Statin-induced myopathy (SIM) has been partially attributed to deficiency of dolichol and coenzyme Q10 (CoQ10). We aimed to test the safety and efficacy of plant polyprenols in combination with CoQ10 for alleviation of SIM. In an open-label, one-center prospective pilot study patients with SIM received conifer-tree needle polyprenols (4mg/day) and CoQ10 (100mg/day) for 8 weeks. Symptoms and safety were evaluated according to symptom severity score (0-10), creatine kinase (CK) levels, exercise test, dynamometry, complete blood count, clinical biochemistry and electrocardiography. Of the 14 patients, 11 completed the study per protocol. Two patients withdrew consent due to travels abroad, and it was discontinued for one patient with stage 3 chronic kidney disease due to asymptomatic elevations of liver enzymes at week 4. No safety parameters changed significantly in per protocol group. Non-significant increase of CK levels was observed (P=0.231). Muscle pain (n=10) and weakness (n=7) scores improved significantly (P<0.001 and P=0.018, respectively). Muscle pain completely disappeared in 2 patients, weakness resolved in 3 patients and cramps disappeared in two patients. Four patients assessed improvement strong enough to consider increase of statin dose. No changes were observed in exercise test or dynamometry. Conifer-tree polyprenols in combination with CoQ10 may be generally safe in patients with SIM, but caution should be exercised in patients with glomerular filtration rate <60mL/min and routine monitoring of the liver enzymes and CK is advocated in all patients. The observed efficacy provides the rationale for a larger, double-blind controlled study with polyprenols.

Background: There is limited data on the genetic characteristics of patients with familial hypercholesterolemia (FH) in Latvia. We aim to describe monogenic variants in patients from the Latvian Registry of FH (LRFH). Methods: Whole genome sequencing with 30× coverage was performed in unrelated index cases from the LRFH and the Genome Database of Latvian Population. LDLR, APOB, PCSK9, LDLRAP1, ABCG5, ABCG8, LIPA, LPA, CYP27A1, and APOE genes were analyzed. Only variants annotated as pathogenic (P) or likely pathogenic (LP) using the FH Variant Curation Expert Panel guidelines for LDLR and adaptations for APOB and PCSK9 were reported. Results: Among 163 patients, the mean highest documented LDL-cholesterol level was 7.47 ± 1.60 mmol/L, and 79.1% of patients had LDL-cholesterol ≥6.50 mmol/L. A total of 15 P/LP variants were found in 34 patients (diagnostic yield: 20.9%): 14 in the LDLR gene and 1 in the APOB gene. Additionally, 24, 54, and 13 VUS were detected in LDLR, APOB, and PCSK9, respectively. No P/LP variants were identified in the other tested genes. Conclusions: Despite the high clinical likelihood of FH, confirmed P/LP variants were detected in only 20.9% of patients in the Latvian cohort when assessed with genome-wide next generation sequencing.

Despite the implementation of next-generation sequencing-based genetic testing on patients with clinical familial hypercholesterolemia (FH), most cases lack complete genetic characterization. We aim to investigate the utility of the polygenic risk score (PRS) in specifying the genetic background of patients from the Latvian Registry of FH (LRFH). We analyzed the whole-genome sequencing (WGS) data of the clinically diagnosed FH patients (n = 339) and controls selected from the Latvian reference population (n = 515). Variant pathogenicity in FH patients was classified according to the ACMG/AMP guidelines. The low-density lipoprotein cholesterol (LDL-C) and lipoprotein (a) (LPA) PRS were calculated based on the WGS data. We identified unique causative variants in 80 (23.6%) of the tested individuals (39 variants in FH genes and 4 variants in phenocopy genes, with 6 variants being novel). The LDL-C PRS was highly discriminative compared to the LPA PRS. Nevertheless, both PRS were able to explain the genetic cause of hypercholesterolemia in 26.3% of the remaining non-monogenic patients. The combined genetic analysis of monogenic and polygenic hypercholesterolemia resulted in 43.7% genetically explained hypercholesterolemia cases. Even though the application of PRS alone does not exclude monogenic testing in clinical FH patients, it is a valuable tool for diagnosis specification.