Abstract
This study is to determine symptomatic intracranial atherosclerotic stenosis (ICAS), a significant stroke cause with high recurrence risks, by examining the relationship between lipoprotein(a) and ischemic stroke recurrence. Analyzing data from the RICA trial (chronic remote ischemic conditioning in patients with symptomatic ICAS) involving 1286 patients aged 40–80 years across 84 Chinese stroke centers, we found that participants with lipoprotein(a) levels above 17.4 mg/dL experienced markedly higher stroke recurrence rates (adjusted hazard ratio [HR], 1.38; 95 % CI, 1.05–1.80; P = 0.02), with each doubling of lipoprotein(a) increasing recurrent stroke risk by 18 % (adjusted HR, 1.18; 95 % CI, 1.09–1.29; P < 0.001). Notably, among high lipoprotein(a) participants, the remote ischemic conditioning group demonstrated a lower stroke incidence (16.7 %) compared to the control group (22.6 %), suggesting potential therapeutic benefits (adjusted HR, 0.67; 95 % CI, 0.47–0.96; P = 0.03). The study revealed that elevated lipoprotein(a) levels are independently correlated with increased recurrent ischemic stroke risk in patients with symptomatic ICAS, and those with higher lipoprotein(a) levels might derive more clinical advantages from remote ischemic conditioning. Additional research is required to validate these results.
Keywords: Lipoprotein(a), Remote ischemic conditioning, Stroke, Symptomatic intracranial atherosclerotic stenosis
Introduction
Stroke is the main contributing factor of both mortality and disability worldwide [1]. In recent decades, the discovery of stroke risk factors and emergence of novel therapies have led to advancements in primary and secondary stroke prevention. Nevertheless, some types of stroke still have a high risk of recurrence despite optimal management [2]. For instance, intracranial atherosclerotic stenosis (ICAS), a primary cause of ischemic stroke, is linked to a significant risk of recurrent stroke [3,4], leading to >10 % annual risk of stroke recurrence even with optimal medical treatment and risk factor management [5,6]. Several randomized trials have indicated that endovascular therapy does not yield a statistically significant advantage over medical treatment alone [7,8]. Therefore, new targets for intervention are urgently required to decrease the risk of stroke recurrence in patients with symptomatic ICAS.
Limb remote ischemic conditioning (RIC) is an innovative neuroprotective strategy that employs brief, repetitive cycles of sublethal ischemia-reperfusion in peripheral limbs to activate systemic endogenous protective mechanisms. By inducing transient ischemia through controlled cuff inflation (typically 200 mmHg for 5 min followed by 5-min reperfusion), this intervention establishes cross-organ tolerance capable of mitigating ischemic injury in critical remote tissues such as the brain [9]. Emerging clinical evidence positions RIC as a promising therapeutic approach for ICAS, demonstrating potential in reducing stroke recurrence rates [10,11]. However, critical gaps persist in clinical translation—particularly the absence of validated biomarkers to predict therapeutic responsiveness and stratify patient populations with differential treatment outcomes.
Lipoprotein(a) is a low-density lipoprotein-like particle that is covalently bound to apolipoprotein B100 by disulfide bonds [12]. Unlike other lipid components, plasma lipoprotein(a) levels show minimal fluctuation throughout life in the absence of specific conditions. Various research approaches, including epidemiological, genome-wide association, and Mendelian randomization studies, have provided evidence supporting a causality between lipoprotein(a) and cardiovascular disease and other atherosclerotic diseases [[13], [14], [15]]. Notably, the pro-inflammatory, pro-thrombotic, and pro-atherosclerotic characteristics of lipoprotein(a) suggest its involvement in the pathophysiology of ICAS [16]. In addition, lipoprotein(a) levels vary by race and are higher in individuals with African ancestry [17], which is consistent with the high prevalence of ICAS in African populations [5]. Thus far, there has been limited research exploring the correlation between lipoprotein(a) levels and the risk of recurrent ICAS-related stroke. Understanding this relationship is important for investigating novel therapeutic strategies for ICAS-related stroke, particularly because lipoprotein(a)-lowering drugs are likely to become clinically available in the near future [18].
Hence, in this post hoc analysis of data from the RICA (chronic remote ischemic conditioning in patients with symptomatic ICAS) trial, we aimed to determine whether lipoprotein(a) levels could predict recurrent ischemic stroke in patients with symptomatic ICAS and explore whether the efficacy of remote ischemic conditioning was influenced by lipoprotein(a) levels.
Material and methods
Study population
Detailed information on the design and results of the RICA trial has been published previously [6]. Briefly, the clinical trial included 3033 participants aged 40–80 years who had experienced either an ischemic stroke within 30 days or a transient ischemic attack within 15 days of study randomization. The ischemic events of all patients were attributable to the 50–99 % stenosis of a crucial intracranial artery (middle cerebral, carotid, vertebral, or basilar), verified by computed tomography or magnetic resonance angiography.
Participants were enrolled at 84 stroke centers in China and randomly assigned in a 1:1 ratio to two groups. One group received remote ischemic conditioning, whereas the other underwent a sham procedure. In the RICA trial, we utilized the Xuanyitong® device (China), a commercially available automated apparatus equipped with two cuffs designed for the concurrent compression of both upper arms (eFig. 1). The device operates through a series of automated cycles, each consisting of a 5-min inflation period followed by a 5-min deflation period, totaling 5 cycles per treatment session. For participants in the remote ischemic conditioning group, the compression pressure was set at 200 mmHg, whereas in the sham remote ischemic conditioning group, it was set at 60 mmHg. Both interventions were administered once daily for a year, and the participants were able to voluntarily continue the treatment after one year. The trial was performed between October 2015 and February 2019 with a median follow-up of 3.3 years, and 2921 (96.2 %) participants completed the follow-up. Each site's ethical committee approved the trial, and all participants submitted written informed consent through their authorized representatives or themselves.
Lipoprotein measurements
As lipoprotein(a) measurement was not a predetermined test for the RICA trial, the decision to perform the test was at the discretion of the investigators at each participating center, in accordance with local practice. In the RICA trial, lipoprotein(a) measurements were performed in 1826 participants (60.2 %). Of them, 1510 (82.7 %) had results expressed in milligrams per deciliter (mg/dL), whereas the remaining participants had results indicated in nanomoles per liter (nmol/L).
To minimize bias, this study only included participants with lipoprotein(a) levels tested via a facility accredited by the China National Accreditation Service for Conformity Assessment for ISO 15189 quality and competence in medical laboratories. Because of the absence of a fixed conversion factor between mg/dL and nmol/L, we only included participants with lipoprotein(a) results reported as mg/dL. Lipoprotein(a) levels were determined using commercially available assay kits in accordance with the manufacturer's instructions. The limit of detection was 1–2 mg/dL, and the inter-assay coefficient of variation was 2.8–4.9 %, depending on the lipoprotein(a) level and the laboratory performing the test. If participants had multiple lipoprotein(a) results at baseline or during follow-up, the mean of these results was calculated.
Subgroup analysis of the effect of remote ischemic conditioning on Lipoprotein(a) levels
To analyze the potential effect of remote ischemic conditioning on lipoprotein(a) levels, a subset of participants from the remote ischemic conditioning group of the RICA trial was selected based on the following criteria: two measurements of lipoprotein(a) before (at baseline) and after remote ischemic conditioning treatment at least 3 months apart; performing remote ischemic conditioning regularly, defined as at least 50 % compliance with the intervention which was monitored using a device that automatically uploaded data to a central database (eFig. 1); and the regimen of lipid-lowering medications was stable between the two lipoprotein(a) tests.
Clinical outcomes
In this analysis, the main outcome was fatal and nonfatal ischemic stroke, which was also the primary efficacy endpoint of the RICA trial. Ischemic stroke was defined as a sudden onset of a new focal neurological impairment lasting more than 24 h, worsening of an existing focal neurological deficit lasting more than 24 h, or focal neurological deficit lasting less than 24 h, which pertains to neuroimaging-based evidence of fresh ischemia alterations. Focal neurological deficits with a non-ischemic etiology were excluded. Death within 28 days after a confirmed ischemic stroke without another definitive cause was considered a fatal ischemic stroke. A committee not informed of the participants' baseline characteristics or treatment assignment adjudicated all outcomes. A neutral data monitoring commission oversaw the study data.
Statistical analyses
Proportions are used to summarize baseline characteristics for categorical variables, whereas mean and standard deviation (SD) or median and interquartile range (IQR) are used for continuous variables. The normality of the data distribution was evaluated using the Kolmogorov–Smirnov test. The groups were compared using independent samples t tests or Mann–Whitney U-tests for continuous variables, according to the distribution. Pearson's chi-squared test or Fisher's exact test were used for categorical variables. The empirical cumulative distribution function was used to create the graph on lipoprotein(a) distribution. The correlation between lipoprotein (a) and low-density lipoprotein (LDL) levels was estimated using Spearman's correlation coefficient (ρ).
For most analyses, the participants were divided into a higher lipoprotein(a) group (lipoprotein(a) level higher than the median value) and lower lipoprotein(a) group (lipoprotein(a) level lower than or similar to the median value). The associations between lipoprotein(a) level and the clinical outcome was evaluated using the Kaplan–Meier method and Cox regression, with the lipoprotein(a) category as an independent variable. Additionally, lipoprotein(a) level was evaluated as a continuous variable, with the hazard ratio (HR) determined per doubling of lipoprotein(a) level. Multivariable models were adjusted for LDL, total cholesterol, and serum glucose levels in Model 1; variables in Model 1 plus demographic variables (age, sex, hypertension, diabetes, smoking condition, and body mass index) in Model 2; and variables in Model 2 plus imaging data (site and degree of arterial stenosis) in Model 3. A sensitivity analysis was performed, excluding participants without baseline lipoprotein (a) measurements. If a participant had multiple results at baseline and during follow-up, only the baseline value was used in the sensitivity analysis. The HR of the impact of remote ischemic conditioning or sham remote ischemic conditioning on the risk of recurrent ischemic stroke was adjusted for variables in Model 3.
To examine whether the impact of remote ischemic conditioning was modified by the lipoprotein(a) category, we categorized the participants into two groups based on whether their lipoprotein(a) level was above or similar to/below the median value for the whole participant cohort. Differences in lipoprotein(a) levels before and after remote ischemic conditioning were tested using the Wilcoxon signed-rank test. Statistical significance was set as a two-tailed P value < 0.05. All analyses were accomplished using R version 4.6 (The R Foundation for Statistical Computing, Vienna, Austria).
Results
Baseline characteristics
The study enrolled 1286 eligible participants (mean age, 60.7 years, 34.9 % women) (eFig. 2 in Supplement). Lipoprotein(a) exhibited a highly asymmetrical distribution pattern (median, 17.4 mg/dL; IQR, 7.1–46.1 mg/dL). The baseline characteristics of participants overall and stratified by whether their lipoprotein(a) level was at/below or above the median (17.4 mg/dL) are shown in Table 1. Of the total participants, 83.0 % had hypertension, and 34.4 % had diabetes. The qualifying artery had 50–69 % stenosis in 60.2 % of participants and 70–99 % stenosis in 39.8 %. The average LDL level was 114.7 mg/dL (SD, 31.3). The lipoprotein(a) and LDL levels were not significantly correlated (ρ = −0.35; 95 % CI, −0.089 to 0.02; P = 0.20; eFig. 3 in Supplement). Factors associated with a higher lipoprotein(a) level (>17.4 mg/dL) included female sex, ≥70 % stenosis of the qualifying artery, history of ischemic stroke or myocardial infarction, and higher total cholesterol level (Table 1).
Table 1.
Baseline characteristics of study population, according to median lipoprotein(a).
| Characteristics | All (n = 1286) |
Lipoprotein(a) ≤ 17.4 mg/dL (n = 643) |
Lipoprotein(a) > 17.4 mg/dL (n = 643) |
p Value |
|---|---|---|---|---|
| Age, mean (SD), y | 60.7 (9.0) | 60.6 (8.7) | 60.9 (9.3) | 0.52 |
| Sex, no. (%) | 0.03 | |||
| Female | 449/1286 (34.9) | 206/643 (32.0) | 243/643 (37.8) | |
| Male | 837/1286 (65.1) | 437/643 (68.0) | 400/643 (62.2) | |
| BMI, mean (SD), kg/m2 | 25.0 (3.1) | 25.1 (3.1) | 25.0 (3.1) | 0.60 |
| Qualifying event, no. (%) | 0.11 | |||
| Transient ischemic stroke | 228/1286 (17.1) | 125/643 (19.4) | 103/643 (16.0) | |
| Ischemic stroke | 1058/1286 (82.3) | 518/643 (80.6) | 540/643 (84.0) | |
| Previous ischemic stroke, no. (%) | 305/1286 (23.7) | 133/643 (20.7) | 172/643 (26.7) | 0.011 |
| Previous transient ischemic stroke, no. (%) | 133/1286 (10.3) | 68/643 (10.6) | 65/643 (10.1) | 0.78 |
| Previous myocardial infarction, no. (%) | 106/1286 (8.2) | 40/643 (6.2) | 66/643 (10.3) | 0.008 |
| Hypertension, no. (%) | 1067/1286 (83.0) | 528/643 (82.1) | 539/643 (83.8) | 0.41 |
| Diabetes mellitus, no. (%) | 443/1286 (34.4) | 229/643 (35.6) | 214/643 (33.3) | 0.38 |
| Smoking, no. (%) | 814/1286 (63.3) | 422/643 (65.6) | 392/643 (61.0) | 0.083 |
| Symptomatic qualifying artery, no. (%) | 0.56 | |||
| Internal carotid | 186/1286 (14.5) | 87/643 (13.5) | 99/643 (15.4) | |
| Middle cerebral | 670/1286 (52.1) | 331/643 (51.5) | 339/643 (52.7) | |
| Vertebral | 198/1286 (15.4) | 98/643 (15.2) | 100/643 (15.6) | |
| Basilar | 167/1286 (13.0) | 92/643 (14.3) | 75/643 (11.7) | |
| Multiple arteries | 65/1286 (5.1) | 35/643 (5.4) | 30/643 (4.7) | |
| Percent stenosis of affected artery, no. (%) | 0.012 | |||
| 50–69 % | 774/1286 (60.2) | 409/643 (63.6) | 365/643 (56.8) | |
| 70–99 % | 512/1286 (39.8) | 234/643 (36.4) | 278/643 (43.2) | |
| Biochemical measures | ||||
| lipoprotein(a), median (IQR), mg/dl | 17.4 (7.1–46.1) | 7.1 (4.1–11.0) | 46.1 (30.0–68.1) | <0.001 |
| LDL cholesterol, mean (SD), mg/dl | 114.7 (31.7) | 113.1 (31.6) | 116.3 (31.7) | 0.066 |
| HDL cholesterol, mean (SD), mg/dl | 43.3 (10.6) | 42.9 (10.4) | 43.6 (10.9) | 0.25 |
| Total cholesterol, mean (SD), mg/dl | 185.3 (37.0) | 183.3 (37.3) | 187.4 (36.6) | 0.048 |
| Serum glucose, mean (SD), mmol/l | 6.8 (2.8) | 7.0 (3.0) | 6.7 (2.6) | 0.11 |
SD, standard deviation; BMI, body mass index; IQR, interquartile range; LDL, low-density lipoprotein; HDL, high-density lipoprotein.
Risk of recurrent ischemic stroke according to Lipoprotein(a) level
During an average follow-up duration of 3.3 years (IQR, 2.6–4.4 years), 221 participants (17.2 %) had a confirmed fatal or nonfatal ischemic stroke, of whom 128 (57.9 %) and 93 (42.1 %) were in the higher and lower lipoprotein(a) group, respectively (P = 0.01). Table 2 displays the baseline features of individuals with and without recurrent ischemic stroke. The data revealed that those who experienced a recurrent ischemic stroke had higher levels of lipoprotein(a) than those who did not (median, 25.4 mg/dL, IQR, 9.8–53.6 mg/dL vs. median, 16.4 mg/dL; IQR, 6.7–45.2 mg/dL, P = 0.003) (eFig. 4 in Supplement).
Table 2.
Baseline characteristics of study population, according to clinical outcome.
| Characteristics | Without recurrent ischemic stroke (n = 1065) |
With recurrent ischemic stroke (n = 221) |
p Value |
|---|---|---|---|
| Age, mean (SD), y | 60.3 (9.1) | 62.7 (8.1) | <0.0001 |
| Sex, no. (%) | 0.90 | ||
| Female | 371/1065 (34.8) | 78/221 (35.3) | |
| Male | 694/1065 (65.2) | 143/221 (64.7) | |
| BMI, mean (SD), kg/m2 | 24.9 (3.1) | 25.5 (3.2) | 0.015 |
| Qualifying event, no. (%) | 0.67 | ||
| Transient ischemic stroke | 191/1065 (17.9) | 37/221 (16.7) | |
| Ischemic stroke | 874/1065 (82.1) | 184/221 (83.3) | |
| Previous ischemic stroke, no. (%) | 243/1065 (22.8) | 62/221 (28.1) | 0.10 |
| Previous transient ischemic stroke, no. (%) | 112/1065 (10.5) | 21/221 (9.5) | 0.65 |
| Previous myocardial infarction, no. (%) | 83/1065 (7.8) | 23/221 (10.4) | 0.20 |
| Hypertension, no. (%) | 873/1065 (82.0) | 194/221 (87.8) | 0.036 |
| Diabetes mellitus, no. (%) | 347/1065 (32.6) | 96/221 (43.4) | 0.002 |
| Smoking, no. (%) | 668/1065 (62.7) | 146/221 (66.1) | 0.35 |
| Symptomatic qualifying artery, no. (%) | 0.04 | ||
| Internal carotid | 149/1065 (14.0) | 37/221 (16.7) | |
| Middle cerebral | 572/1065 (53.7) | 98/221 (44.3) | |
| Vertebral | 158/1065 (14.8) | 40/221 (18.1) | |
| Basilar | 129/1065 (12.1) | 38/221 (17.2) | |
| Multiple arteries | 57/1065 (5.4) | 8/221 (3.6) | |
| Percent stenosis of affected artery, no. (%) | <0.001 | ||
| 50–69 % | 671/1065 (63.0) | 103/221 (46.6) | |
| 70–99 % | 394/1065 (37.0) | 118/221 (53.4) | |
| Biochemical measures | |||
| lipoprotein(a), median (IQR), mg/dl | 16.4 (6.7–45.2) | 25.4 (9.8–53.6) | 0.003 |
| LDL cholesterol, mean (SD), mg/dl | 115.1 (31.7) | 112.7 (31.2) | 0.29 |
| HDL cholesterol, mean (SD), mg/dl | 43.5 (10.7) | 42.3 (10.3) | 0.12 |
| Total cholesterol, mean (SD), mg/dl | 186.0 (37.5) | 182.1 (34.5) | 0.16 |
| Serum glucose, mean (SD), mmol/l | 6.8 (2.8) | 7.0 (2.8) | 0.22 |
SD, standard deviation; BMI, body mass index; IQR, interquartile range; LDL, low-density lipoprotein; HDL, high-density lipoprotein.
The risk of recurrent ischemic stroke was significantly higher for participants in the higher lipoprotein(a) group (HR, 1.43; 95 % CI 1.09–1.86; P = 0.009; Table 3) than for participants in the lower lipoprotein(a) group. Kaplan–Meier estimates of the cumulative event rate in the higher and lower lipoprotein(a) groups are presented in Fig. 1. When the lipoprotein(a) level was analyzed as a continuous variable, a comparable increase in risk was observed, with each doubling of the lipoprotein(a) level associated with a 20 % increase in the likelihood of recurrent ischemic stroke (HR, 1.20; 95 % CI 1.10–1.30; P < 0.001; Table 3). In the adjusted analyses, increased lipoprotein(a) level remained an independent predictor of recurrent ischemic stroke (Table 3).
Table 3.
Risk of recurrent ischemic stroke, according to lipoprotein(a) level.
| Risk of event | Hazard ratio (95 % CI)a lipoprotein(a) > 17.4 mg/dl |
p Value | Hazard ratio (95 % CI) per doubling of lipoprotein(a) level |
p Value |
|---|---|---|---|---|
| Unadjusted hazard ratio | 1.43 (1.09–1.86) | 0.009 | 1.20 (1.10–1.30) | P < 0.001 |
| Adjusted hazard ratio | ||||
| Model 1b | 1.42 (1.09–1.86) | 0.10 | 1.20 (1.10–1.30) | P < 0.001 |
| Model 2c | 1.44 (1.10–1.88) | 0.008 | 1.20 (1.10–1.31) | P < 0.001 |
| Model 3d | 1.38 (1.05–1.80) | 0.02 | 1.18 (1.09–1.29) | P < 0.001 |
The reference was patients with lipoprotein(a) ≤ 17.4 mg/dl.
In model 1, hazard ratios were adjusted for low-density lipoprotein cholesterol, total cholesterol, serum glucose.
In model 2, hazard ratios were adjusted for all factors in model 1, plus demographic variable (age, sex, hypertension, diabetes, smoking status, body mass index).
In model 3, hazard ratios were adjusted for all factors in model 2, plus imaging data (site of arterial stenosis, degree of arterial stenosis).
Fig. 1.
Kaplan-Meier analysis showing the cumulative incidence of recurrent ischemic stroke in patients stratified by lipoprotein(a) levels (≤17.4 mg/dL versus >17.4 mg/dL). The number of patients at risk at each time point is indicated below the graph.
As lipid-lowering drugs, such as statins, which are commonly prescribed following an ischemic stroke, may affect the lipoprotein level, sensitivity analyses were performed in 1101 participants with baseline lipoprotein(a) data. The final results resembled those observed in the complete cohort (eTables 1 and 2, and eFig. 5 in Supplement).
Among the 1286 participants analyzed, 631 (49.1 %) were allocated to the remote ischemic conditioning group, whereas 655 (50.9 %) were allocated to the control group. In the control group, the incidence of recurrent ischemic stroke was significantly higher for participants with higher lipoprotein(a) levels than for those with lower levels (adjusted HR, 1.73; 95 % CI, 1.19–2.56; P = 0.004; eTable 3). However, the lipoprotein(a) level did not significantly alter the risk of a recurrent stroke in the remote ischemic conditioning group (adjusted HR, 1.06; 95 % CI, 0.70–1.56; P = 0.83; eTable 4). When lipoprotein(a) was analyzed as a continuous variable, it was significantly associated with an elevated risk of recurrent ischemic stroke in both the control (adjusted HR per doubling of lipoprotein(a) level, 1.23; 95 % CI, 1.09–1.38; P < 0.001; eTable 3) and remote ischemic conditioning groups (adjusted HR per doubling of lipoprotein(a) level, 1.15; 95 % CI, 1.01–1.30; P = 0.032; eTable 4).
Effect of remote ischemic conditioning on risk of recurrent ischemic stroke, stratified by Lipoprotein(a) category
Among the 1286 RICA trial participants included in the analysis, remote ischemic conditioning did not decrease the risk of stroke recurrence (104 cases [15.8 %] in the remote ischemic conditioning and 121 cases [18.5 %] in the control group; unadjusted HR, 0.84; 95 % CI, 0.65–1.10; P = 0.20; adjusted HR, 0.82; 95 % CI, 0.63–1.07; P = 0.15; eFig. 6 in Supplement).
Among those with a higher lipoprotein(a) level (>17.4 mg/dL), the occurrence rate of ischemic stroke was 16.7 % in the remote ischemic conditioning group and 22.6 % in the control group (unadjusted HR, 0.70; 95 % CI, 0.49–1.003; P = 0.052; adjusted HR, 0.67; 95 % CI, 0.47–0.96; P = 0.03; Fig. 2). However, remote ischemic conditioning was not associated with decreased occurrence rate of ischemic stroke in participants with a lower lipoprotein(a) level (≤17.4 mg/dL) (unadjusted HR, 1.12; 95 % CI, 0.74–1.68; P = 0.60; adjusted HR, 1.10; 95 % CI, 0.73–1.66; P = 0.66; Fig. 2). Notably, the interaction between the intervention and lipoprotein(a) level was not statistically significant (Pinteraction = 0.097).
Fig. 2.
Kaplan-Meier analysis of the cumulative incidence of recurrent ischemic stroke in patients receiving either remote ischemic conditioning (RIC) or sham RIC, stratified by lipoprotein(a) levels. A. Lipoprotein(a) > 17.4 mg/dL. B. Lipoprotein(a) ≤ 17.4 mg/dL. The number of patients at risk at each time point is indicated below each graph.
Effect of remote ischemic conditioning on Lipoprotein(a) level
Further analyses were conducted on data from 128 participants with two lipoprotein(a) levels measured more than 3 months apart to ascertain whether or not remote ischemic conditioning affects the lipoprotein(a) level. Remote ischemic conditioning did not affect the lipoprotein(a) level (median, 17.3 [IQR, 8.4–47.3] mg/dL before; and 19.2 [IQR, 8.9–45.6] mg/dL after long-term remote ischemic conditioning; P = 0.86).
Discussion
In this study, we determined whether lipoprotein(a) levels could predict recurrent ischemic stroke in patients with symptomatic ICAS and whether the outcome of remote ischemic conditioning was influenced by lipoprotein(a) levels. We found that higher lipoprotein(a) levels were associated with a higher risk of recurrent stroke in patients with symptomatic ICAS throughout a median follow-up period of 3.3 years. Increment levels of lipoprotein(a) were identified as an independent risk factor for recurrent ischemic stroke in patients with elevated lipoprotein(a) levels. Furthermore, remote ischemic conditioning decreased the occurrence rate of recurrent ischemic stroke in participants with higher lipoprotein(a) levels but not in those with lower lipoprotein(a) levels. Nevertheless, this effect does not appear to have been mediated by a direct reduction in plasma lipoprotein(a) levels through remote ischemic conditioning.
Previous studies have presented that increased serum lipoprotein(a) levels are associated with both intracranial and extracranial artery stenosis [19]. This study also revealed a significant relevance between the enormity of intracranial artery stenosis and high levels of lipoprotein(a). However, the precise mechanism by which ICAS leads to ischemic stroke remain unclear. Three mechanisms have been proposed. First, rupture of a plaque may result in situ thrombosis, leading to vascular occlusion or artery-to-artery embolization. Second, severe stenosis may result in hemodynamic failure. Third, branch occlusion may occur due to plaque at the origin of small perforating arteries [5,20]. Theoretically, these three distinct mechanisms are all triggered by atherosclerosis. Evidence suggests that atherosclerotic cardiovascular disease and increased lipoprotein(a) levels are causally related [[21], [22], [23], [24]]. According to this study, among individuals with ICAS, lipoprotein(a) represents an independent risk factor for stroke recurrence. Lowering lipoprotein(a) levels may decrease the incidence of ischemic stroke and have a causal effect on the pathophysiology of stroke recurrence. These findings are of clinical relevance because lipoprotein(a)-lowering drugs are expected to become clinically available in the near future [18,25,26].
Our findings imply that remote ischemic conditioning lowered the incidence of recurrent ischemic stroke in individuals with elevated lipoprotein(a) levels but not in those with lower lipoprotein(a) levels. Notably, we did not find any interaction between lipoprotein(a) and remote ischemic conditioning, probably owing to the small sample size. The initial hypothesis was that remote ischemic conditioning directly reduces lipoprotein(a) levels. However, the results suggest that the beneficial influence of remote ischemic conditioning was not a direct consequence of a reduction in lipoprotein(a) level. Another plausible explanation is that individuals who have high lipoprotein(a) levels at a higher risk of experiencing stroke recurrence, and it is easier to confirm the efficacy of remote ischemia conditioning in these individuals. However, patients with severe ICAS had a considerably higher chance of stroke recurrence (≥70 %), and remote ischemic conditioning was not more efficacious in patients with severe stenosis [6]. We hypothesized that there may be a partial overlap between the pathogenic mechanisms of lipoprotein(a) and the protective mechanisms of remote ischemic conditioning, such as inflammation [27,28]. This study offers unique insights into the association between lipoprotein(a) levels, remote ischemic conditioning, and stroke recurrence in patients with ICAS. However, further studies are needed to validate this correlation and elucidate the underlying pathogenic mechanisms.
This study has some limitations. First, the conclusions are based on a post hoc analysis, and lipoprotein(a) was not a predetermined test in the RICA trial. Hence, approximately half of the RICA trial participants did not have lipoprotein(a) test results available and were excluded from the analysis. Nevertheless, even after the exclusion of participants without lipoprotein(a) results, this study remains one of the largest cohort on symptomatic ICAS to date [5]. Second, lipoprotein(a) was measured by the laboratories of the research centers, rather than in a central laboratory. However, we excluded participants whose lipoprotein (a) tests were performed in facilities not accredited by the China National Accreditation Service for Conformity Assessment to minimize potential measurement bias. Third, the lipoprotein(a) level was quantified in units of mg/dL, which is influenced by the size of the apolipoprotein(a) isoform. Although several guidelines and statements recommend reporting lipoprotein(a) levels in nmol/L, mg/dL remains the most commonly used reporting unit in most Chinese medical laboratories. Finally, all study participants were Chinese. Given the considerable interracial and interregional variability in lipoprotein(a) levels [29], the findings of this study need to be further validated in non-Chinese populations.
Author contributions
Drs. D. Wu, Ji, and C. Wu had complete access to all study data and are accountable for its integrity and the accuracy of the analysis. Drs C. Wu and Hou contributed equally to this work as co-first authors.
Study concept and design: C. Wu, Hou, Ji, D. Wu.
Acquisition, analysis, or interpretation of data: C. Wu, Hou, Zhao, C. Li, Chu, L. Wu, Wang, Zhou, Liu, Zhang, M. Li, Ma, Ding, Meng, Ji, D. Wu.
Drafting of the manuscript: C. Wu, Hou, D. Wu.
Critical revision of the manuscript for important intellectual content: C. Wu, Hou, Zhao, C. Li, Chu, L. Wu, Wang, Zhou, Liu, Zhang, M. Li, Ma, Ding, Meng, Ji, D. Wu.
Statistical analysis: Hou.
Obtained funding: D. Wu, Ji, C. Wu.
Administrative, technical, or material support: Hou, Zhao, C. Li, Chu, L. Wu, Wang, Zhou, Liu, Zhang, M. Li, Ma, Ding, Meng, Ji.
Study supervision: D. Wu, Ji, C. Wu.
Funding
This research is supported by the National Natural Science Foundation of China (grant numbers 82271507), the Beijing Natural Science Foundation (JQ24041), Noncommunicable Chronic Diseases - National Science and Technology Major Project (2030ZD0505400-2023ZD0505403)and the Beijing Physician Scientist Training Project (BJPSTP-2024-04).
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
We appreciate the research coordinators and site investigators.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.neurot.2025.e00579.
Contributor Information
Xunming Ji, Email: jixm@ccmu.edu.cn.
Di Wu, Email: seadi-wu@163.com.
Appendix A. Supplementary data
The following is the Supplementary data to this article:
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