Examinando por Autor "Mastronardi, Claudio A."
Mostrando 1 - 3 de 3
Resultados por página
Opciones de ordenación
Ítem ADGRL3 (LPHN3) variants predict substance use disorder(Nature Research, 2019-01) Arcos-Burgos, Mauricio; Vélez, Jorge I.; Martinez, Ariel F.; Ribasés, Marta; Ramos-Quiroga, Josep A.; Sánchez-Mora, Cristina; Richarte, Vanesa; Roncero, Carlos; Cormand, Bru; Fernández-Castillo, Noelia; Casas, Miguel; Lopera, Francisco; Pineda, David A.; Palacio, Juan D.; Acosta-López, Johan E.; Cervantes-Henriquez, Martha L.; Sánchez-Rojas, Manuel G.; Puentes-Rozo, Pedro J.; Molina, Brooke S. G.; MTA Cooperative Group; Boden, Margaret T.; Wallis, Deeann; Lidbury, Brett; Newman, Saul; Easteal, Simon; Swanson, James; Patel, Hardip; Volkow, Nora; Acosta, Maria T.; Castellanos, Francisco X.; de Leon, Jose; Mastronardi, Claudio A.; Muenke, MaximilianGenetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attentiondeficit/ hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world (n = 2698), recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive-partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD.Ítem Genetic variation underpinning ADHD risk in a caribbean community(Published by MDP, 2019) Puentes-Rozo, Pedro J.; Acosta-López, Johan E.; Cervantes-Henríquez, Martha L.; Martínez-Banfi, Martha L.; Mejia-Segura, Elsy; Sánchez-Rojas, Manuel; Anaya-Romero, Marco E.; Acosta-Hoyos, Antonio; García-Llinás, Guisselle A.; Mastronardi, Claudio A.; Pineda, David A.; Castellanos, F. Xavier; Arcos-Burgos, Mauricio; Vélez, Jorge I.Attention Deficit Hyperactivity Disorder (ADHD) is a highly heritable and prevalent neurodevelopmental disorder that frequently persists into adulthood. Strong evidence from genetic studies indicates that single nucleotide polymorphisms (SNPs) harboured in the ADGRL3 (LPHN3), SNAP25, FGF1, DRD4, and SLC6A2 genes are associated with ADHD. We genotyped 26 SNPs harboured in genes previously reported to be associated with ADHD and evaluated their potential association in 386 individuals belonging to 113 nuclear families from a Caribbean community in Barranquilla, Colombia, using family-based association tests. SNPs rs362990-SNAP25 (T allele; p = 2.46 10x-4), rs2282794-FGF1 (A allele; p = 1.33 10x-2), rs2122642-ADGRL3 (C allele, p = 3.5 10x-2), and ADGRL3 haplotype CCC (markers rs1565902-rs10001410-rs2122642, OR = 1.74, Ppermuted = 0.021) were significantly associated with ADHD. Our results confirm the susceptibility to ADHD conferred by SNAP25, FGF1, and ADGRL3 variants in a community with a significant African American component, and provide evidence supporting the existence of specific patterns of genetic stratification underpinning the susceptibility to ADHD. Knowledge of population genetics is crucial to define risk and predict susceptibility to disease.Ítem Targeting Neuroplasticity, Cardiovascular, and Cognitive-Associated Genomic Variants in Familial Alzheimer’s Disease(SpringerLink, 2018-08) Vélez, Jorge I.; Lopera, Francisco; Creagh, Penelope K.; Piñeros, Laura B.; Das, Debjani; Cervantes-Henríquez, Martha L.; Acosta-López, Johan E.; Isaza – Ruget, Mario A.; Espinosa, Lady G.; Easteal, Simon; Quintero, Gustavo A.; Tamar Silva, Claudia; Mastronardi, Claudio A.; Arcos-Burgos, MauricioBackground: The identification of novel genetic variants contributing to the widespread in the age of onset (AOO) of Alzheimer’s disease (AD) could aid in the prognosis and/or development of new therapeutic strategies focused on early interventions. Methods: We recruited 78 individuals with AD from the Paisa genetic isolate in Antioquia, Colombia. These individuals belong to the world largest multigenerational and extended pedigree segregating AD as a consequence of a dominant fully penetrant mutation in the PSEN1 gene and exhibit an AOO ranging from the early 30s to the late 70s. To shed light on the genetic underpinning that could explain the large spread of the age of onset (AOO) of AD, 64 single nucleotide polymorphisms (SNP) associated with neuroanatomical, cardiovascular and cognitive measures in AD were genotyped. Standard quality control and filtering procedures were applied, and single- and multi-locus linear mixed-effects models were used to identify AOO associated SNPs. A full two-locus interaction model was fitted to define how identified SNPs interact to modulate AOO. Results: We identified two key epistatic interactions between the APOE*E2 allele and SNPs ASTN2-rs7852878 and SNTG1-rs16914781 that delay AOO by up to ~8 years (95%CI: 3.2-12.7, P=1.83x10-3) and ~7.6 years (95%CI: 3.3-11.8, P = 8.69x10-4), respectively, and validated our previous finding indicating that APOE*E2 delays AOO of AD in PSEN1 E280 mutation carriers. Discussion: This new evidence involving APOE*E2 as an AOO delayer could be used for developing precision medicine approaches and predictive genomics models to potentially determine AOO in individuals genetically predisposed to AD.