Impact of Hyperlipidemia on Osseointegration and Peri-implant Diseases

Abstract

The long-term success of dental implants depends critically on osseointegration and peri-implant tissue health. While local factors have been extensively investigated, the influence of systemic metabolic disorders—particularly hyperlipidemia—on implant outcomes remains insufficiently understood. Hyperlipidemia is among the most common metabolic diseases globally and is increasingly recognized for its adverse effects on bone metabolism, immune response, and microcirculation. However, its role in osseointegration, which is responsible for peri-implant bone healing and the development of peri-implant diseases, is still controversial and lacks systematic evaluation. Based on our summary of the latest literature, the process of osseointegration can be summarized as angiogenesis-mediated 5-phase osseointegration. The 5 phases refer to 1) hydration/protein adsorption, 2) platelet-mediated fibrin clot formation, 3) immune cell adhesion, 4) osteogenic–bacterial competitive adhesion, and 5) angiogenesis–osteogenesis coupling. Angiogenesis-mediated 5-phase osseointegration facilitates a dynamic perspective for understanding the physiological processes involved in osseointegration. This review comprehensively summarizes clinical and experimental studies on the relationship between hyperlipidemia and osseointegration. The analysis focuses on peri-implant bone healing and peri-implant disease development from the perspective of angiogenesis-mediated 5-phase osseointegration. To our knowledge, this review creatively integrates both clinical and experimental evidence regarding the impact of hyperlipidemia on peri-implant bone healing and complications.

Keywords

dental implants hyperlipidemias hypercholesterolemia peri-implantitis osseointegration angiogenesis

Introduction

Dental implants, with notable advantages in stability and aesthetics, have been increasingly used to restore missing teeth and have received widespread favor among partially or fully edentulous patients. Osseointegration is the critical biological process for stable fixation between implants and bone and is considered the basis of long-term success (Albrektsson and Wennerberg 2019). However, local plaque-induced inflammations affecting soft and bone tissues around implants, referred to as “peri-implant mucositis” and “peri-implantitis,” are the most common complications of dental implants (Ivanovski et al 2022). The marginal bone loss (MBL) caused by peri-implantitis poses a major threat to the implants’ functional survival, even in cases of initial good osseointegration (Figuero et al 2014).

Recently, studies have concluded that peri-implantitis is more likely to occur under conditions such as poor oral hygiene, lack of regular maintenance of implants, smoking, and the presence of systemic diseases (Wada et al 2021). A growing number of studies have concentrated on and indicated the association between systemic conditions with peri-implant diseases and dental implant failure, such as cardiovascular disease (CVD) (Ustaoğlu and Erdal 2020; Hofer et al 2024) and diabetes (Nibali et al 2022). Awareness of such systemic risk factors could help dentists better identify and monitor the high-risk population, as well as develop early interventions during healing and maintenance after implantation. Hyperlipidemia refers to a set of acquired or genetic serum lipid disorders, characterized by abnormally elevated levels of total cholesterol (TC), triglycerides (TGs), and/or low-density lipoprotein (LDL) and a decreased level of high-density lipoprotein (HDL) (Liang et al 2025). The global prevalence of high total cholesterol in adults (≥5.0 mmol/L; ≥190 mg/dL) was approximately 40% (Mattiuzzi et al 2020). Previous studies have shown a certain correlation between hyperlipidemia and periodontitis (Xu and Duan 2020). Thus, hyperlipidemia is not uncommon in patients receiving dental implant treatment. Hyperlipidemia disrupts systemic homeostasis, affecting bone metabolism and immune response. While its association with periodontal diseases is well documented, its role as a systemic risk factor for peri-implant disorders remains controversial.

Based on current evidence, the process of osseointegration can be summarized as angiogenesis-mediated 5-phase osseointegration. The 5 phases refer to the following:

Hydration and protein adsorption: Within mere nanoseconds after implant placement, water molecules rapidly adsorb onto the implant surface (Wu et al 2022), creating favorable conditions for subsequent protein adsorption. This leads to the formation of a “protein layer” (Ngandu Mpoyi et al 2016), which facilitates platelet adhesion and initiates subsequent biological processes.

Platelet-mediated fibrin clot formation: Within minutes to hours postimplantation, platelets adhere to the implant surface and form fibrin clots, releasing growth factors that promote the migration of immune cells to the implant interface (Ivanovski et al 2025).

Immune cell adhesion: Over hours to days following implantation, immune cells (including macrophages and neutrophils) migrate and adhere to the surface, releasing cytokines that recruit osteogenic-related cells (Zhu et al 2021).

Osteogenic–bacterial competitive adhesion: Osteogenic-related cells, including osteoblasts and bone marrow–derived mesenchymal stem cells, migrate to the implant surface and compete with bacteria for adhesion sites, a process described by the “surface competition” theory (Gristina 1987; Covato et al 2025).

Angiogenesis–osteogenesis coupling: Following the adhesion of osteogenic-related cells, these cells undergo differentiation, secrete osteoid matrix, and contribute to the formation of new bone (Mahon et al 2020). Concurrently, they establish coupling with angiogenesis by secreting signaling molecules such as vascular endothelial growth factor (VEGF) (Burger et al 2022).

Angiogenesis permeates throughout the entire process: Angiogenesis plays a pivotal role throughout the osseointegration process. In the early stages, endothelial cells proliferate, sprout, and form tubular structures, supporting the migration and recruitment of immune cells (Šalandová et al 2021). In the intermediate stages, the establishment of vascular networks facilitates material transport (Šalandová et al 2021). In the later stages, the maturation and stabilization of vascular networks provide the foundation for tissue remodeling and circulation (Liu et al 2025).

Disruption of any single stage may lead to implant osseointegration failure or the development of peri-implant diseases. Hyperlipidemia, as a systemic metabolic disorder, can infiltrate and compromise each stage of implant osseointegration through multiple mechanisms, thereby increasing the risk of implant failure. Nevertheless, targeted interventions addressing these 5 critical stages in hyperlipidemic patients may significantly improve implant success rates. Therefore, this comprehensive review systematically analyzes published clinical and experimental studies to elucidate the biological associations between hyperlipidemia and osseointegration, as well as peri-implant diseases, within the 5-phase osseointegration framework. We aim to summarize the pathophysiology and provide evidence-based guidance on osseointegration in hyperlipidemic patients.

Effects of Hyperlipidemia on Osseointegration

As the initial hydration/protein adsorption phase is brief (lasting only nanoseconds), the following sections focus on the remaining 4 critical stages of osseointegration.

Effects of Hyperlipidemia on Platelet Function

Platelets play a crucial role in the osseointegration process of dental implants. Under normal conditions, platelets release key growth factors, such as bone morphogenetic protein 2 (BMP-2), platelet-derived growth factor–BB (PDGF-BB), and VEGF, and form a 3-dimensional fibrin network that promotes cell adhesion, migration, and proliferation, thereby potentially supporting early osseointegration events (Ivanovski et al 2025).

However, the diminished blood wettability induced by hyperlipidemia may compromise the pivotal role of platelets in the osseointegration process. Koca et al (2020) demonstrated in a hyperlipidemic rabbit model that hyperlipidemia was associated with surface-dependent changes in blood wettability. Higher contact angle values were observed during the hyperlipidemic period on certain surface types, indicating altered wetting behavior under specific conditions. Although the impact of hyperlipidemia and its treatment appears relatively limited on implants subjected to specialized metal alloy treatments or gas-phase chemical modifications, its effects remain pronounced on clinically prevalent surfaces. This phenomenon may be attributed to elevated levels of lipid components (TC and TGs) in the blood, with particularly pronounced effects observed on grade 4 machined surfaces and grade 4 sandblasted, large-grit, acid-etched (SLA) surfaces (Koca et al 2020).

Since machined and SLA surfaces remain the clinically dominant surfaces for most contemporary implant systems, these findings are of significant clinical relevance, suggesting that elevated systemic lipids may potentially interfere with early events such as platelet adhesion and the recruitment of cellular aggregates. The reduction in blood wettability may further compromise platelet adhesion, activation, and their capacity to recruit other cellular aggregates.

Hyperlipidemia as a Promoter of Inflammation

Studies have shown that lipid metabolism can regulate the polarization state of macrophages through NF-κB and further affect immune homeostasis, which is disrupted under conditions of hyperlipidemia (Wang et al 2025a). On the other hand, hyperlipidemia disrupts inflammatory homeostasis through dual interconnected lipid-mediated pathways. The oxidation of LDL is a key trigger of inflammation. Oxidized LDL (oxLDL) activates macrophages and dendritic cells, and it interacts with gingival epithelial cells to induce local inflammation (Suzuki et al 2010). Meanwhile, dendritic cells present oxLDL antigens, thereby activating a specific immune response (Thangasparan et al 2024). Furthermore, triglyceride-rich lipoproteins (TRLs) amplify this inflammatory process by promoting the secretion of adhesion molecules and inflammatory factors (Norata et al 2007). Collectively, these lipid-mediated inflammatory pathways can contribute to the recruitment of inflammatory cells and the establishment of a proinflammatory microenvironment.

Recent mechanistic studies have elucidated that disrupted cholesterol homeostasis triggers periodontal inflammation through C-X-C motif chemokine ligand 16 (CXCL16)–mediated cholesterol influx, 25-hydroxycholesterol metabolite accumulation, and retinoic acid receptor–related orphan receptor α (RORα) activation pathways (Tran et al 2023). The study of this mechanism reveals the impact of the sustained proinflammatory state induced by hyperlipidemia on bone resorption at the cellular level.

The inflammatory environment associated with hyperlipidemia may interfere with immune cell recruitment and polarization during the early postimplantation period, potentially altering the balance between osteogenic cell adhesion and bacterial colonization at the implant surface.

Inhibitory Effects of Hyperlipidemia on Osteogenesis

The detrimental effects of hyperlipidemia on osteogenesis have been validated by various clinical observations and animal experiments. Nonetheless, the related mechanisms still need further exploration.

The impact of hyperlipidemia on osseointegration in clinical studies

Current clinical research illustrated a complex and sometimes inconsistent picture. A cross-sectional study (Carlos et al 2024) showed that MBL around dental implants was closely associated with hyperlipidemia, with the effect being more pronounced when combined with other systemic diseases. Conversely, in contrast to this study (57 patients, 165 implants), several other cross-sectional clinical studies in implant dentistry typically involved substantially larger sample sizes (Aljalloud et al 2023 [142 patients with 380 dental implants]; Baima et al 2025 [146 patients with 511 dental implants]; Sun et al 2025 [732 patients with 1,873 dental implants]). In addition, the systemic disease definitions in the inclusion criteria were vague, which relied on medical records rather than standardized diagnostic thresholds. Future studies could provide clearer explanations of radiograph timing, which would enhance the robustness of their conclusions. Another prospective study (Grigoras, et al 2025) presented different findings. The study found no significant correlation between early implant failure and blood lipid indicators, including LDL, HDL, TGs, and cholesterol. The authors acknowledged several limitations, including the small sample size and the relatively short follow-up period.

Overall, clinical studies have suggested a possible link between hyperlipidemia and peri-implant bone changes, but neither can strongly prove nor deny the potential association between MBL around dental implants and hyperlipidemia. The main common issues in existing clinical studies were the reliance on a single data source, insufficient control of confounding factors, and a lack of long-term observation. These concerns about implant conditions in clinical studies have also been noted in recent reviews. Kupka et al (2024) stressed the need for long-term observation, while Monje and Salvi (2024) pointed out the heterogeneity of diagnostic approaches and the limited control of confounders.

The effect of hyperlipidemia on osseointegration in animal models

Recent experimental studies have provided important insights into how hyperlipidemia may affect osseointegration at the cellular and molecular levels (Table 1). The studies that used high-fat diet–induced mice compared the bone-to-implant contact rate (BIC), bone volume fraction (BV/TV), related proteins, and so on between the experimental groups and the control groups (Mu et al 2023; Wang and Liu 2025; Wang et al. 2025b). They all reached a consistent conclusion that hyperlipidemia significantly inhibited osteogenesis. There were several limitations in these studies. First, the model selection was singular. Most studies used femoral implant models, but the bone metabolism characteristics of the jawbone differ significantly from those of long bones (López 2024). While hyperlipidemia exerts a consistent systemic influence via circulation, localized responses during osseointegration vary significantly due to distinct embryological origins (López 2024). Consequently, evidence from femoral models requires cautious extrapolation, as differing ossification patterns and metabolic turnover rates may modulate the local impact of lipid dysregulation. Second, some studies used only male mice to avoid the effects of the female reproductive cycle on bone metabolism, but this also meant that the conclusions may not be applicable to females (Kurapaty and Hsu 2022). Moreover, the experimental periods were generally short. The observation period after implant placement did not exceed 8 wk, making it impossible to assess the long-term stability of osseointegration.

Table 1.

Summary of Animal Experimental Studies on the Effects of Hyperlipidemia on Osseointegration.

Author	Type	Model	Results	Innovation Points	Critical Review	Completeness Score^a
Öztürk et al (2023)	Experimental study	Animal: rabbits (male) Induction: 8-wk high-fat diet (HFD) presurgery Graft: bovine xenogeneic bone Site: mandibular corpus, the level of the corpus at the alignment of the first and second molar teeth	The atorvastatin group showed significantly greater new bone area and alkaline phosphatase intensities compared to the control group, whereas the control group exhibited higher tartrate-resistant acid phosphatase intensities than the atorvastatin group.	• Showed systemic atorvastatin can promote bone regeneration under hyperlipidemic conditions.	• Model relied on xenografts rather than titanium implants, limiting relevance. • Normolipidemic controls were absent and observation time was short.	12/18
Wang et al (2023)	Experimental study	Animal: C57BL/6J mice, apolipoprotein E knockout (ApoE^−/−) mice (male) Implant: Ti Site: femur, the distal end	ApoE deficiency significantly impaired bone formation around titanium implants. ApoE3 significantly enhanced titanium implant osseointegration in ApoE^−/− mice and shifted bone marrow mesenchymal stem cells (BMSCs) toward osteogenesis while suppressing lipogenesis on titanium surfaces.	• Demonstrated ApoE3 as a key regulator of osteogenesis–lipogenesis balance, enhancing implant osseointegration.	• Effects of ApoE deficiency could not be fully separated from hyperlipidemia. • The downstream signaling pathways mediating ApoE’s regulation of osteogenesis–lipogenesis balance remain insufficiently defined.	11/18
Wang et al (2025b)	Experimental study	Animal: mice (male) Induction: 4-wk HFD presurgery Implant: Ti Site: femur, the distal end	ALDH6A1 played a crucial role in promoting osseointegration by reducing reactive oxygen species (ROS) levels in individuals with hyperlipidemia. Creating specific ALDH6A1 activators could be an effective approach to improve osseointegration in patients with hyperlipidemia.	• Proposed ALDH6A1 as a novel therapeutic target for improving osseointegration in hyperlipidemic conditions.	• ALDH6A1 downregulation was linked to impaired osseointegration, but the causes of this reduction and its role in lipid metabolism remain unresolved.	11/18
Wang and Liu (2025)	Experimental study	Animal: mice (male) Induction: 1-mo HFD presurgery Implant: Ti Site: femur, the distal end	Hyperlipidemia induced oxidative stress through lipid droplet accumulation. It inhibited osteogenesis (ROS/Wnt/β-catenin signaling pathway) and activated osteoclasts (ROS/RANKL/NF-κB pathway), severely impairing the osseointegration of titanium implants. Although N-acetyl-L-cysteine (NAC) can alleviate oxidative damage and partially restore osseointegration, it cannot reduce the lipid droplets themselves.	• Highlighted lipid droplet accumulation as a key driver of poor osseointegration, suggesting reduction as a therapeutic strategy.	• Although NAC reduced oxidative stress, lipid droplet accumulation persisted, and the specific droplet subtypes involved remain undefined.	11/18
Mu et al (2023)	Experimental study	Animal: rats (male), nude mice (female) Induction: 8-wk HFD presurgery Implant: Ti Site: femur, the distal end	Overexpression of VPS26 significantly enhanced the osteogenic activity of BMSCs in a high-fat environment while inhibiting their adipogenic differentiation and reducing lipid droplet formation. Mechanistically, VPS26 interacted with β-catenin to activate the Wnt/β-catenin signaling pathway, thereby promoting implant osseointegration in HFD rats and ectopic bone formation in nude mice.	• Identified VPS26 as a regulator of implant osseointegration through Wnt/β-catenin signaling.	• The study confirmed VPS26 interaction with β-catenin, but the precise molecular mechanisms and additional contributing factors remain unclear.	11/18

The checklist is based on the “Essential 10” items of the ARRIVE guidelines 2.0.

Completeness score: Calculated as the number of “YES” items divided by the total number of applicable items for each study.

The above evidence has indicated that hyperlipidemia might weaken early osseointegration by inhibiting osteogenic activity. Also, the decline in bone quality caused by hyperlipidemia may affect the initial stability of implants. Common methodological limitations in these studies limit their clinical relevance. Future research needs jaw-specific, long-term, and more diverse experimental models to provide clearer insights.

The underlying molecular mechanisms of hyperlipidemia affecting osseointegration

Current research into the molecular mechanisms linking systemic lipid metabolism to peri-implant osseointegration focuses primarily on the disruption of osteogenic differentiation and the resulting imbalance in the local physiological environment. Central to this discussion is the fate of bone marrow mesenchymal stem cells (BMSCs). Research by Mu et al (2023) suggests that hyperlipidemia may suppress VPS26 expression, a key regulator in cargo sorting, thereby tilting the differentiation potential of BMSCs toward adipocytes at the expense of osteoblasts. This shift is further supported by observations in apolipoprotein E-deficient models, where a preferential differentiation into peri-implant adipocytic tissue has been noted (Wang et al 2023).

Beyond osteogenic differentiation, the local biochemical environment appears compromised by lipid-induced metabolic stress. Wang et al (2021) demonstrated that hyperlipidemia increases oxidative stress by downregulating ALDH6A1, with elevated reactive oxygen species (ROS) levels subsequently inhibiting osteoblast activity and impairing implant osseointegration. A later study (Wang et al 2026) directly proved that hyperlipidemia can downregulate ALDH6A1, thereby inhibiting the osteogenic activity of osteoblasts. After restoring ALDH6A1, the osteogenic activity of osteoblasts is effectively restored, providing a stronger theoretical basis for the direct regulation of implant osseointegration by hyperlipidemia.

While these findings begin to bridge the gap between systemic dysregulation and local healing, further studies are required to consolidate these molecular events into a definitive clinical model for peri-implant success.

Statin therapy: dual effects on osseointegration

Statins exhibit complex, dose-dependent effects on osseointegration in hyperlipidemic patients. Experimental evidence demonstrates beneficial effects: atorvastatin improved bone regeneration in hyperlipidemic rabbits by inhibiting osteoclast activity and promoting osteogenesis (Öztürk et al 2023), while simvastatin enhanced new bone formation (Inbarajan et al 2024). At low doses, statins promote angiogenesis–osteogenesis coupling, potentially restoring impaired microcirculation in hyperlipidemic conditions (Li et al 2023). However, clinical studies suggest potential risks, with some evidence linking statin use to peri-implant bone loss (Bahrami-Hessari and Jansson 2022).

These contradictory findings can be reconciled by considering the gap between preclinical models and clinical practice. While animal studies provide strong mechanistic evidence for statins’ osteogenic potential, they often utilize controlled environments that do not account for the chronic systemic inflammation and polypharmacy present in human patients. Currently, preclinical evidence for bone-promoting effects is robust, but clinical evidence remains observational and less conclusive.

Furthermore, it is essential to distinguish between systemic and local effects. Systemic statin therapy primarily aims at lipid reduction, where bone-related outcomes are often secondary and subject to dose-dependent systemic toxicity. In contrast, local delivery systems—such as statin-loaded coatings or scaffolds—have shown more consistent success in promoting osseointegration by concentrating the drug at the bone–implant interface, thereby avoiding the pitfalls of high-dose systemic administration. These findings suggest that future research should focus on determining optimal dosing protocols and identifying patient subgroups most likely to benefit from statin therapy during implant treatment.

Hyperlipidemia-Induced Impairment of Microcirculation and Angiogenesis

Recent studies suggest that hyperlipidemia may compromise peri-implant tissue stability and increase implant complications, as evidenced by observational and longitudinal investigations. In Galos’s report, uncontrolled LDL cholesterol (LDL-C) and TG levels significantly increased plasma and whole-blood viscosity in high-risk cardiovascular patients while reducing erythrocyte deformability, leading to inadequate microvascular perfusion (Galos et al 2024). Using nailfold capillaroscopy, Martino et al (2023) also demonstrated early capillary abnormalities in children with heterozygous familial hypercholesterolemia (HeFH), including reduced density, slowed blood flow, and the sludge phenomenon. These findings suggested that hypercholesterolemia may contribute to early microvascular impairment.

While valuable in identifying associations, they had limitations in inferring causality due to the study design of cross-sectional studies. In addition, as noted in their studies, sample sizes were relatively small, indicating the need for cautious interpretation and validation in larger populations. In addition, most studies have primarily focused on cardiovascular or systemic circulation, whereas evidence directly addressing the bone defect microenvironment remains scarce.

A view is that hyperlipidemia might suppress angiogenesis under various physiological conditions. This conclusion is supported by several mechanistic studies (Bogachkov et al 2020; Mo et al 2023). Elevated LDL levels increased cholesterol loading in endothelial cell membranes and reduced responsiveness to VEGF and other growth factors, resulting in impaired angiogenesis during wound healing and ischemia (Bogachkov et al 2020). Moreover, dysfunctional HDL (dHDL) failed to effectively degrade the inhibitory long noncoding RNA high-density lipoprotein-regulated angiogenesis in coronary artery disease (HDRACA), leading to decreased expression of proliferating cell nuclear antigen (PCNA) and subsequent suppression of endothelial proliferation and vessel formation (Mo et al 2023). Given the large body of research on cellular mechanisms, only selected representative studies are cited here.

It should be noted that hyperlipidemia may promote angiogenesis in tumor, chronic inflammatory, and other pathological settings (Xiao et al 2023). Intervention with agents such as the traditional Chinese medicine formula Yinlan Tiaozhi Capsule improved lipid and inflammatory profiles and downregulated the expression of vascular endothelial growth factor A (VEGFA). This suggests that hyperlipidemia itself may be associated with excessive or abnormal angiogenic signaling, while pharmacological treatment restores normal angiogenesis by rebalancing metabolism and inflammation (Xiao et al 2023). These differences suggest that hyperlipidemia is not a unidirectional regulator but exerts environment-dependent effects.

Nonetheless, there are several limitations. First, there is a scarcity of research directly addressing bone defect repair or implant osseointegration. Moreover, most existing studies have focused primarily on angiogenesis markers like VEGF, rather than systematically investigating how hyperlipidemia modulates angiogenesis via immune–metabolic interactions across diverse microenvironments.

Angiogenesis–osteogenesis coupling is considered central to bone regeneration. Blood vessels not only deliver oxygen and nutrients to bone tissue but also secrete angiocrine factors that directly regulate osteoblast differentiation and activity. A recent study summarized that bone-related cells and endothelial cells communicated through multiple mechanisms, including paracrine signaling, extracellular vesicles, and intercellular junctions, thereby coordinating angiogenesis and osteogenesis (Li et al 2025). Furthermore, VEGF regulated this coupling in a dose-dependent manner: low levels promoted vascular invasion and osteogenic differentiation, whereas excessive levels may disrupt remodeling and favor bone resorption (Grosso et al 2023). Collectively, these findings underscored that coordinated angiogenesis and osteogenesis were prerequisites for high-quality bone repair and osseointegration. On the other hand, direct studies on how hyperlipidemia influences this coupling remain scarce, particularly in the context of bone defects and implant integration.

Future studies should prioritize elucidating the underlying mechanisms by which hyperlipidemia might disrupt the angiogenic–osteogenic coupling in the context of bone defect repair and implant osseointegration. Such insights will be instrumental in developing precise therapeutic strategies to mitigate these adverse effects and improve clinical outcomes for hyperlipidemic patients undergoing bone regeneration or implantation.

Peri-implant Disease in Hyperlipidemia

Over the past years, research has increasingly highlighted the potential link between hyperlipidemia and peri-implant outcomes, moving beyond isolated clinical observations toward more structured epidemiological evidence. Both observational and longitudinal investigations have explored this relationship, indicating that altered lipid metabolism may compromise peri-implant tissue stability and increase the risk of implant complications.

Regarding peri-implant diseases, several investigations have suggested that elevated serum levels of TC, LDL-C, and TG, in combination with the presence of metabolic syndrome (MetS), could be associated with an increased risk of peri-implantitis and peri-implant mucositis (Papi et al 2019; Ustaoğlu and Erdal 2020; Blanco et al 2021). Table 2 summarizes the key clinical studies examining the relationship between hyperlipidemia and peri-implant disease. In terms of implant failure, retrospective analyses indicated that hypercholesterolemia, particularly TC >200 mg/dL, might be linked to a higher likelihood of implant or graft failure (Tirone et al 2016). The above studies have proved that hyperlipidemia is associated with peri-implant diseases, but not all studies show a significant relation. Conversely, prospective cohort studies conducted under standardized surgical and follow-up protocols have not consistently demonstrated a significant association between lipid profiles and short-term implant failure rates (Marchio et al 2020). The reasons for the above differences may be related to changes in study design, diagnostic criteria, follow-up time, or population characteristics. Therefore, this potential link needs to be further clarified through high-quality prospective studies.

Table 2.

Summary of Clinical Studies on the Association between Hyperlipidemia and Peri-implant Disease.

Author	Type	Model	Results	Innovation Points	Critical Review	Methodological Quality^a
Blanco et al (2021)	Clinical study (cross-sectional study)	47 patients, 56 implants; groups defined by 2018 consensus; PI: 16/20, health: 31/36; cross-sectional; no follow-up; single-center (dental school clinic 2018–2019, university hospital 2016–2017)	Peri-implantitis vs. health: higher TC, higher LDL-C, higher WBC, and lower IL-10. Secondary: PPD positively correlated with TC, LDL-C, and WBC and negatively with IL-10; BOP showed similar associations.	• Combined lipid profiles with systemic inflammatory markers to explore the “lipid–inflammation–peri-implant” relationship. • Adopted consensus-based diagnostic criteria to ensure a standardized classification.	• Hyperlipidemia was not explicitly defined. • Case and control groups were recruited in different settings and time frames, potentially introducing bias.	8/8
Ustaoğlu and Erdal (2020)	Clinical study (cross-sectional study)	156 patients, 196 implants; groups per 2017 World Workshop (PI, mucositis, health); PI: 58/81, mucositis: 49/55, health: 49/60; cross-sectional; no follow-up; single-center (Bolu Abant Izzet Baysal University)	Primary: across peri-implantitis, mucositis, health: peri-implantitis group had higher TG, higher uric acid, lower vitamin D, and higher WBC. LDL-C, HDL-C, and TC did not differ. Secondary: TG positively correlated with GI, PD, and BOP and inversely with KMW. Uric acid positively correlated with GI, PD, and BOP and inversely with KMW. Vitamin D negatively correlated with GI.	• Integrated TG, uric acid, vitamin D, and CBC measurements with peri-implant indices (PD, GI, BOP, KMW). • Diagnosis was based on the 2017 World Workshop criteria.	• Hyperlipidemia was not clearly defined and lipid thresholds were not specified.	7/8
Papi et al (2019)	Clinical study (cross-sectional study)	183 patients, 567 implants; groups by systemic status (MetS vs. non-MetS, NCEP ATP III) and peri-implant disease (2017 World Workshop); MetS 45.9%, non-MetS 54.1%; cross-sectional; no follow-up; multiorigin implants, examined at Sapienza University of Rome	Primary: MetS vs. non-MetS: peri-implantitis prevalence 36.9% vs. 26.3%, mucositis 60.7% vs. 55.5%. MetS associated with peri-implantitis and mucositis. Secondary: Periodontitis history associated with peri-implantitis and mucositis.	• Investigated the association between metabolic syndrome (NCEP ATP III) and peri-implant diseases. • Both MetS and peri-implant disease diagnoses were clearly defined. • Enrolled a relatively large cohort with implants in function ≥5 y.	• Rules for merging implant-level outcomes within the same patient were not specified. • The composite nature of MetS may obscure the independent contribution of hyperlipidemia. • Lack of baseline data: Without standardized X-rays taken when the implant was restored, bone loss may be overestimated.	8/8
Grigoraș et al (2025)	Clinical study (prospective observational study)	166 patients, 556 implants; stratified by lipid profile (LDL, HDL, TG) and vitamin D (normal, borderline, high risk); not comparative arms; prospective; follow-up at 14–21 d, 6 and 12 mo; single-center (private clinic, Târgu Mureș, Romania).	Primary: 166 patients, 556 implants; failures at 14–21 d (2.34%), 6 mo (0.35%), and 12 m (1.44%). At 12 mo, no significant correlation between implant failure and LDL-C, HDL-C, TC, TG, or vitamin D. Secondary: Survival rates stratified by lipid/vitamin D categories did not differ significantly across 14–21 d, 6 mo, or 12 mo.	• Preoperative laboratory testing (within 7 d) included LDL, HDL, TC, TG, and vitamin D. • Detailed follow-up schedule at multiple time points.	• LDL “normal” cutoff (150 mg/dL) exceeded guideline-based ranges, potentially underestimating moderate risk. • Assessment of peri-implant disease lacked radiographic and probing-based criteria. • Failure definitions were not fully aligned with Albrektsson or ICOI multidimensional standards.	7/8
Marchio et al (2020)	Clinical study (prospective observational study)	72 patients, 72 implants (1 each); groups: 36 healthy vs. 36 medically compromised (CVD, diabetes, hypercholesterolemia, depression, GI diseases, asthma, osteoporosis, glaucoma); prospective; 1-y follow-up; single-center (University Hospital of Pisa, with 1 private practitioner).	Primary: Healthy vs. medically compromised (36 vs. 36): at 1 y, implant success 91.7% vs. 94.4%, survival 94.4% vs. 94.5%, MBL 0.4 ± 0.6 mm vs. 0.5 ± 0.6 mm. Secondary: Keratinized tissue width decreased in healthy people but increased in compromised patients.	• Compared healthy and medically compromised patients under the same implant protocol. • Incorporated soft-tissue and aesthetic indices, reporting differences in keratinized mucosa and papilla level.	• Medically compromised patients were grouped as a whole, without stratification by specific conditions such as hyperlipidemia.	8/9

BOP, bleeding on probing; CBC, complete blood count; CVD, cardiovascular disease; GI, gastrointestinal; HDL, high-density lipoprotein; ICOI, international congress of oral implantologists; KMW, Kruskal-Wallis test; MetS, metabolic syndrome; LDL, low-density lipoprotein; LDL-C, low-density lipoprotein cholesterol; MBL, marginal bone loss; NCEP ATP III, national cholesterol education program adult treatment panel III; PD, probing depth; PI, plaque index; PPD, probing pocket depth; TC, total cholesterol; WBC, white blood cell.

Methodological quality: Scores are calculated as the ratio of criteria met (or stars awarded) to the total number of applicable items. The JBI checklist was used for cross-sectional studies and the Newcastle-Ottawa Scale (NOS) for prospective/cohort studies.

Despite these emerging findings, several methodological limitations warrant careful consideration. Definitions and diagnostic thresholds for hyperlipidemia varied considerably across studies, with most relying on dichotomous classifications (presence vs. absence) rather than exploring dose–response relationships. Differences in lipid measurement protocols and analytical approaches likely contributed to the heterogeneity of findings. Regarding outcome assessment, although many studies referred to established criteria for peri-implant diseases and implant survival, inconsistencies persisted. For instance, peri-implant mucositis was not consistently defined (Blanco et al 2021), and investigations of implant failure primarily focused on early events, with follow-up durations rarely exceeding 1 y. This lack of long-term observation limits the evaluation of outcomes beyond 3 to 5 y, a period generally considered necessary to capture late failures. Grigoras, et al (2025) provided a broader framework by analyzing both implant loss and peri-implant disease, yet radiographic parameters were not fully incorporated, potentially limiting the robustness of the diagnoses.

Sample size and statistical power constitute additional limitations. Studies on peri-implant diseases rarely report formal sample size calculations. Ustaoğlu and Erdal (2020) acknowledged this issue. In contrast, in the aforementioned study, the relatively low incidence of implant failure limited the stability of the regression models. Although some studies adjusted for confounders such as history of periodontitis, smoking, glycemic control, and operator or examiner effects, residual confounding likely persisted. Important factors, including systemic metabolic conditions, medication use, and clustering at the patient–implant level, were often insufficiently accounted for (Papi et al 2019; Ustaoğlu and Erdal 2020; Blanco et al 2021). These methodological issues may have undermined the reliability of the effect estimates. Currently, there is no universally accepted threshold for lipid levels (e.g., LDL, HDL, or TGs) that serves as a contraindication for dental implant surgery. In the absence of dental-specific guidelines, we recommend using systemic health markers as a proxy. Patients with “very high” cardiovascular risk (e.g., LDL-C >190 mg/dL or persistently high TGs >200 mg/dL) (Mach et al 2020) should be considered at potentially higher risk for impaired bone healing. For these patients, we suggest preoperative consultation with the patient’s physician to ensure lipid levels are managed.

Future investigations should ideally be conducted as multicenter prospective cohort studies with adequate sample sizes and extended follow-up periods. The adoption of comprehensive and multidimensional outcome measures will be essential to elucidate the independent impact of hyperlipidemia on long-term implant prognosis and to generate stronger evidence for clinical risk stratification and tailored intervention strategies.

Conclusion and Prospects

Hyperlipidemia may represent a previously overlooked yet systemic risk factor that affects postimplant tissue healing and long-term outcomes. It can directly or indirectly disrupt the angiogenesis-mediated 5-phase osseointegration process, potentially leading to implant failure (Fig.). However, most existing studies have failed to comprehensively investigate this multilevel mechanistic influence, often resorting to simplistic correlational analyses without uncovering the underlying pathophysiological pathways. Furthermore, some experiments suffer from significant design limitations, such as insufficient sample sizes, short follow-up periods, simplistic methods for evaluating osseointegration, and inadequate control of confounding biases. These issues collectively undermine the reliability and generalizability of research findings.

Figure.

Schematic illustration of the mechanisms by which hyperlipidemia affects osseointegration and peri-implant complications.

Future studies should place greater emphasis on integrating mechanistic exploration with clinical translation. For example, multiomics technologies could be employed to analyze the immune-metabolic crosstalk within the bone microenvironment under hyperlipidemic conditions, or animal models could be established to simulate the effects of dyslipidemia on peri-implant healing in clinically relevant settings. Building on this knowledge, the development of personalized treatment strategies for hyperlipidemic patients—such as preoperative lipid management, local drug delivery systems, or bioactive-coated implants—may significantly improve therapeutic success rates. Therefore, elucidating the specific mechanisms through which hyperlipidemia influences implant outcomes will not only aid in identifying high-risk populations and optimizing perioperative management but also provide a new theoretical foundation and clinical pathway for enhancing long-term implant efficacy.

Author Contributions

R. Mai, X. Li, contributed to conception and design, data acquisition and interpretation, drafted and critically revised the manuscript; X. Yang, O. Hu, J. Zhang, contributed to interpretation, drafted the manuscript; S.W. Cheung, Y.Tang, S. Feng, contributed to design, data acquisition and analysis, critically revised the manuscript; L. Huang, contributed to conception and design, critically revised manuscript; J. Wang, Y. Wu, contributed to design, critically revised the manuscript; Y. Man, contributed to conception and design, critically revised the manuscript; L. Xiang, contributed to conception and design, data interpretation, critically revised the manuscript. All authors have their final approval and agree to be accountable for all aspects of work.

Supplemental Material

sj-docx-1-jdr-10.1177_00220345261442179 – Supplemental material for Impact of Hyperlipidemia on Osseointegration and Peri-implant Diseases

Supplemental material, sj-docx-1-jdr-10.1177_00220345261442179 for Impact of Hyperlipidemia on Osseointegration and Peri-implant Diseases by R. Mai, X. Li, X. Yang, O. Hu, J. Zhang, S.W. Cheung, Y. Tang, S. Feng, L. Huang, J. Wang, Y. Wu, Y. Man and L. Xiang in Journal of Dental Research

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by grants from the National Natural Science Foundation of China (Nos. 82571134, 82370996, and 82170997) and the Sichuan Science and Technology Program (No. 2024NSFSC0537).

ORCID iDs

R. Mai

X. Li

X. Yang

O. Hu

J. Zhang

S.W. Cheung

Y. Tang

S. Feng

L. Huang

J. Wang

Y. Wu

Y. Man

L. Xiang

Data Availability

Data availability is not applicable to this article as no new data were created or analyzed in this study.

A supplemental appendix to this article is available online.

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