Expressive

rs10868235 - NTRK2

Magnitude 2.2 · 2 studies on file

Reported associations

  • The first genome-wide association study of internet addiction; Revealed substantial shared risk factors with neurodevelopmental psychiatric disorders. - Research in developmental disabilities (2023) · Haghighatfard A, Ghaderi AH, Mostajabi P, Kashfi SS, Mohabati Somehsarayee H, Shahrani M, Mehrasa M, Haghighat S, Farhadi M, Momayez Sefat M, Shiryazdi AA, Ezzati N, Qazvini MG, Alizadenik A, Moghadam ER · PubMed 36566681

    Internet addiction disorder (IAD) is listed as a disorder requiring further studies in the diagnostic and statistical manual of mental disorders (DSM-V). Psychological studies showed significant co-morbidity of IAD with depression, alcohol abuse, and anxiety disorder. Etiology and genetic bases of IAD are unclear. Present study aimed to investigate the genetic, psychological, and cognitive bases of a tendency to internet addiction. DNA was extracted from blood samples of IADs (N = 16,520) and 18,000 matched non-psychiatric subjects. Genotyping for the subjects was performed using SNP Array. Psychological, neuropsychological, and neurological characteristics were conducted. Seventy-two SNPs in 24 genes have been detected significantly associated with IAD. Most of these SNPs were risk fact

  • A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286

    ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%

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