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Published on: September 15, 2018
The Genetic Landscape of Familial Hypercholesterolemia in Telangana, Southern India: Novel Mutations and Clinical
Supriya Garapati1, Sakthivadivel Varatharajan2, Ariyanachi K1
1Anatomy, All India Institute of Medical Sciences, Bibinagar, Hyderabad, IND.
Background:
Familial hypercholesterolemia (FH) is a genetic disorder characterized by elevated low-density lipoprotein cholesterol (LDL-C) levels, leading to premature cardiovascular disease (CVD). This study aimed to identify genetic variants associated with FH in patients from Telangana State, India.
Methods:
Probands with suspected FH were identified using the Dutch Lipid Clinic Network (DLCN) score, followed by cascade screening of their first-degree relatives. Targeted exome sequencing and pedigree analysis were performed to identify FH-associated genetic variants.
Results:
We identified both novel and known high-impact mutations in genes implicated in FH pathogenesis, including stop-gain mutations in LPL (6/30; 20%) and LDLR (4/30; 13.3%), as well as splice donor site mutations in SLCO1B1 (1/30; 3.3%) and CETP (3/30; 10%). Notably, a novel frameshift mutation in LDLR was identified in two siblings (2/30; 6.7%), one of whom (50%) exhibited a homozygous variant and met the "Definite FH" classification based on the DLCN criteria. Additionally, moderate-impact variants rs2075291 (APOA5) and rs193922571 (LDLR) showed strong correlations with the DLCN score, suggesting increased susceptibility to FH. In contrast, rs6756629 (ABCG5) and rs11887534 (ABCG8) were strongly negatively correlated with LDL-C levels and the DLCN score, indicating potential protective effects against FH.
Conclusions:
These findings highlight the genetic heterogeneity of FH and emphasize the importance of identifying novel pathogenic variants. Moreover, the study underscores the role of moderate-impact variants in FH susceptibility. Overall, this research enhances our understanding of the genetic landscape of FH in the Indian population, with implications for improved diagnosis, risk assessment, and personalized management.
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