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Is There a Reliable, Rapid, and Economic Diagnostic Approach for SLCO2A1-Related Chronic Enteropathy?
Rongbei Liu1,2, Yujuan Fu2,3, Jie Mao2,3
1Department of Gastroenterology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310027, China.
None:
Background: Chronic enteropathy associated with SLCO2A1 (CEAS) is a rare genetic disorder that is prone to misdiagnosis and characterized by significant challenges in achieving an early diagnosis. Current diagnosis relies on clinical manifestation combined with genetic sequencing. This study aimed to evaluate immunohistochemical (IHC) staining for SLCO2A1 protein deficiency as a diagnostic alternative, in addition to clinical pathological features. Method: Ten patients diagnosed with CEAS between January 2018 and August 2024 were enrolled. Clinicodemographic data, endoscopic findings, and treatment history were collected. Whole-exome sequencing identified SLCO2A1 variants. IHC staining for SLCO2A1 protein was performed from small intestine lesions and accessible GI sites. Results: Complete absence of SLCO2A1 protein expression was demonstrated by IHC in 9/10 patients, with significantly reduced expression in 1/10. This protein deficiency was consistently observed not only in the small intestine but also in the gastric antrum, duodenum, and terminal ileum. Genetic analysis revealed 7 novel SLCO2A1 variants among a total of 11 variants. A median diagnostic delay of 15 years (IQR 6-24) was observed. Ileal involvement and hypoalbuminemia (median albumin 28.02 g/L, IQR 22.1-33.0) were present in all patients. Common symptoms included abdominal pain (70%), melena (60%), and ileus (50%). Conclusions: The diagnosis of CEAS has been time-consuming and challenging. Detection of SLCO2A1 protein deficiency via IHC in either the disease-predominant small bowel or accessible non-lesional upper/lower GI mucosa demonstrates high diagnostic sensitivity for CEAS. This method could provide a practical, cost-effective alternative to genetic sequencing, particularly in resource-limited settings, and has the potential to significantly reduce diagnostic delays for this condition.
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