Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease
Abstract This study aimed to determine whether remnant cholesterol (RC) and its variability can predict the onset of metabolic dysfunction-associated steatotic liver disease (MASLD) independently of low-density lipoprotein cholesterol (LDL-C) levels. A longitudinal cohort study involving 43,065 part...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-88000-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823862509310836736 |
|---|---|
| author | Yuting Sun Xinlei Miao Manling Hu Xiaoling Xie Shuang Liu Ziping Song Jiayi Deng Fei Xu Meng Li Yangxuan He Song Leng |
| author_facet | Yuting Sun Xinlei Miao Manling Hu Xiaoling Xie Shuang Liu Ziping Song Jiayi Deng Fei Xu Meng Li Yangxuan He Song Leng |
| author_sort | Yuting Sun |
| collection | DOAJ |
| description | Abstract This study aimed to determine whether remnant cholesterol (RC) and its variability can predict the onset of metabolic dysfunction-associated steatotic liver disease (MASLD) independently of low-density lipoprotein cholesterol (LDL-C) levels. A longitudinal cohort study involving 43,065 participants who underwent at least two physical examinations was conducted. This study used Cox proportional hazards models to assess the relationships among RC quartile levels (Q1–Q4), visit-to-visit variability, and the risk of MASLD. This variability was quantified using several metrics: standard deviation (SD), logSD, average real variability (ARV), logARV, mean absolute deviation (MAD), and logMAD. Concurrently, this study utilized a combined analysis of RC and LDL-C groups to assess the independent risk of MASLD associated with RC. During a mean visit-to-visit of 3.19 years (SD 2.06 years), 8374 patients (19.45%) developed MASLD. Compared with Q1, Q4 was associated with a significantly greater risk of MASLD (hazard ratio [HR] 1.309, 95% confidence interval [CI] 1.220–1.403, P < 0.001). The fully adjusted Cox model revealed that the HRs of SD, logSD, ARV, logARV, MAD and logMAD were 1.400 (95% CI 1.305–1.502), 1.278 (95% CI 1.188–1.374), 1.152 (95% CI 1.079–1.229), 1.183 (95% CI 1.140–1.227), 1.578 (95% CI 1.433–1.737) and 1.263 (95% CI 1.175–1.358), respectively. In both LDL-C subgroups (≥ 3.4 mmol/L and < 3.4 mmol/L), high baseline RC was associated with elevated MASLD risk (HR 1.208, 95% CI 1.148–1.270, P < 0.001; HR 1.246, 95% CI 1.129–1.374, P < 0.001). RC levels were independently associated with MASLD in healthy individuals, irrespective of LDL-C level. The variability of RC during visit-to-visit periods provides a predictive marker for identifying individuals at heightened risk of MASLD. |
| format | Article |
| id | doaj-art-bf66558e353445eca3affca5d17a7ee3 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-bf66558e353445eca3affca5d17a7ee32025-02-09T12:31:43ZengNature PortfolioScientific Reports2045-23222025-02-0115111110.1038/s41598-025-88000-9Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver diseaseYuting Sun0Xinlei Miao1Manling Hu2Xiaoling Xie3Shuang Liu4Ziping Song5Jiayi Deng6Fei Xu7Meng Li8Yangxuan He9Song Leng10Health Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityHealth Management Center, The Second Hospital of Dalian Medical UniversityAbstract This study aimed to determine whether remnant cholesterol (RC) and its variability can predict the onset of metabolic dysfunction-associated steatotic liver disease (MASLD) independently of low-density lipoprotein cholesterol (LDL-C) levels. A longitudinal cohort study involving 43,065 participants who underwent at least two physical examinations was conducted. This study used Cox proportional hazards models to assess the relationships among RC quartile levels (Q1–Q4), visit-to-visit variability, and the risk of MASLD. This variability was quantified using several metrics: standard deviation (SD), logSD, average real variability (ARV), logARV, mean absolute deviation (MAD), and logMAD. Concurrently, this study utilized a combined analysis of RC and LDL-C groups to assess the independent risk of MASLD associated with RC. During a mean visit-to-visit of 3.19 years (SD 2.06 years), 8374 patients (19.45%) developed MASLD. Compared with Q1, Q4 was associated with a significantly greater risk of MASLD (hazard ratio [HR] 1.309, 95% confidence interval [CI] 1.220–1.403, P < 0.001). The fully adjusted Cox model revealed that the HRs of SD, logSD, ARV, logARV, MAD and logMAD were 1.400 (95% CI 1.305–1.502), 1.278 (95% CI 1.188–1.374), 1.152 (95% CI 1.079–1.229), 1.183 (95% CI 1.140–1.227), 1.578 (95% CI 1.433–1.737) and 1.263 (95% CI 1.175–1.358), respectively. In both LDL-C subgroups (≥ 3.4 mmol/L and < 3.4 mmol/L), high baseline RC was associated with elevated MASLD risk (HR 1.208, 95% CI 1.148–1.270, P < 0.001; HR 1.246, 95% CI 1.129–1.374, P < 0.001). RC levels were independently associated with MASLD in healthy individuals, irrespective of LDL-C level. The variability of RC during visit-to-visit periods provides a predictive marker for identifying individuals at heightened risk of MASLD.https://doi.org/10.1038/s41598-025-88000-9Primary preventionVisit-to-visit variabilityParticipation in healthy check-upsNovel lipid biomarkersJoint analysis |
| spellingShingle | Yuting Sun Xinlei Miao Manling Hu Xiaoling Xie Shuang Liu Ziping Song Jiayi Deng Fei Xu Meng Li Yangxuan He Song Leng Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease Scientific Reports Primary prevention Visit-to-visit variability Participation in healthy check-ups Novel lipid biomarkers Joint analysis |
| title | Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease |
| title_full | Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease |
| title_fullStr | Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease |
| title_full_unstemmed | Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease |
| title_short | Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease |
| title_sort | remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease |
| topic | Primary prevention Visit-to-visit variability Participation in healthy check-ups Novel lipid biomarkers Joint analysis |
| url | https://doi.org/10.1038/s41598-025-88000-9 |
| work_keys_str_mv | AT yutingsun remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT xinleimiao remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT manlinghu remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT xiaolingxie remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT shuangliu remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT zipingsong remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT jiayideng remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT feixu remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT mengli remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT yangxuanhe remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease AT songleng remnantcholesterolanditsvariabilityindependentoflowdensitylipoproteincholesterolpredictmetabolicdysfunctionassociatedsteatoticliverdisease |