RESUMO
BACKGROUND: Prolactin is a polypeptide hormone secreted by the anterior pituitary gland that plays an essential role in lactation, tissue growth, and suppressing apoptosis to increase cell survival. Prolactin serves as a key player in many life-critical processes, including immune system and reproduction. Prolactin is also found in multiple fluids throughout the body, including plasma and cerebrospinal fluid (CSF). METHODS: In this study, we measured prolactin levels in both plasma and CSF, and performed a genome-wide association study. We then performed meta-analyses using METAL with a significance threshold of p < 5 × 10(-8) and removed SNPs where the direction of the effect was different between the two datasets. RESULTS: We identified 12 SNPs associated with increased prolactin levels in both biological fluids. CONCLUSIONS: Our efforts will help researchers understand how prolactin is regulated in both CSF and plasma, which could be beneficial in research for the immune system and reproduction.
Assuntos
Estudo de Associação Genômica Ampla/métodos , Polimorfismo de Nucleotídeo Único , Prolactina/sangue , Prolactina/líquido cefalorraquidiano , Adulto , Idoso , Idoso de 80 Anos ou mais , Doença de Alzheimer/sangue , Doença de Alzheimer/líquido cefalorraquidiano , Doença de Alzheimer/genética , Biomarcadores/sangue , Biomarcadores/líquido cefalorraquidiano , Proteínas Quinases Dependentes de Cálcio-Calmodulina/genética , Feminino , Frequência do Gene , Genótipo , Humanos , Peptídeos e Proteínas de Sinalização Intracelular/genética , Modelos Lineares , Desequilíbrio de Ligação , Metanálise como Assunto , Pessoa de Meia-Idade , Sulfotransferases/genéticaRESUMO
BACKGROUND: CCL16 is a chemokine predominantly expressed in the liver, but is also found in the blood and brain, and is known to play important roles in immune response and angiogenesis. Little is known about the gene's regulation. METHODS: Here, we test for potential causal SNPs that affect CCL16 protein levels in both blood plasma and cerebrospinal fluid in a genome-wide association study across two datasets. We then use METAL to performed meta-analyses with a significance threshold of p < 5x10(-8). We removed SNPs where the direction of the effect was different between the two datasets. RESULTS: We identify 10 SNPs associated with increased CCL16 protein levels in both biological fluids. CONCLUSIONS: Our results will help understand CCL16's regulation, allowing researchers to better understand the gene's effects on human health.
