Artigo Acesso aberto Revisado por pares

Twelve Variants Polygenic Score for Low‐Density Lipoprotein Cholesterol Distribution in a Large Cohort of Patients With Clinically Diagnosed Familial Hypercholesterolemia With or Without Causative Mutations

2022; Wiley; Volume: 11; Issue: 7 Linguagem: Inglês

10.1161/jaha.121.023668

ISSN

2047-9980

Autores

Elena Olmastroni, Marta Gazzotti, Marcello Arca, Maurizio Averna, Angela Pirillo, Alberico L. Catapano, Manuela Casula, Stefano Bertolini, S. Calandra, Patrizia Tarugi, Fabio Pellegatta, Andrea Bartuli, Andrea Benso, Giacomo Biasucci, Gianni Biolo, Luca Bonanni, Katia Bonomo, Claudio Borghi, Antonio Bossi, Adriana Branchi, Paolo Calabrò, Francesca Carubbi, Francesco Cipollone, Nadia Citroni, Maria Del Ben, Massimo Federici, Claudio Ferri, A.M. Fiorenza, Andrea Giaccari, Ornella Guardamagna, Marcello Arca, Gabriella Iannuzzo, Lorenzo Iughetti, Graziana Lupattelli, Alessandro Lupi, Giuseppe Mandraffino, Rossella Marcucci, Lorenzo Maroni, Giuliana Mombelli, Sandro Muntoni, Valerio Pecchioli, Cristina Pederiva, A. E. Pípolo, Livia Pisciotta, Antonio Pujia, Francesco Purrello, Elena Repetti, Carlo Sabbà, Riccardo Sarzani, Chiara Trenti, Giovanni Battista Vigna, José Pablo Werba, Sabina Zambon, Maria Grazia Zenti, Alessia Di Costanzo, Giuliana Fortunato, Rossella Spina, Davide Baldera, Giuseppe Banderali, Francesco Baratta, Guglielmo Beccuti, Sandra Bertocco, Patrizia Bruzzi, Marco Bucci, Paola Sabrina Buonuomo, Maria Elena Capra, Iris Cardolini, Angelo Baldassarre Cefalù, Maria Cinquegrani, Emanuela Colombo, Giuseppe Covetti, Anna Laura Cremonini, Ada Cutolo, Sergio D’Addato, Vincenzo D’Ambrosio, Giuseppe De Corrado, Chiara Di Pentima, Fabio Fimiani, Marco Gentile, Omar Ghirardello, Betti Giusti, D. Grassi, Liliana Grigore, Giulia Massini, Giancarla Meregalli, Ilenia Minicocci, Simona Moffa, Tiziana Montalcini, Fabio Nascimbeni, Emanuele Alberto Negri, Chiara Pavanello, Lucia Prati, Anna Rita Roscini, Elena Sani, Alon Schaffer, Roberto Scicali, Patrizia Suppressa, M. Tedeschi, Pierandrea Vinci, Enzo Manzato, Elena Tragni, V. Zampoleri,

Tópico(s)

Genetic factors in colorectal cancer

Resumo

Background A significant proportion of individuals clinically diagnosed with familial hypercholesterolemia (FH), but without any disease-causing mutation, are likely to have polygenic hypercholesterolemia. We evaluated the distribution of a polygenic risk score, consisting of 12 low-density lipoprotein cholesterol (LDL-C)-raising variants (polygenic LDL-C risk score), in subjects with a clinical diagnosis of FH. Methods and Results Within the Lipid Transport Disorders Italian Genetic Network (LIPIGEN) study, 875 patients who were FH-mutation positive (women, 54.75%; mean age, 42.47±15.00 years) and 644 patients who were FH-mutation negative (women, 54.21%; mean age, 49.73±13.54 years) were evaluated. Patients who were FH-mutation negative had lower mean levels of pretreatment LDL-C than patients who were FH-mutation positive (217.14±55.49 versus 270.52±68.59 mg/dL, P<0.0001). The mean value (±SD) of the polygenic LDL-C risk score was 1.00 (±0.18) in patients who were FH-mutation negative and 0.94 (±0.20) in patients who were FH-mutation positive (P<0.0001). In the receiver operating characteristic analysis, the area under the curve for recognizing subjects characterized by polygenic hypercholesterolemia was 0.59 (95% CI, 0.56-0.62), with sensitivity and specificity being 78% and 36%, respectively, at 0.905 as a cutoff value. Higher mean polygenic LDL-C risk score levels were observed among patients who were FH-mutation negative having pretreatment LDL-C levels in the range of 150 to 350 mg/dL (150-249 mg/dL: 1.01 versus 0.91, P<0.0001; 250-349 mg/dL: 1.02 versus 0.95, P=0.0001). A positive correlation between polygenic LDL-C risk score and pretreatment LDL-C levels was observed among patients with FH independently of the presence of causative mutations. Conclusions This analysis confirms the role of polymorphisms in modulating LDL-C levels, even in patients with genetically confirmed FH. More data are needed to support the use of the polygenic score in routine clinical practice.

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