Introduction

Diabetes Mellitus (DM) is a heterogeneous metabolic disorder identified by persistent hyperglycemia. Based on etiology and pathophysiology, DM can be classified into type 1 (T1DM), type 2 (T2DM), gestational DM, and other specific causes of DM.1 The number of people affected by DM continues to rise at a pace that has made it one of the most consequential metabolic diseases worldwide. The International Diabetes Federation (IDF) reported that 588.7 million people were living with diabetes in 2024, and projections indicate a steep rise to 852.5 million over the next two decades.2 According to the World Health Organization (WHO), more than 95% of this diabetic population has T2DM.

As the most widespread type of DM, intensive research on the detection, treatment, and prevention of T2DM has been reported,3 yet its pathophysiology is not fully understood. T2DM is a complex metabolic disorder, a condition in which lipid abnormalities, chronic inflammation, and endothelial injury play central roles, resulting in deficient insulin secretion by the pancreatic islet β-cell.4 This multifactorial nature has pushed clinicians and researchers to explore biomarker candidates capable of capturing the complexity of diabetic risk beyond hyperglycemia alone.

Traditional biomarkers, such as fasting glucose, hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and related indices, remain fundamental to diabetes management, yet they unveil only a small part of the wide inter-individual variation in metabolic deterioration and vascular complications.5,6 Compared with non-high-density lipoprotein cholesterol (non-HDL-C) and apolipoprotein B (apoB), remnant cholesterol (RC) may more directly reflect triglyceride-rich lipoprotein (TRL) remnants that are highly prevalent in insulin-resistant states. This makes RC particularly relevant in T2DM. Despite intensive glycemic control and the broad use of statins, many individuals with T2DM continue to develop progressive organ damage, particularly vascular injury.7 This gap has urged the exploration of alternative risk indicators and therapeutic targets, HDL-C,8 apoB,9 and TRL subclasses such as RC.10

RC represents the cholesterol content of partially lipolyzed TRLs, and its elevation reflects a specific metabolic disturbance tied closely to insulin resistance: the overproduction of hepatic very-low-density lipoprotein (VLDL), impaired lipolysis, and reduced clearance of remnant particles.11–13 RC provides a dynamic readout of TRL handling, a process that is disproportionately altered in T2DM.14 In epidemiologic and clinical studies, associations between RC and T2DM persist even after extensive adjustment for LDL-C, TG, apoB, and conventional T2DM risk factors.15 This also explains why individuals with well-controlled LDL-C can still exhibit high T2DM risk when RC is elevated. Therefore, RC presents as a potential biomarker and therapeutic target.

Given the persistent residual risk observed in T2DM, understanding RC has become increasingly relevant. This review aims to synthesize current knowledge on the metabolic origins of RC in T2DM, examine the mechanistic pathways by which RC promotes atherosclerosis and vascular diseases, evaluate clinical evidence supporting its role as an independent risk factor, and consider its potential implications for diagnosis, risk stratification, and therapy. By situating RC within the broader metabolic disturbances of T2DM, this review seeks to clarify why remnant cholesterol is emerging as a compelling and clinically actionable component of diabetic dyslipidemia.

Methods

This narrative review synthesizes current evidence on remnant cholesterol as an independent atherogenic lipoprotein in T2DM. A literature search was conducted in PubMed and Scopus databases to identify relevant publications primarily from the past decade. The search strategy included combinations of the following keywords: atherogenic lipoprotein, cardiovascular risk, insulin resistance, and remnant cholesterol, filtered to the publication period from 2015 to 2025. Original research articles, cohort and population-based studies, mechanistic and genetic investigations, and relevant clinical trials written in English were selected. Reference lists of key articles were also manually screened. As this work represents a narrative review, no formal systematic review protocol or meta-analysis was applied.

Pathophysiology and Measurement of RC Metabolic Pathway of RC

RC originates from the metabolism of hepatic TRLs, which enter circulation via two major pathways: hepatic secretion of VLDL and intestinal absorption of dietary lipids as chylomicrons.16 As illustrated in Figure 1, during normal lipolysis, lipoprotein lipase (LPL) breaks down VLDL and chylomicron to their remnant forms: VLDL remnants, intermediate density lipoprotein (IDL), and chylomicron remnants, before being efficiently cleared by hepatic receptors.17 This tightly coordinated system ensures that remnants circulate only briefly under healthy metabolic conditions.

Figure 1 Metabolic pathway and atherogenic mechanism of RC. The blue lines represent the internalization of RC particles into the artery, and the green lines represent de novo lipolysis.

Abbreviations: LRP, lipoprotein receptor protein; HSPG, heparan sulfate proteoglycans; LDRL, low-density receptor protein, LDL, low-density lipoprotein; IDL, intermediate-density lipoprotein; VLDL, very low-density lipoprotein; LPL, lipoprotein lipase; FFA, free fatty acid; ROS, reactive oxygen species.

However, RC is highly sensitive to insulin action and lipolytic efficiency; therefore, their levels become disproportionately elevated when insulin signaling is disrupted.18 Insulin resistance (IR) shifts hepatic nutrient handling toward de novo lipogenesis and increases the production of apoB-containing VLDL.19 In parallel, impaired insulin signaling in adipose tissue enhances lipolysis, thereby increasing the flux of free fatty acids entering the liver. These changes supply a continuous substrate stream for TRL overproduction.20 Simultaneously, reduced LPL activity and alterations in apolipoprotein composition, especially elevations in apoC-III (an inhibitor of both lipolysis and hepatic uptake), slow the conversion and clearance of TRL remnants. These disturbances, coupled with impaired glucose oxidation and mitochondrial stress, create a metabolic environment that supports sustained RC elevation.21

In contrast to LDL, which represents the end-product of intravascular lipolysis, RC particles retain a heterogeneous composition of cholesterol, surface apolipoproteins (apoE, apoC-II/III), and residual TG, giving them metabolic properties that are highly sensitive to insulin action and hepatic clearance pathways.22 This biochemical identity is central to their atherogenicity: remnants are sufficiently small to enter the arterial intima yet large enough to deposit disproportionately greater cholesterol mass per particle once retained in the macrophage-rich subendothelial space.

Atherogenic Mechanism of RC in T2DM

Due to their small size and composition, RC particles easily penetrate the arterial intima and deliver a substantial amount of cholesterol directly to macrophages without requiring oxidative modification.23 As illustrated in Figure 1, once within the vascular wall, RC act as pro-inflammatory stimuli: macrophages exposed to RC upregulate cytokines such as IL-6 and TNF-α, amplifying leukocyte recruitment and sustaining a local inflammatory milieu.24 RC also drives oxidative stress through increased production of reactive oxygen species, reducing nitric oxide bioavailability, and impairing endothelial function.25 The inflammation accelerates foam-cell formation and early lesion development.26

It is worth noting that these vascular effects occur independently of traditional lipid parameters, helping to explain why individuals with T2DM continue to exhibit high cardiovascular risk even after achieving optimal LDL-C control. This is why elevated RC shows strong, independent associations with cardiometabolic events in T2DM even after adjustment for LDL-C, TG, glycemic indices, and markers of systemic inflammation: RC amplifies pathogenic pathways that are already dysregulated in diabetes, rather than acting as a passive marker of dyslipidemia.27

Measurement of RC

RC can be measured directly using homogeneous enzymatic assays (RemL-C), which selectively measure cholesterol contained within TRL remnants. The method employs surfactants and reactive masking agents that render LDL-C and HDL-C enzymatically inactive, while leaving remnant particles accessible to cholesterol esterase and cholesterol oxidase. The liberated cholesterol is subsequently quantified through a standard peroxidase-coupled colorimetric reaction on an automated chemistry analyzer.28 This approach is independent of triglyceride level or LDL-C estimation error, and is particularly suited for evaluating TRL metabolism in T2DM.

Alternatively, the RC level can be calculated using the following formula:

RC = Total Cholesterol – LDL-C – HDL-C29

Where LDL-C is typically derived using the Martin–Hopkins or the Friedewald method, this approach is analytically convenient and reproducible, allowing for large cohort analyses. Nonetheless, the level of LDL-C is unstable when T2DM complications are present, including elevated TG, IR, or hepatic overproduction of VLDL. Since the RC value is derived from the LDL-C value as one of the parameters, the calculated RC may not accurately reflect the true cholesterol mass carried in remnants.

Varbo & Nordestgaard compare the direct and calculated RC value of 16,207 individuals over 14 years. Although direct and calculated RC provided similar hazard ratios (HR) for high-risk individuals (myocardial infarction (MI) HR 2.05 vs 1.93 for ≥95th percentile), the two methods diverged at the level of clinical classification. Despite having a normal calculated RC, 5% of the population exhibited high direct RC, a subgroup that carried an 83% higher risk of MI (HR 1.83). Conversely, individuals with high calculated RC alone showed no meaningful excess risk. These discordant findings illustrate that direct RC captures a phenotype of cholesterol-rich, triglyceride-poor remnants that calculated RC fails to identify particles that are particularly relevant in insulin-resistant metabolism, where lipolysis is impaired and apoB-containing remnants accumulate.30

Most clinical and epidemiological studies rely on calculated RC because it is inexpensive, universally obtainable from standard lipid panels, and requires no specialized instrumentation. On the other hand, despite its high precision in isolating cholesterol within remnant-rich particles, the direct RemL-C assay is less preferable due to limited availability and higher cost. These methodological differences have practical consequences: calculated RC tends to yield slightly higher absolute values in individuals with elevated TG, whereas direct assays may identify a subset of patients whose remnants are disproportionately cholesterol-dense despite only modest triglyceride levels. Thus, the choice of method shapes the distribution of RC within a population and can influence how individuals are classified as having “high” or “normal” remnant cholesterol. This emphasizes the need to interpret RC values within the context of the assay used, particularly when comparing studies or considering potential clinical cut-offs.

Clinical Evidence: RC as an Independent Risk Factor

A growing body of clinical work shows that RC captures cardiometabolic risk that conventional lipids often miss. Elevated RC has been linked not only to the future development of T2DM but also to a broad set of downstream complications once diabetes is established. As summarized in Table 1, elevated or unstable RC showed reproducible associations with outcomes spanning macrovascular disease to microvascular injury. These findings position RC as a meaningful indicator of residual risk across the diabetes continuum. The following sections examine these complications in greater detail, outlining how RC contributes to each domain and where its clinical relevance is most clearly demonstrated.

RC as a Predictor of T2DM Onset

A retrospective Chinese cohort study by Li et al demonstrated RC’s independent role in predicting new-onset T2DM.31 The study showed that a one-standard-deviation (1-SD) increase in RC conferred a 13.4% higher risk of developing T2DM (adjusted HR, 1.134; p = 0.025). Notably, RC remained significant after adjusting for TG, LDL-C, HDL-C, body mass index (BMI), liver enzymes, smoking, and alcohol use, demonstrating that RC captures metabolic risk beyond traditional lipids. In this cohort, RC outperformed LDL-C and TG as a predictor, highlighting its closer relationship to insulin resistance and early β-cell strain.

In a large Japanese population followed for 93,537 person-years, Yang et al reported that the relationship between RC and incident T2DM is profoundly influenced by hepatic metabolic vulnerability. Among individuals with non-alcoholic fatty liver disease (NAFLD) that shows impaired hepatic insulin signaling, those in the highest quartile of RC faced a 68% higher risk of developing T2DM compared with the lowest quartile (adjusted HR 1.68; 95% confidence interval (CI) 1.13–2.51). Conversely, in participants without NAFLD, the association diminished after multivariable adjustment, suggesting that RC interacts with hepatic steatosis to accelerate glycemic deterioration.32 This finding aligns with the concept that RC is tightly linked to hepatic insulin resistance, a core defect that precedes hyperglycemia.

The National Health and Nutrition Examination Survey (NHANES) from the US complements this perspective. In the NHANES 2013–2018 analysis, Li et al identified a clear nonlinear, dose-dependent association between RC and prevalent T2DM. A threshold emerged around 19 mg/dL, beyond which diabetes odds rose sharply. Individuals in the highest RC quartile had more than threefold higher odds of T2DM compared with the lowest quartile (adjusted odds ratio (OR) ≈ 3.11). Even below the threshold, RC behaved as a sensitive metabolic indicator, with each 1 mg/dL increase associated with a 46% rise in T2DM odds within the lower RC range.33 This pattern suggests that RC captures early metabolic inflection points, subtle shifts in lipoprotein handling, and insulin signaling that precede overt biochemical abnormalities.

These studies depict that the RC biomarker is tightly aligned with the biology of T2DM onset. Its elevation co-occurs with hepatic nutrient overload, impaired insulin action, and the rising secretory pressure on pancreatic β-cells. Unlike LDL-C or TG, RC reflects a stage of metabolic deterioration where lipid and glucose pathways intersect. The consistency of its predictive performance across ethnicities, study designs, and metabolic backgrounds positions RC as a valuable early indicator of T2DM risk.

RC and Macrovascular Atherosclerotic Complications in T2DM

The clinical expression of atherosclerotic macrovascular disease in T2DM is multifaceted, ranging from coronary plaque instability to cardiovascular events. The strongest macrovascular evidence comes from the reanalysis of the Accurate Consensus Reporting Document (ACCORD) by Fu et al. Among 10,196 adults with T2DM for a median of 8.8 years, 1,815 major adverse cardiovascular events (MACEs) occurred. Each one-standard-deviation (1-SD) increase in RC conferred a 7% higher risk of MACE (HR 1.07, 95% CI 1.02–1.12), independent of traditional lipid markers. Importantly, fluctuations in RC measured as visit-to-visit variability were even more predictive: patients in the highest variability strata showed 41–45% greater risk for MACEs.34 These patterns highlight RC not only as a static risk factor but as a dynamic indicator of ongoing atherogenic flux.

Population-based work by Hu et al focuses on early arterial changes rather than clinical events. An RC threshold around 24 mg/dL corresponded with reduced ankle-brachial index (ABI) and heightened leukocyte counts. Mediation analysis attributed 14% of the RC-vascular association to insulin resistance, with additional contributions from low-grade inflammation, indicating that remnants reflect intertwined metabolic and inflammatory pressure on the vasculature. Even without longitudinal follow-up, the constellation of perfusion deficits and inflammatory activation points toward an arterial environment primed for accelerated atherosclerosis.35

A recent multicenter study further links elevated RC to subclinical arterial injury. Among 158 adults with T2DM, participants above the median RC level exhibited significantly greater carotid intima thickness (CIT) compared with those below the median, despite comparable age, BMI, glycemic indices, and HDL-C. Notably, the effect was specific to the intimal layer: CIT differed markedly between high- and low-RC groups, while carotid intima media thickness did not. Multiple regression analysis identified RC as an independent determinant of CIT (β = 0.473, p = 0.005), reinforcing the concept that RC exerts targeted adverse effects on early arterial remodeling even before global intima media thickening becomes measurable.36

Peripheral arterial disease (PAD) also shows sensitivity to RC burden. In the Japanese cohort studied by Matsushima-Nagata et al, a RemL-C level of 0.24 mmol/L identified individuals with greater arterial stiffness and worse PAD indicators. Remnant concentrations correlated more strongly with measures like brachial-ankle pulse wave velocity (baPWV) than LDL-C or traditional TG, suggesting that remnants better capture the diffuse arterial thickening and loss of elasticity characteristic of diabetic vasculopathy.28

The other studies of RC-related macrovascular complications summarized in Table 1 show that RC is repeatedly present in the background of these atherogenic risks: it predicts cardiovascular events, identifies early arterial damage, and captures systemic vascular stiffness more sharply than LDL-C or TG. For clinicians, this means RC provides a window into vascular processes that remain active even when guideline-directed lipid targets are met. Its performance across settings underscores its relevance as a distinct vascular risk determinant in DM.

Table 1 Representative Studies on the Relationship Between Remnant Cholesterol (RC) and Macrovascular-Microvascular Injury

RC and Microvascular Complications in T2DM

Although microvascular complications do not develop classical atherosclerotic plaques, the same biochemical properties that make RC particles atherogenic in large arteries also impose strain on capillary-level and arteriolar networks. RC exposure in the endothelium increases oxidative stress, reduces nitric oxide bioavailability, and intensifies local inflammatory signaling, which directly undermines microvascular stability.49 In the context of T2DM, where the microcirculation is already compromised by hyperglycemia, advanced glycation, and impaired autoregulatory capacity, these additional insults potentially accelerate renal and retinal injury.44,50

The most compelling quantitative evidence comes from a nationwide renal cohort study of 2.53 million adults with T2DM by Roh et al, which demonstrated a clear dose-response gradient between RC and the development of end-stage renal disease (ESRD). Relative to the lowest RC quartile, ESRD risk rose steadily across quartiles, HR 1.12, 1.20, and 1.33 for Q2-Q4, despite adjustment for demographic, metabolic, and therapeutic factors. The association persisted across sex, age, lipid-lowering status, and comorbidity profiles, and was amplified in individuals with hypertension, obesity, early CKD, or longer diabetes duration.41 This large-scale population signal is consistent with RC acting as a vascular stressor that precedes overt renal failure.

Retinal microcirculation exhibits similar susceptibility, though in a non-linear fashion. In Pan et al’s study of 1,964 Taiwanese adults with T2DM, overall associations between RC and diabetic retinopathy (DR) were not significant in fully adjusted models. However, generalized additive models uncovered non-linear thresholds. When RC was below 13 mg/dL, each 1-mg/dL increase was associated with a 19.4% rise in DR odds (OR 1.194; 95% CI 1.070–1.333). For proliferative retinopathy, an inflection emerged at 39 mg/dL; below this point, each 1-mg/dL RC increase raised PDR odds by 2.1% (OR 1.021; 95% CI 1.004–1.038).43 These threshold effects suggest that retinal micro-vessels, highly oxygen-dependent and structurally delicate, may respond to RC-driven endothelial stress in a graded manner, with injury emerging most clearly at specific metabolic states.

Beyond the kidney and retina, a parallel microvascular vulnerability is increasingly recognized within the central nervous system. Studies linking RC to cerebral small vessel disease (CSVD) and diabetes-related cognitive impairment suggest that small penetrating arterioles in the brain exhibit the same sensitivity to oxidative stress, endothelial dysfunction, and impaired vasoreactivity that characterizes peripheral microvascular beds.48 Higher RC has been associated with greater white-matter hyperintensity burden, reduced microstructural integrity, and poorer performance on cognitive testing patterns that are difficult to attribute solely to macrovascular pathology.47 Instead, they point to a microangiopathic process in which RC amplifies the chronic hypoperfusion and inflammatory milieu already present in diabetes. This convergence across organs supports the notion that microvascular systems share a common susceptibility to RC-driven injury.

Therapeutic and Clinical Implications

Contemporary therapeutic strategies relevant to RC modulation span traditional lipid-lowering agents, regulators of TRL metabolism, and emerging biologics that directly target remnant-forming pathways. What becomes evident across these approaches is a dissociation between the biochemical ability to lower RC and the clinical capacity to translate these changes into reduced cardiovascular or microvascular events in T2DM.

Statins remain the foundation of lipid management, and recent cohort work demonstrates that high-intensity regimens can meaningfully reduce RC and substantially increase the proportion of patients achieving RC targets.51 Nevertheless, even under optimized statin therapy, a considerable proportion of T2DM patients exhibit persistent elevations in RC, emphasizing that LDL-centered lipid lowering incompletely addresses the TRL remnant axis.52 This residual burden is consistent with longitudinal evidence showing that RC continues to predict major adverse cardiovascular events despite aggressive LDL-C reduction.

The Pemafibrate to Reduce Cardiovascular Outcomes by Reducing Triglycerides in Patients with Diabetes (PROMINENT) trial provides an instructive contrast. Although pemafibrate robustly lowered TG, VLDL-C, RC, and apoC-III, it conferred no cardiovascular benefit among more than 10,000 individuals with T2DM.53 The lack of event reduction despite clear biochemical improvements suggests that lowering circulating remnant cholesterol alone may be insufficient when hepatic VLDL overproduction and systemic insulin resistance remain unmodified. This result shifts the field from a simplistic “lower-is-better” paradigm to one that recognizes the metabolic context in which RC is generated. Legacy therapies such as niacin similarly illustrate the limitation of modifying RC indirectly. Despite modest favorable effects on HDL-C and lipoprotein(a), niacin has not demonstrated convincing efficacy in slowing atherosclerotic progression, and its glycemic liabilities reduce its applicability in diabetic populations.54 For this reason, niacin now occupies a minimal role in modern RC-oriented management.

By contrast, therapies that intervene upstream in TRL metabolism, specifically those targeting APOC3 and ANGPTL3, offer a mechanistic precision that aligns more closely with the biology of remnant particle formation. ApoC-III inhibition accelerates remnant clearance and markedly reduces postprandial TRL burden, while ANGPTL3 inhibition simultaneously lowers RC, apoB, and hepatic lipid flux. Early studies show substantial reductions in atherogenic remnants with these agents, and unlike fibrates or niacin, they modify the pathways that give rise to RC rather than simply clearing its downstream products.55,56 Although long-term cardiovascular outcome trials remain ongoing, these biologics represent the most rational strategy for addressing RC-driven residual risk in T2DM.

This mechanistic framing is consistent with the broader metabolic model described in the review by Li et al, who emphasize that RC in diabetes should be approached not solely as a lipid abnormality but as a metabolic phenotype arising from insulin resistance, hepatic fat accumulation, apoC-III-mediated lipolysis inhibition, and impaired postprandial clearance.57 Their synthesis argues for integrated therapy in which LDL-C reduction (via statins) is complemented by agents that specifically modulate TRL production, lipase function, or hepatic fatty acid flux. Such an approach is further supported by insights from recent enzymology studies, which show that T2DM-associated alterations in hepatic lipase and endothelial lipase generate cholesterol-enriched remnants that are more readily sequestered in the arterial intima, reinforcing that metabolic correction, not solely numerical RC reduction, is required to influence clinical outcomes.

Therapeutically, targeting RC could bridge a critical gap in current diabetes management, focusing on postprandial triglyceride metabolism and remnant clearance. RC is a modifiable target, but not all RC-lowering strategies are equally capable of reducing atherosclerotic progression. Potential interventions of integrated therapy include statins, fibrate therapy, omega-3 fatty acids, APOC3 or ANGPTL3 inhibition, and other therapies addressing postprandial lipemia.58 Therapies that merely shift circulating lipid fractions without correcting TRL overproduction or remnant retention have limited clinical effect, whereas agents that intervene at regulatory nodes of TRL metabolism hold the greatest promise for altering the natural history of diabetic vascular disease. Ultimately, this therapeutic insight indicates that RC should be recognized as an independent therapeutic target in diabetes care, complementing LDL-C and non-HDL-C reduction strategies, to mitigate both macrovascular and microvascular complications.

Research Limitations and Gaps

Although the accumulated evidence strongly supports RC as an independent atherogenic factor in T2DM, several issues complicate interpretation and limit translation into practice. A major constraint arises from the study designs that dominate this field. Much of the available work relies on observational or cross-sectional analyses, such as those by Matsushima-Nagata et al,28 Song et al,37 and Wu et al,59 which are invaluable for identifying associations but cannot establish causal relationships. Whether modifying RC directly alters cardiometabolic or renal trajectories in T2DM remains an unanswered question.

Another challenge is methodological heterogeneity. RC is variably quantified using calculated values (typically TC − LDL-C − HDL-C) or directly measured RemL-C, and LDL-C itself is often derived from differing equations (Friedewald vs Martin–Hopkins). These discrepancies produce wide variation in reported clinical thresholds, spanning roughly 0.56 to 0.80 mmol/L across East Asian cohorts and make it difficult to compare findings across studies or apply them consistently in clinical settings.

The mechanistic literature lags behind epidemiologic insights. While many studies invoke insulin resistance, inflammation, and oxidative stress as likely intermediates, few have directly interrogated the molecular pathways through which remnants injure vascular tissue. The specific contributions of APOC3-mediated lipolysis inhibition, ANGPTL3-driven TRL retention, or RC-induced endothelial transcriptomic dysregulation remain poorly characterized, as emphasized by Bornfeldt.60

Questions about generalizability also persist. The bulk of RC research has been conducted in East Asian populations, which differ from Western and multiethnic cohorts in lipoprotein metabolism, patterns of visceral adiposity, and dietary fat exposure. As a result, the external validity of current findings, particularly regarding cut-off values and risk magnitudes, remains uncertain.

Finally, although renal outcomes have been studied extensively,12,61 evidence for other microvascular sequelae is limited. Associations with retinopathy or neuropathy are inconsistently reported, and mechanistic explanations for these relationships are still speculative. This gap is striking given the shared endothelial vulnerabilities that link remnant accumulation to both microvascular and macrovascular injury. Altogether, these limitations highlight the need for harmonized measurement strategies, diverse populations, mechanistic depth, and controlled interventional trials to firmly establish RC’s role as a modifiable target in diabetic vascular disease.

Future Directions

Despite the growing recognition of RC as a clinically meaningful atherogenic particle in T2DM, the current evidence base remains incomplete. Several key avenues below require focused investigation:

First, definitive RCTs are urgently needed to establish whether targeted lowering of RC through fibrates, omega-3 formulations, APOC3 or ANGPTL3 inhibitors, or combination regimens can translate into meaningful reductions in cardiovascular events or renal deterioration. Observational associations, however robust, cannot substitute for mechanistic or interventional confirmation.

Second, the field requires harmonization of RC quantification. Both calculated and directly measured approaches are used across studies, yielding heterogeneous cut-offs and complicating integration across cohorts. Establishing validated thresholds for high-risk states (eg, ≥ 0.56 mmol/L for renal risk or ≥ 0.64 mmol/L for peripheral arterial dysfunction) should be a priority for clinical translation and guideline adoption.

Third, mechanistic research remains sparse. The molecular determinants of RC-induced vascular injury, including the roles of APOC3, APOE isoforms, ANGPTL3, and postprandial lipoprotein metabolism, are largely inferred rather than demonstrated. Integrating lipidomics, transcriptomics, and endothelial functional assays could clarify how remnants promote oxidative stress, immune activation, and intimal retention in the diabetic milieu.

Fourth, future work must include more ethnically and clinically diverse populations. Much of the current evidence originates from East Asian cohorts; replication in European, African, and multiethnic populations is essential to establish generalizability. Moreover, specific high-risk subgroups such as young-onset diabetes, patients with advanced CKD, and post-revascularization populations remain underexamined.

Finally, incorporating RC into predictive modeling represents an important translational step. Algorithms that integrate RC alongside LDL-C, non-HDL-C, HbA1c, and inflammatory markers may refine cardiovascular and renal risk stratification in diabetes and help identify individuals who would benefit from early or intensified lipid intervention.

Together, these research directions outline a pathway toward moving RC from an emerging biomarker to a validated therapeutic target in diabetes care.

Conclusion

RC has emerged as a central yet long-overlooked driver of vascular injury in T2DM. Distinct from LDL-C, remnants carry a disproportionately large cholesterol payload, penetrate the arterial wall with ease, and trigger inflammatory and metabolic perturbations that accelerate atherogenesis. Across diverse cohorts, elevated RC consistently predicts incident diabetes, cardiovascular events, renal deterioration, and peripheral vascular injury, even when LDL-C, TG, and glycemic indices are optimally controlled. This constellation of evidence positions RC as a critical component of the residual risk that persists in modern diabetes management. Although much has been learned, several gaps remain, including standardized measurement, mechanistic insight, and interventional data. Addressing these gaps will be essential for determining whether RC should enter routine risk assessment and serve as a therapeutic target alongside LDL-C and non-HDL-C. As understanding deepens, RC may ultimately reshape the lipid-centric framework of diabetes care, offering new opportunities to mitigate the disproportionate cardiovascular burden borne by this population.

Acknowledgments

The authors gratefully acknowledge the financial support provided by the Directorate of Research, Downstream, and Community Engagement, Universitas Padjadjaran, through the Rector’s initiative for covering the article processing charges (APC) via The Indonesian Endowment Fund for Education (LPDP) on behalf of the Indonesian Ministry of Higher Education, Science and Technology, and managed under the EQUITY Program.

This study is a part of the dissertation work of the first author in the Doctoral Program in Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran. The authors also thank all the Reviewers and Editors for their valuable feedback that helped improve the quality and clarity of this manuscript.

Author Contributions

All authors have made a significant contribution to the work reported, whether that is in the Conception, Study Design, Execution, Acquisition of Data, Analysis and Interpretation, or in all these areas; all authors took part in Drafting, Revising or Critically Reviewing the Article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

(1) The Indonesian Endowment Fund for Education (LPDP) of the Indonesian Ministry of Finance of the Republic of Indonesia, for the tuition fee and research of the first author (document contract number SKPB10106/LPDP/LPDP.3/2024); (2) The Indonesian Endowment Fund for Education (LPDP) on behalf of the Indonesian Ministry of Higher Education, Science and Technology, and managed under the EQUITY Program (document contract number 4303/B3/DT.03.08/2025 and 3927/UN6. RKT/HK.07.00/2025) for the APC.

Disclosure

The authors declare that there are no conflicts of interest—financial, academic, or personal—related to the research, authorship, or publication of this article.

References

1. American Diabetes Association Professional Practice Committee. 2. Diagnosis and classification of diabetes: standards of care in diabetes-2025. Diabetes Care. 2025;48(1 Suppl 1):S27–13. doi:10.2337/dc25-S002

2. Magliano DJ, Boyko EJ; IDF Diabetes Atlas 10th edition scientific committee. IDF Diabetes Atlas. 10th ed. Brussels: International Diabetes Federation; 2021.

3. Gieroba B, Kryska A, Sroka-Bartnicka A. Type 2 diabetes mellitus - conventional therapies and future perspectives in innovative treatment. Biochem Biophys Rep. 2025;42:102037. doi:10.1016/j.bbrep.2025.102037

4. Galicia-Garcia U, Benito-Vicente A, Jebari S, et al. Pathophysiology of type 2 diabetes mellitus. Int J Mol Sci. 2020;21(17):6275. doi:10.3390/ijms21176275

5. Lu X, Xie Q, Pan X, et al. Type 2 diabetes mellitus in adults: pathogenesis, prevention and therapy. Signal Transduct Target Ther. 2024;9(1):262. doi:10.1038/s41392-024-01951-9

6. Packard CJ. Remnants, LDL, and the quantification of lipoprotein-associated risk in atherosclerotic cardiovascular disease. Curr Atheroscler Rep. 2022;24(3):133–142. doi:10.1007/s11883-022-00994-z

7. Antar SA, Ashour NA, Sharaky M, et al. Diabetes mellitus: classification, mediators, and complications; A gate to identify potential targets for the development of new effective treatments. Biomed Pharmacother. 2023;168:115734. doi:10.1016/j.biopha.2023.115734

8. Tan J, Zhu H, Zeng Y, et al. Non-high-density lipoprotein to high-density lipoprotein cholesterol ratio and type 2 diabetes in middle-aged and elderly Chinese. Sci Rep. 2025;15(1):8485. doi:10.1038/s41598-024-84686-5

9. Bekbossynova M, Ivanova-Razumova T, Kali A, et al. Apolipoprotein B and glycemic dysregulation: new predictors of type 2 diabetes in high-cardiovascular-risk populations. J Pers Med. 2025;15(5):163. doi:10.3390/jpm15050163

10. Huh JH, Roh E, Lee SJ, et al. Remnant cholesterol is an independent predictor of type 2 diabetes: a Nationwide Population-Based Cohort Study. Diabetes Care. 2023;46(2):305–312. doi:10.2337/dc22-1550

11. Sebastian-Valles F, Montes Muñiz Á, Marazuela M. Remnant cholesterol: from pathophysiology to clinical implications in type 1 diabetes. Endocrines. 2025;6(3):46. doi:10.3390/endocrines6030046

12. Karakasis P, Patoulias D, Rizzo M, et al. Association between remnant cholesterol and chronic kidney disease: systematic review and meta-analysis. Diabetes Obes Metab. 2025;27(5):2573–2583. doi:10.1111/dom.16258

13. Li Y, Zeng Q, Peng D, et al. Association of remnant cholesterol with insulin resistance and type 2 diabetes: mediation analyses from NHANES 1999-2020. Lipids Health Dis. 2024;23(1):404. doi:10.1186/s12944-024-02393-6

14. Gugliucci A. Triglyceride-rich lipoprotein metabolism: key regulators of their flux. J Clin Med. 2023;12(13):4399. doi:10.3390/jcm12134399

15. Miyake T, Furukawa S, Kanamoto A, et al. Effect of remnant cholesterol on the onset of diabetes mellitus. J Diabetes Investig. 2026;17(1):120–128. doi:10.1111/jdi.70163

16. Cui D, Yu X, Guan Q, et al. Cholesterol metabolism: molecular mechanisms, biological functions, diseases, and therapeutic targets. Mol Biomed. 2025;6(1):72. doi:10.1186/s43556-025-00321-3

17. Chen X, Li LH. Remnant cholesterol, a valuable biomarker for assessing arteriosclerosis and cardiovascular risk: a systematic review. Cureus. 2023;15(8):e44202. doi:10.7759/cureus.44202

18. Hao X, Li D, Huang X, et al. Remnant cholesterol, a potential risk factor of metabolic dysfunction-associated fatty liver disease. Nutr Metab. 2025;22(1):13. doi:10.1186/s12986-025-00898-0

19. Wadström BN, Pedersen KM, Wulff AB, et al. Elevated remnant cholesterol and atherosclerotic cardiovascular disease in diabetes: a population-based prospective cohort study. Diabetologia. 2023;66(12):2238–2249. doi:10.1007/s00125-023-06016-0

20. García-Rodríguez S, Espinosa-Cabello JM, García-González A, et al. Interplay of postprandial triglyceride-rich lipoprotein composition and adipokines in obese adolescents. Int J Mol Sci. 2024;25(2):1112. doi:10.3390/ijms25021112

21. Ginsberg HN, Packard CJ, Chapman MJ, et al. Triglyceride-rich lipoproteins and their remnants: metabolic insights, role in atherosclerotic cardiovascular disease, and emerging therapeutic strategies-a consensus statement from the European Atherosclerosis Society. Eur Heart J. 2021;42(47):4791–4806. doi:10.1093/eurheartj/ehab551

22. Baratta F, Cocomello N, Coronati M, et al. Cholesterol remnants, triglyceride-rich lipoproteins and cardiovascular risk. Int J Mol Sci. 2023;24(5):4268. doi:10.3390/ijms24054268

23. Bharadiya VM, Rawal S, Jain V, et al. Triglyceride-rich lipoproteins, remnants, and atherosclerotic cardiovascular disease risk. Curr Cardiovasc Risk Rep. 2022;16:131–144. doi:10.1007/s12170-022-00702-1

24. Xiong YJ, Shao DM, Zhu XY, et al. Joint Association of remnant cholesterol and body mass index with hypertension: a National Cohort Study in Chinese Adults. J Multidiscip Healthc. 2025;18:1813–1825. doi:10.2147/JMDH.S516335

25. Cui L, Liu C, Yang L, et al. Association of remnant cholesterol with new-onset hypertension among middle-aged and older adults in China. Sci Rep. 2025;15(1):25296. doi:10.1038/s41598-025-09678-5

26. Xu X, Pan T, Zhong X, et al. Associations of the triglyceride-glucose index and remnant cholesterol levels with the prevalence of Carotid Plaque in patients with type 2 diabetes: a retrospective study. Lipids Health Dis. 2025;24(1):26. doi:10.1186/s12944-025-02449-1

27. Wang Y, Bi L, Li Q, et al. Remnant cholesterol inflammatory index and its association with all-cause and cause-specific mortality in middle-aged and elderly populations: evidence from US and Chinese national population surveys. Lipids Heal Dis. 2025;24(1). doi:10.1186/s12944-025-02580-z

28. Matsushima-Nagata K, Matsumura T, Kondo Y, et al. Significance of circulating remnant lipoprotein cholesterol levels measured by homogeneous assay in patients with type 2 diabetes. Biomolecules. 2023;13(3):468. doi:10.3390/biom13030468

29. Nordestgaard BG, Varbo A. Triglycerides and cardiovascular disease. Lancet. 2014;384:626–635. doi:10.1016/S0140-6736(14)61177-6

30. Varbo A, Nordestgaard BG. Directly measured vs. calculated remnant cholesterol identifies additional overlooked individuals in the general population at higher risk of myocardial infarction. Eur Heart J. 2021;42(47):4833–4843. doi:10.1093/eurheartj/ehab293

31. Li B, Liu Y, Zhou X, et al. Remnant cholesterol, but not other traditional lipids or lipid ratios, is independently and positively related to future diabetes risk in Chinese general population: a 3 year cohort study. J Diabetes Investig. 2024;15(8):1084–1093. doi:10.1111/jdi.14205

32. Yang L, Huang H, Wang Z, et al. Remnant cholesterol predicts the development of type 2 diabetes in patients with nonalcoholic fatty liver disease. Diabetol Metab Syndr. 2025;17(1). doi:10.1186/s13098-025-01828-z

33. Li X, Cui G, Wang X. A cross-sectional analysis of remnant cholesterol-diabetes association in US adults. Sci Rep. 2025;15(1):26572. doi:10.1038/s41598-025-10961-8

34. Fu L, Tai S, Sun J, et al. Remnant cholesterol and its visit-to-visit variability predict cardiovascular outcomes in patients with type 2 diabetes: findings from the ACCORD cohort. Diabetes Care. 2022;45(9):2136–2143. doi:10.2337/dc21-2511

35. Hu X, Liu Q, Guo X, et al. The role of remnant cholesterol beyond low-density lipoprotein cholesterol in diabetes mellitus. Cardiovasc Diabetol. 2022;21(1):117. doi:10.1186/s12933-022-01554-0

36. Liu R, Xu T, Gan L, et al. Influence of remnant cholesterol levels on carotid intima thickness in type 2 diabetes patients. Sci Rep. 2024;14(1):20893. doi:10.1038/s41598-024-71780-x

37. Song Y, Zhao Y, Bai X, et al. Remnant cholesterol is independently associated with an increased risk of peripheral artery disease in type 2 diabetic patients. Front Endocrinol. 2023;14:1111152. doi:10.3389/fendo.2023.1111152

38. Li Z, Yu C, Zhang H, et al. Impact of remnant cholesterol on short-term and long-term prognosis in patients with prediabetes or diabetes undergoing coronary artery bypass grafting: a large-scale cohort study. Cardiovasc Diabetol. 2025;24(1):8. doi:10.1186/s12933-024-02537-z

39. Chen J, Wu Q, Liu H, et al. Predictive value of remnant cholesterol inflammatory index for stroke risk: evidence from the China health and retirement longitudinal study. J Adv Res. 2025;76:543–552. doi:10.1016/j.jare.2024.12.015

40. Cao B, Li K, Ke J, et al. Trajectories of remnant cholesterol are associated with diabetic foot ulcer in adult patients with type 2 diabetes: a retrospective cohort study. Diabetes Metab Syndr Obes. 2024;17:3043–3051. doi:10.2147/DMSO.S461330

41. Roh E, Heo JH, Jung HN, et al. Impact of remnant cholesterol on the risk for end-stage renal disease in type 2 diabetes mellitus: a nationwide population-based cohort study. Diabetes Metab J. 2025;49(5):1106–1115. doi:10.4093/dmj.2024.0406

42. Zhao Y, Liu K, Zou Y, et al. Remnant cholesterol and the risk of diabetic nephropathy progression to end-stage kidney disease in patients with type 2 diabetes mellitus: a longitudinal cohort study. Endocrine. 2024;86(3):994–1002. doi:10.1007/s12020-024-03948-4

43. Pan W, Han Y, Hu H, et al. The non-linear link between remnant cholesterol and diabetic retinopathy: a cross-sectional study in patients with type 2 diabetic mellitus. BMC Endocr Disord. 2022;22(1):326. doi:10.1186/s12902-022-01239-5

44. Zhu W, Liu Q, Liu F, et al. High remnant cholesterol as a risk factor for developing chronic kidney disease in patients with prediabetes and type 2 diabetes: a cross-sectional study of a US population. Acta Diabetol. 2024;61(6):735–743. doi:10.1007/s00592-024-02249-6

45. Chen S, Xu Y, Chen B, et al. Remnant cholesterol is correlated with retinal vascular morphology and diabetic retinopathy in type 2 diabetes mellitus: a cross-sectional study. Lipids Health Dis. 2024;23(1):75. doi:10.1186/s12944-024-02064-6

46. Wei C, Huang Y, Xi P, et al. The non-linear association between remnant cholesterol/high-density lipoprotein cholesterol ratio and diabetic retinopathy: a cross-sectional study in type 2 diabetic patients. Diabetol Metab Syndr. 2025;17(1):172. doi:10.1186/s13098-025-01719-3

47. Ding Y, Wang L, Sun J, et al. Remnant cholesterol and dyslipidemia are risk factors for Guillain-Barré syndrome and severe Guillain-Barré syndrome by promoting monocyte activation. Front Immunol. 2022;13:946825. doi:10.3389/fimmu.2022.946825

48. Dai LR, Lyu L, Zhan WY, et al. Genetic evidence for causal effects of circulating remnant lipid profile on cerebral hemorrhage and ischemic stroke: a Mendelian randomization study. World Neurosurg. 2025;195:123649. doi:10.1016/j.wneu.2024.123649

49. Grego A, Fernandes C, Fonseca I, et al. Endothelial dysfunction in cardiovascular diseases: mechanisms and in vitro models. Mol Cell Biochem. 2025;480(8):4671–4695. doi:10.1007/s11010-025-05289-w

50. Shan Y, Wang Q, Zhang Y, et al. High remnant cholesterol level is relevant to diabetic retinopathy in type 2 diabetes mellitus. Lipids Health Dis. 2022;21(1):12. doi:10.1186/s12944-021-01621-7

51. Lee JH, Ahn SG, Jeon HS, et al. Remnant cholesterol as a residual risk in atherosclerotic cardiovascular disease patients under statin-based lipid-lowering therapy: a post hoc analysis of the RACING trial. J Clin Lipidol. 2024;18(6):e905–e914. doi:10.1016/j.jacl.2024.07.005

52. Balling M, Roepstorff OG, Gerds TA, et al. Risk reduction of ASCVD attributed to lowering of remnant cholesterol from statins, fibrates, APOC3 inhibitors, and ANGPTL3 inhibitors: a cohort study. Atherosclerosis. 2025;409:120471. doi:10.1016/j.atherosclerosis.2025.120471

53. Das Pradhan A, Glynn RJ, Fruchart JC, et al. Triglyceride lowering with pemafibrate to reduce cardiovascular risk. N Engl J Med. 2022;387(21):1923–1934. doi:10.1056/NEJMoa2210645

54. Song S, Lee CJ, Oh J, et al. Effect of niacin on carotid atherosclerosis in patients at low-density lipoprotein-cholesterol goal but high lipoprotein (a) level: a 2-year follow-up study. J Lipid Atheroscler. 2019;8(1):58–66. doi:10.12997/jla.2019.8.1.58

55. Chapman MJ, Zamorano JL, Parhofer KG. Reducing residual cardiovascular risk in Europe: therapeutic implications of European medicines agency approval of icosapent ethyl/eicosapentaenoic acid. Pharmacol Ther. 2022;237:108172. doi:10.1016/j.pharmthera.2022.108172

56. Kobayashi Y, Fujikawa T, Haruna A, et al. Omega-3 fatty acids reduce remnant-like lipoprotein cholesterol and improve the ankle-brachial index of hemodialysis patients with dyslipidemia: a pilot study. Medicina. 2023;60(1):75. doi:10.3390/medicina60010075

57. Li X, Li ZF, Wu NQ. Remnant cholesterol and residual risk of atherosclerotic cardiovascular disease. Rev Cardiovasc Med. 2025;26(2):25985. doi:10.31083/RCM25985

58. Bonilha I, Zimetti F, Zanotti I, et al. Dysfunctional high-density lipoproteins in type 2 diabetes mellitus: molecular mechanisms and therapeutic implications. J Clin Med. 2021;10(11):2233. doi:10.3390/jcm10112233

59. Wu Y, Wei Q, Li H, et al. Association of remnant cholesterol with hypertension, type 2 diabetes, and their coexistence: the mediating role of inflammation-related indicators. Lipids Health Dis. 2023;22(1):158. doi:10.1186/s12944-023-01915-y

60. Bornfeldt KE. The remnant lipoprotein hypothesis of diabetes-associated cardiovascular disease. Arterioscler Thromb Vasc Biol. 2022;42(7):819–830. doi:10.1161/ATVBAHA.122.317163

61. Li Q, Wang T, Shao X, et al. Association of remnant cholesterol with renal function and its progression in patients with type 2 diabetes related chronic kidney disease. Front Endocrinol. 2024;15:1331603. doi:10.3389/fendo.2024.1331603