TY - JOUR
T1 - Nucleotide variation in central nervous system genes among male suicide attempters
AU - Baca-Garcia, Enrique
AU - Vaquero-Lorenzo, Concepción
AU - Perez-Rodriguez, M. Mercedes
AU - Gratacòs, Mònica
AU - Bayés, Mònica
AU - Santiago-Mozos, Ricardo
AU - Leiva-Murillo, Jose Miguel
AU - De Prado-Cumplido, Mario
AU - Artes-Rodriguez, Antonio
AU - Ceverino, Antonio
AU - Diaz-Sastre, Carmen
AU - Fernandez-Navarro, Pablo
AU - Costas, Javier
AU - Fernandez-Piqueras, José
AU - Diaz-Hernandez, Montserrat
AU - De Leon, Jose
AU - Baca-Baldomero, Enrique
AU - Saiz-Ruiz, Jeronimo
AU - Mann, J. John
AU - Parsey, Ramin V.
AU - Carracedo, Angel
AU - Estivill, Xavier
AU - Oquendo, Maria A.
PY - 2010/1
Y1 - 2010/1
N2 - Despite marked morbidity and mortality associated with suicidal behavior, accurate identification of individuals at risk remains elusive. The goal of this study is to identify a model based on single nucleotide polymorphisms (SNPs) that discriminates between suicide attempters and non-attempters using data mining strategies. We examined functional SNPs (n=840) of 312 brain function and development genes using data mining techniques. Two hundred seventy-seven male psychiatric patients aged 18 years or older were recruited at a University hospital psychiatric emergency room or psychiatric short stay unit. The main outcome measure was history of suicide attempts. Three SNPs of three genes (rs10944288, HTR1E; hCV8953491, GABRP; and rs707216, ACTN2) correctly classified 67% of male suicide attempters and non-attempters (0.50 sensitivity, 0.82 specificity, positive likelihood ratio=2.80, negative likelihood ratio=1.64). The OR for the combined three SNPs was 4.60 (95% CI: 1.31-16.10). The model's accuracy suggests that in the future similar methodologies may generate simple genetic tests with diagnostic utility in identification of suicide attempters. This strategy may uncover new pathophysiological pathways regarding the neurobiology of suicidal acts.
AB - Despite marked morbidity and mortality associated with suicidal behavior, accurate identification of individuals at risk remains elusive. The goal of this study is to identify a model based on single nucleotide polymorphisms (SNPs) that discriminates between suicide attempters and non-attempters using data mining strategies. We examined functional SNPs (n=840) of 312 brain function and development genes using data mining techniques. Two hundred seventy-seven male psychiatric patients aged 18 years or older were recruited at a University hospital psychiatric emergency room or psychiatric short stay unit. The main outcome measure was history of suicide attempts. Three SNPs of three genes (rs10944288, HTR1E; hCV8953491, GABRP; and rs707216, ACTN2) correctly classified 67% of male suicide attempters and non-attempters (0.50 sensitivity, 0.82 specificity, positive likelihood ratio=2.80, negative likelihood ratio=1.64). The OR for the combined three SNPs was 4.60 (95% CI: 1.31-16.10). The model's accuracy suggests that in the future similar methodologies may generate simple genetic tests with diagnostic utility in identification of suicide attempters. This strategy may uncover new pathophysiological pathways regarding the neurobiology of suicidal acts.
KW - Glutamate receptors
KW - Sensitivity and specificity
KW - Serotonin receptors
KW - Single nucleotide polymorphism
KW - Statistical models
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U2 - 10.1002/ajmg.b.30975
DO - 10.1002/ajmg.b.30975
M3 - Article
C2 - 19455598
AN - SCOPUS:73949128499
SN - 1552-4841
VL - 153
SP - 208
EP - 213
JO - American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
JF - American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
IS - 1
ER -