Evidence map›Paper›PMID 42183279›Full record

ArticleFrontiers in immunology2026

Association of metabolic and inflammation vulnerabilities with systemic lupus erythematosus: a prospective UK Biobank study.

Dongqi Zhou, Lisha Sun, Na Li, Yi Liang, Gaofeng Gan, Dazhou Liao, Qiu Chen

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Dongqi Zhou *Department of Endocrine, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Lisha Sun *Department of Endocrine, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Na Li *Department of Infectious Diseases, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Yi LiangDepartment of Endocrine, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Gaofeng GanDepartment of Traditional Chinese Medicine, Taikang Hospital of Sichuan Province, Chengdu, Sichuan, China.
Dazhou LiaoWest China Hospital, Sichuan University, Chengdu, Sichuan, China.
Qiu ChenHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease influenced by complex metabolic and inflammatory pathways, but the impact of specific metabolic and inflammatory signatures, particularly metabolic vulnerability index (MVX), inflammation vulnerability index (IVX), and metabolic malnutrition index (MMX), on the incidence of SLE remains unclear. Methods: We evaluated the association of MVX, IVX, and MMX with the risk of incident SLE using data from 398,200 participants in the UK Biobank. MVX was constructed from IVX (calculated using glycA and small HDL particles) and MMX (calculated using citrate, isoleucine, leucine, and valine). The primary outcome was SLE based on the International Classification of Diseases, 10th Revision (ICD-10) codes. Risks were estimated using Cox proportional hazards models, while restricted cubic spline (RCS) analysis was applied to identify potential non-linear trends. Subgroup analyses were performed by demographics, comorbidities, and lifestyle factors. Sensitivity analyses included a 3-year lag exclusion, landmark analyses at 5 and 10 years, additional adjustment for C-reactive protein (CRP), the use of time-dependent covariates combined with stratification, and the use of data after multiple imputation. Additionally, the Fine-Gray competing risk model was employed treating all-cause mortality and CVD-specific mortality as competing events. Results: Over a median follow-up of 13.2 years, a per standard deviation (SD) increment in MVX was associated with a 44% higher risk of SLE (HR = 1.44, 95% CI: 1.28-1.62, P < 0.01). Participants in the highest tertile (T3) of MVX had an 89% increased risk compared to those in the lowest tertile (T1) (HR = 1.89, 95% CI: 1.35-2.63, P < 0.01). Similar but attenuated associations were observed for IVX and MMX; per SD increases in IVX and MMX were associated with HRs of 1.34 (95% CI: 1.17-1.54, P < 0.01) and 1.24 (95% CI: 1.14-1.36, P < 0.01), respectively, while T3 versus T1 HRs were 1.85 (95% CI: 1.25-2.74, P < 0.01) and 1.82 (95% CI: 1.42-2.33, P < 0.01). MVX consistently demonstrated a stronger association with SLE than the sub-indices IVX and MMX. Subgroup analyses indicated that the significant association persisted across most groups, with a notable effect observed in females (HR = 1.59, 95% CI: 1.39-1.81, P < 0.01). RCS analysis confirmed a linear dose-response relationship, with risk thresholds of 36 for MVX, 40 for IVX, and 45 for MMX; beyond these thresholds, the risk of SLE increases as the index rises. Sensitivity analyses and the Fine-Gray competing risk model both confirmed the robustness of the study results, demonstrating that MVX is significantly associated with the risk of incident SLE. Conclusions: MVX serves as an independent risk factor for the development of SLE. Notably, MVX demonstrates a stronger association with SLE risk compared to its individual components, IVX and MMX. Our results suggest that MVX is valuable for risk assessment for SLE, particularly within the female population.

Indexed as

InflammationLupus Erythematosus, SystemicAdultBiological Specimen BanksFemaleHumansIncidenceMaleMiddle AgedProspective StudiesRisk FactorsUK BiobankUnited Kingdominflammation vulnerabilitymetabolic malfunctionmetabolic vulnerabilitysystemic lupus erythematosusUK Biobank

Identifiers

PMID42183279
PMCPMC13195015

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.