{Reference Type}: Journal Article
{Title}: The impact of genetic risk on the prevalence of advanced fibrosis and cirrhosis in prospectively assessed patients with type 2 diabetes.
{Author}: Bridi L;Agrawal S;Tesfai K;Madamba E;Bettencourt R;Richards LM;Khera AV;Loomba R;Ajmera V;
{Journal}: Aliment Pharmacol Ther
{Volume}: 60
{Issue}: 3
{Year}: 2024 08 2
{Factor}: 9.524
{DOI}: 10.1111/apt.18099
{Abstract}: Genetic factors contribute to the risk and severity of metabolic dysfunction-associated steatotic liver disease (MASLD). However, the utility of genetic testing in risk stratification remains poorly characterised.
To examine the influence of genetic risk on advanced fibrosis and cirrhosis in patients with type 2 diabetes mellitus (T2DM) and the utility of a polygenic risk score (PRS) in screening guidelines.
We prospectively enrolled adults aged ≥50 years with T2DM recruited from clinics. PRS was the sum of risk alleles in PNPLA3, TM6SF2 and SERPINA1 minus the protective variant in HSD17B13. We performed magnetic resonance elastography and vibration-controlled transient elastography to assess for advanced fibrosis and cirrhosis.
Of 382 included patients, the mean age and BMI were 64.8 (±8.4) years and 31.7 (±6.2) kg/m2 respectively. The prevalence of advanced fibrosis and cirrhosis were 12.3% and 5.2% respectively; higher PRS was associated with increased risk of cirrhosis (2.7% vs. 7.5%, p = 0.037). High PRS was associated with increased risk of advanced fibrosis among those with fibrosis-4 index (FIB-4) index <1.3 (9.6% vs. 2.3%, p = 0.036) but was not significantly different in other FIB-4 categories. Incorporating PRS determination into the American Gastroenterological Association and American Association for the Study of Liver Diseases screening guidelines prevented approximately 20% of all participants with advanced fibrosis from being inappropriately classified as low risk.
Utilising a well-phenotyped, prospective cohort of adults with T2DM, we found that adding an assessment of genetic risk to recommendations to screen at-risk populations may improve risk prediction.