African Americans Demonstrate Significantly Lower Serum Alanine Aminotransferase Compared to Non-African Americans

Journal of Racial and Ethnic Health Disparities(2020)

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摘要
Background and Aims Normal ranges of serum alanine aminotransferase (ALT) may vary by race. However, results from research studies are contradictory, and many of these studies have included only small numbers of African Americans. We investigated ALT values in patients without evidence of liver disease to determine whether normal ranges differ across race groups. We also evaluated whether a race- and sex-dependent upper limit of normal (ULN) would improve the ability of ALT to predict liver disease compared to the sex-dependent ULN currently in use. Methods We identified ICD9 codes for liver conditions and diabetes in medical records from a sample of 6719 patients. Analysis of variance (ANOVA) was used to assess differences in ALT log-transformed distributions by race. Logistic regression was used to evaluate whether the addition of race to the current sex-dependent ULN improves the ability of ALT to predict liver disease (assessed by area under the receiver operating characteristic curve (AUROC)). Results Among 1200 patients with BMI 18.5 < 25 and no evidence of liver disease or type 2 diabetes in their medical record, African Americans demonstrated significantly lower ALT (23.47 IU/L; 95% CL 22.87–24.10) than a combined group of Asian American/White/Other patients (25.71 IU/L; 95% CL 24.69–26.77). This difference remained across BMI categories. The race- and sex-dependent model demonstrated significantly better predictive ability than the sex-dependent model (AUROC = 66.6% versus 59.6%, respectively; p < 0.0001). Conclusions In a large, racially diverse sample, African Americans demonstrated significantly lower ALT compared to non-African Americans; this difference remained as BMI increased. The establishment of race-specific normal ranges for ALT could contribute to better screening and care for African American patients.
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关键词
Reference range intervals, BMI, Race, Health disparities, ALT
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