Misdiagnosis of alpha-gal syndrome as non-celiac gluten sensitivity or lactose intolerance: A diagnostic blind spot for clinicians

Alpha-gal syndrome (AGS), an emerging tick-borne carbohydrate hypersensitivity, has gained increasing recognition for its atypical presentation and delayed food-related allergic reactions. While urticaria and anaphylaxis dominate the clinical narrative, gastrointestinal (GI) manifestations-including abdominal pain, diarrhea, bloating, and cramping-are common and often underrecognized. These nonspecific GI symptoms create significant diagnostic overlap with prevalent functional and food-related disorders such as non-celiac gluten sensitivity (NCGS) and lactose intolerance. Consequently, many patients with AGS undergo unnecessary dietary restrictions, prolonged symptom burden, or misdirected therapies before an accurate diagnosis is established. The knowledge gap lies in the limited awareness of AGS as a differential diagnosis for food-related GI complaints, especially in regions endemic to tick exposure. Unlike gluten or lactose intolerance, AGS reactions are characterized by a unique delayed onset (2-6 hours postprandially) and a distinct immunologic mechanism mediated by IgE to galactose-α-1,3-galactose. However, clinicians rarely consider AGS when evaluating chronic, unexplained food-triggered symptoms, perpetuating diagnostic blind spots. Current guidelines for evaluating NCGS and lactose intolerance seldom incorporate testing for alpha-gal IgE, despite growing evidence that a subset of misdiagnosed patients may in fact harbor AGS. Clinically, this misclassification carries significant consequences: Patients may continue mammalian food exposure with risk of escalating allergic reactions, including life-threatening anaphylaxis, while adhering to unnecessary or ineffective gluten-free or lactose-free diets. Raising awareness, integrating alpha-gal IgE testing into gastroenterology workups, and refining diagnostic algorithms are urgently needed. Addressing this blind spot has the potential to reduce morbidity, improve diagnostic accuracy, and optimize individualized patient care.