Background and Aim : -ADHD (attention deficit hyperactivity disorder) is characterized by ageinappropriate symptoms of inattention, impulsiveness, and hyperactivity. It affects 3%– 8% of school-age children, disrupting academic and social development, and persists into adulthood in 65% of those affected, amounting to 4% of the adult population. Cognitively, children and adults with ADHD have deficits in late-developing cognitive functions, most prominently inhibition, attention, motivation, and timing functions that are known to be mediated by late-developing frontostriatal and cerebellar networks. Many studies have reported an association between DAT1 (Dopamine Transporter 1) and ADHD since this gene encodes for dopamine transporters. ADHD patients have excess dopamine transporters and studies showed that Methylphenidate, which is a drug used for ADHD treatment, had negative effects on dopamine reuptake from pre-synaptic neurons, which ultimately leads to reduced symptoms of ADHD. This study reports the effect of the DAT1 gene on ADHD. Methods : -Electronic searches were performed using PubMed. In the extensive electronic literature search, keywords “SLC6A3 gene”, “DAT1 gene” and “attention deficit hyperactivity disorder”, “ADHD”, “meta” were searched for prospective studies. The pooled effect sizes (ORs) along with 95% confidence intervals (CIs), in “cases” and “controls” groups for different kinds of polymorphisms and SNPs were calculated. Further subgroup analyses were conducted if the data were available. Results : -A meta-analysis done with STATA on 36 studies revealed that the SLC6A3 (DAT1) gene has significant effects on ADHD with reported pooled OR of 1.02; 95% CI = (0.96 – 1.06) 666 and a p-value of 0.00 which rules out the null hypothesis which means that it has significant effect on ADHD. For heterogeneity I2 = 49.47% and H2 = 1.98 which indicates that there is a moderate amount of heterogeneity. Conclusion : These results overall indicate strong evidence against the null hypothesis. (The null hypothesis is a typical statistical theory that suggests that no statistical relationship and significance exists in a set of given single observed variables, between two sets of observed data and measured phenomena.)

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