Establishment of a Screening Program for Familial Hypercholesterolemia along with Comprehensive Assessment of Novel Lipid Biomarkers and Evaluation of a Machine Learning Algorithm in Young Adult Patients Presenting with Premature Coronary Artery Disease to a Tertiary Care Hospital

Familial hypercholesterolemia (FH) is the most common genetic disorder in young adults, predisposing them to develop accelerated premature coronary artery disease (CAD). FH is an autosomal, dominant disorder which follows mendelian inheritance. It is the first genetic disorder of lipid metabolism to be characterized both clinically and molecularly. FH results in elevated serum levels of Low-Density lipoprotein - Cholesterol (LDL-C) and accelerated risk of accelerated CAD in association with cholesterol deposits in peripheral tissues and tendon xanthomas. FH affects around1 in 250–500 individuals globally. The only Indian prevalence study demonstrated a prevalence of 15 percent in patients with premature CAD. There are only 6 genetic studies in India of which 32 percent were LDL-receptor (LDLR) mutations, 4 percent were Apolipoprotein B-100 (ApoB) mutations, 2 percent were PCSK9 mutations and the mutational spectrum for 37 percent were unknown. FH is asymptomatic in the initial stages due to which it is underdiagnosed in routine practice worldwide; hence, the condition is sub-optimally managed. FH can result primarily from gene mutations in either LDLR, ApoB, or PCSK9, singly or in combination. FH exists in two clinical forms. Heterozygous (He) FH is the most common and less severe which affects 1 in 200–250 where LDL-C levels are approximately twice as those of the normal population ranging from 190 to 400 mg per dL (4.9–10.3 mmol per L) . Homozygous (Ho) FH is rare and severe, characterized by

high LDL-C levels greater than 500 mg per dL (13 mmol per dL). Early diagnosis of FH coupled with appropriate management is necessary along with family cascade screening to prevent premature deaths.

Therapeutic reduction of LDL-C is one of the cornerstones in the management of CVD.Traditional lipid measurements may explain the major CVD risk in susceptible populations; yet, an unmet need for other novel diagnostic or therapeutic markers to evaluate CAD status and residual risk remains. Emerging lipid biomarkers have been identified, such as PCSK9, lipoprotein (a) [Lp(a)], apoB, apolipoprotein C3 (apoC3), small dense LDL (sdLDL) and large HDL. The associations between these biomarkers and coronary atherosclerosis have not been studied in great detail in south Asian populations.

As we have noted, genetic testing is the gold standard for diagnosing FH. There are currently no population-wide genetic testing programs. As referral for genetic testing is dependent on the clinical suspicion of FH prompted by a premature atherosclerotic cardiovascular event such as an acute coronary syndrome, the integration of ML derived tools in electronic health records may promote earlier suspicion of FH and subsequent genetic testing. ML derived tools have been utilized in registries in other countries which have demonstrated greater sensitivity and a lower number needed to screen for FH as compared to standard clinical diagnostic criteria and the automated screening criteria.

The PI and his team wish to study the prevalence of FH in a cohort which has been previously noted to have a high prevalence of premature CAD as compared to national and global estimates. On the other hand, FH is a condition of which awareness amongst Indian physicians has been found to be low. FH is a condition, which if detected early, can be controlled adequately and result in the prevention of devastating CVD. This study seeks to determine the prevalence of FH and other lipid disorders via genetic screening, machine learning and clinical screening tools in an ASCVD-prone population and modify lipid lowering therapy to prevent future ASCVD.