# Applying Genetic Risk Score to Improve Risk Assessment of New‐Onset Lupus Nephritis in Systemic Lupus Erythematosus: A Large‐Scale Prospective Cohort Study

## TL;DR

This study shows that combining clinical risk factors and a genetic risk score can better predict the risk of new-onset lupus nephritis in SLE patients.

## Contribution

The study introduces a genetic risk score that improves risk stratification for lupus nephritis when combined with clinical factors.

## Key findings

- A clinical high-risk group had an 18.1% 3-year LN incidence based on age, absence of arthritis, and other factors.
- The genetic risk score was independently associated with LN (HR = 3.19, p = 4.36 × 10−5).
- Clinically low-risk individuals with high GRS had a 15.5% 3-year LN incidence compared to 1.4%.

## Abstract

Lupus nephritis (LN) is one of the most severe manifestation of systemic lupus erythematosus (SLE). However, reliable tools for predicting LN risk remain limited. In this multicenter prospective cohort study, we developed, validated, and refined a risk stratification model for new‐onset LN. A total of 2441 SLE patients without baseline renal involvement were consecutively enrolled from the Chinese SLE Treatment and Research (CSTAR) registry, with 215 (8.8%) developed LN in a median follow‐up time of 3.5 years. A combination of clinical predictors, age < 30 years, absence of arthritis, serositis, hypocomplementemia, and positive anti‐double‐stranded DNA antibodies identified a clinical high‐risk group (n = 537, 22.0%) with a 3‐year LN incidence of 18.1%. The model was externally validated in 451 patients, with 50 developed LN in a median follow‐up time of 3.4 years. In these patients, a genetic risk score (GRS) derived from 112 SLE‐associated loci was found to be independently associated with LN (HR = 3.19, 95% CI, 1.83–5.55, p = 4.36 × 10−5). Among clinically low‐risk individuals, those in the highest GRS quartiles (81/451, 18.0%) showed elevated 3‐year LN incidence (15.5% vs. 1.4%). New‐onset LN may be predicted using a combination of clinical risk factors, and integrating GRS further improves risk stratification, enabling early identification of high‐risk patients.