RESUMO
BACKGROUND: The diabetogenic effect of statins has been well established by clinical trials, Mendelian randomisation studies and meta-analyses. According to large clinical trials, PCSK9 inhibitors (PCSK9i) have no deleterious impact on glucose metabolism. However, few real-life studies have yet evaluated the long-term effects of these drugs on glucose homeostasis and their impact on new-onset diabetes (NODM). METHODS: We studied 218 patients treated with either alirocumab or evolocumab (70% with familial hypercholesterolemia) for at least three years (PCSK9iG). We studied the NODM rate in the nondiabetic group at baseline (168) and overall glucose metabolism control in the whole group. Incidental DM was compared with two groups. The first was a propensity score matching (PSM)-selected group (n = 168) from the database of patients attending the Reus lipid unit (Metbank, n = 745) who were not on PCSK9i (PSMG). The second was a subgroup with a similar age range (n = 563) of the Di@bet.es study (Spanish prospective study on diabetes development n = 5072) (D@G). The incidence was reported as the percentage of NODM cases per year. RESULTS: The fasting glucose (FG) level of the subjects with normoglycaemia at baseline increased from 91 (86-95.5) to 93 (87-101) mg/dL (p = 0.014). There were 14 NODM cases in the PCSK9i group (2.6%/y), all among people with prediabetes at baseline. The incidence of NODM in PSMG and D@G was 1.8%/y (p = 0.69 compared with the PCSK9iG). The incidence among the subjects with prediabetes was 5.1%/y in the PCSK9iG, 4.8%/y in the PSMG and 3.9%/y in the D@G (p = 0.922 and p = 0.682, respectively). In the multivariate analysis, only the FG level was associated with the development of NODM in the PCSK9iG (OR 1.1; 95% CI: 1.0-1.3; p = 0.027). Neither FG nor A1c levels changed significantly in patients with DM at baseline. CONCLUSION: A nonsignificant increase in NODM occurred in the PCSK9iG, particularly in patients with prediabetes, compared with the PSMG and D@G groups. Baseline FG levels were the main variable associated with the development of DM. In the subjects who had DM at baseline, glucose control did not change. The impact of PCSK9i on glucose metabolism should not be of concern when prescribing these therapies.
Assuntos
Diabetes Mellitus , Inibidores de Hidroximetilglutaril-CoA Redutases , Estado Pré-Diabético , Humanos , Inibidores de PCSK9 , Pró-Proteína Convertase 9 , Controle Glicêmico , Estudos Prospectivos , Diabetes Mellitus/diagnóstico , Diabetes Mellitus/tratamento farmacológico , Diabetes Mellitus/epidemiologia , Inibidores de Hidroximetilglutaril-CoA Redutases/efeitos adversos , Glucose , Fatores de RiscoRESUMO
BACKGROUND: The familial hypercholesterolemia (FH) diagnosis is based on clinical and genetic criteria. A relevant proportion of FH patients fulfilling the criteria for definite FH have negative genetic testing. Increasing the identification of true genetic-based FH is a clinical challenge. Deepening the analysis of lipoprotein alterations could help increase the yield of genetic testing. We evaluated whether the number, size, and composition of lipoproteins assessed by 1H-NMR could increase the identification of FH patients with pathogenic gene variants. METHODS: We studied 294 clinically definite FH patients, 222 (75.5%) with positive genetic testing, as the discovery cohort. As an external validation cohort, we studied 88 children with FH, 72 (81%) with positive genetic testing. The advanced lipoprotein test based on 1H-NMR (Liposcale®) was performed at baseline after a lipid-lowering drug wash-out of at least 6 weeks. The association of variables with genetic variants was evaluated by random forest and logistic regression. Areas under the curve (AUCs) were calculated. A predictive formula was developed and applied to the validation cohort. RESULTS: A formula derived from NMR lipoprotein analyses improved the identification of genetically positive FH patients beyond LDL-C levels (AUC=0.87). The parameters contributing the most to the identification formula were LDL particle number, HDL size and remnant cholesterol. The formula also increases the classification of FH children with a pathogenic genetic variation. CONCLUSIONS: NMR lipoprotein profile analysis identifies differences beyond standard lipid parameters that help identify FH with a positive pathogenic gene variant, increasing the yield of genetic testing in FH patients.