard ratio (HR) and 95% confidence interval (CI). The relative excess risk of interaction (RERI) and the HR (95%CI) of interaction terms were used to examine additive and multiplicative interactions.ResultsIn the hypertensive population, Non-HDL-C ≥190 mg/dl, LDL-C/HDL-C ≥2 and HDL-C ≥60 mg/dl were statistically associated with IS, and after adjusting for covariates, HRs (95%CIs) were 1.565 (1.007–2.429), 1.414 (1.034–1.933) and 0.665 (0.450–0.983), respectively. While in the non-hypertension population, no significant association of Non-HDL-C ≥190 mg/dl, LDL-C/HDL-C ≥2, and HDL-C ≥60 was detected with IS (P > 0.05). There was a significant association between TC/HDL-C ≥ 3.6 and the decreased risk of IS in the non-hypertension population, and the HR (95%CI) was 0.479 (0.307–0.750). Whereas, a similar association was not observed in the hypertensive population. HDL-C ≥ 60 mg/dl, Non-HDL-C ≥ 190 mg/dl, TC/HDL-C ≥ 3.6, and TG/HDL-C ≥ 1 have additive and multiplicative interactions with hypertension (P < 0.05). The RERIs (95% CIs) of the additive interaction are −0.93 (−1.882–0.044), 1.394 (0.38–2.407), 0.752 (0.354–1.151) and 0.575 (0.086–1.065), respectively. The HRs (95% CIs) of the multiplicative interaction terms were 0.498 (0.272–0.911), 4.218 (1.230–14.464), 2.423 (1.437–4.086) and 1.701 (1.016–2.848), respectively.ConclusionHigh concentration of HDL-C reduces the impact of hypertension on IS, while the high concentration of Non-HDL-C, TC/HDL-C, and TG/HDL-C positively interact with hypertension affecting the incidence of IS. This study provides useful evidence for the combined effects of dyslipidemia and hypertension in predicting IS.

Background Dyslipidemia and inflammation are significant factors for the onset of cardiovascular diseases (CVD); however, studies regarding their interactions on the risk of CVD are scarce. This study aimed to assess the interaction of dyslipidemia and high-sensitivity C-reactive protein (hs-CRP) on CVD. Methods This prospective cohort enrolled 4,128 adults at baseline in 2009 and followed them up until May 2022 for collecting CVD events. Cox-proportional hazard regression analysis estimated the hazard ratios (HRs) and 95% confidence intervals (CIs) of the associations of increased hs-CRP (≥ 1 mg/L) and dyslipidemia with CVD. The additive interactions were explored using the relative excess risk of interaction (RERI) and the multiplicative interactions were assessed with HRs (95% CI) while the multiplicative interactions were assessed by the HRs (95% CI) of interaction terms. Results The HRs of the association between increased hs-CRP and CVD were 1.42 (95% CI: 1.14–1.79) and 1.17 (95% CI: 0.89–1.53) among subjects with normal lipid levels and subjects with dyslipidemia, respectively. Stratified analyses by hs-CRP levels showed that among participants with normal hs-CRP (< 1 mg/L), TC ≥ 240 mg/dL, LDL-C ≥ 160 mg/dL, non-HDL-C ≥ 190 mg/dL, ApoB < 0.7 g/L, and LDL/HDL-C ≥ 2.02 were associated with CVD [HRs (95%CIs): 1.75 (1.21–2.54), 2.16 (1.37–3.41), 1.95 (1.29–2.97), 1.37 (1.01–1.67), and 1.30 (1.00-1.69), all P < 0.05, respectively]. While in the population with increased hs-CRP, only ApoAI > 2.10 g/L had a significant association with CVD [HR (95% CI): 1.69 (1.14–2.51)]. Interaction analyses showed that increased hs-CRP had multiplicative and additive interactions with LDL-C ≥ 160 mg/dL and non-HDL-C ≥ 190 mg/dL on the risk of CVD [HRs (95%CIs): 0.309 (0.153–0.621), and 0.505 (0.295–0.866); RERIs (95%CIs): -1.704 (-3.430-0.021 and − 0.694 (-1.476-0.089), respectively, all P < 0.05]. Conclusion Overall our findings indicate negative interactions between abnormal blood lipid levels and hs-CRP on the risk of CVD. Further large-scale cohort studies with trajectories measurement of lipids and hs-CRP might verify our results as well explore the biological mechanism behind that interaction.

Haemorrhagic stroke (HS) is a devastating form of stroke with a high fatality rate. The lack of rapid lesion detection limits early diagnosis of HS. Several susceptibility genes of HS found in genome-wide association studies (GWAS) warrant transcriptional-level biomarkers for useful utility. 13 GWAS level loci with minor allele frequency ≥ 0.05 were selected out of 95 loci related to HS. After validation, the mRNA expression in peripheral leukocytes of 11 genes (PMF1, SLC25A44, CASZ1, NINJ2, WNK1, DYRK1A, LRCH1, LDLR, SMARCA4, AQP9, and LIPC) were measured in the HS case-control study (64 HS cases vs. 128 controls), and then verified in an ischemic stroke (IS) case-control study (67 IS cases vs. 61 controls). LIPC (P=0.002) and CASZ1 (P=0.040) were downregulated in HS patients, while SLC25A44 was upregulated (P=0.009). In the IS case-control study, the differential expression of LIPC (P=0.034) and SLC25A44 (P<0.001) was observed. Although CASZ1 expression was not different between IS cases and controls (P=0.419) with fold change (FC) of 1.205, the direction of expression was opposite to that in HS case-control study (FC=0.747). The ROCtrfgs of traditional risk factors and gene score which was estimated by combining LIPC, CASZ1, and SLC25A44 expression weights, improved the utility for HS identification by 14.1% compared with ROC (P=0.001). Expression of LIPC, CASZ1, and SLC25A44 could serve as potential biomarkers for identifying HS. CASZ1 might be a cause-specific indicator for differentiating HS from IS. Transcriptional score of these three genes could improve performance of the traditional risk model for HS identification.

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