The Streetlight Effect: Reappraising the Study of Addiction in Light of the Findings of Genome-wide Association Studies

Abstract

Drug dependence has long been thought to have a genetic component. Research seeking to identify the genetic basis of addiction has gone through important transitions over its history, in part based upon the emergence of new technologies, but also as the result of changing perspectives. Early research approaches were largely dictated by available technology, with technological advancements having highly transformative effects on genetic research, but the limitations of technology also affected modes of thinking about the genetic causes of disease. This review explores these transitions in thinking about the genetic causes of addiction in terms of the “streetlight effect,” which is a type of observational bias whereby people search for something only where it is easiest to search. In this way, the genes that were initially studied in the field of addiction genetics were chosen because they were the most “obvious,” and formed current understanding of the biological mechanisms underlying the actions of drugs of abuse and drug dependence. The problem with this emphasis is that prior to the genomic era the vast majority of genes and proteins had yet to be identified, much less studied. This review considers how these initial choices, as well as subsequent choices that were also driven by technological limitations, shaped the study of the genetic basis of drug dependence. While genome-wide approaches overcame the initial biases regarding which genes to choose to study inherent in candidate gene studies and other approaches, genome-wide approaches necessitated other assumptions. These included additive genetic causation and limited allelic heterogeneity, which both appear to be incorrect. Thus, the next stage of advancement in this field must overcome these shortcomings through approaches that allow the examination of complex interactive effects, both gene × gene and gene × environment interactions. Techniques for these sorts of studies have recently been developed and represent the next step in our understanding of the genetic basis of drug dependence.

Association of Dopamine Transporter Gene (DAT1) 40 bp 3′ UTR VNTR Polymorphism (rs28363170) and Cannabis Use Disorder

“…Genetic factors are known major determinants of addiction, while dopamine is known to be involved in reward and motivation. 13 , 26 Changes in dopaminergic signaling may therefore be expected to influence individual tendencies to addiction. We have, in this study, examined the relationships between a known polymorphism of the DAT1 gene coding for a key protein in the dopaminergic signaling pathway, cannabis use, and cannabis dependence among patients receiving treatment for cannabis use disorders at a tertiary treatment facility within Lagos in Nigeria.…”

“…12 Genetic epidemiology studies especially using twin and adoption studies, have established a strong link between genetic risk factors and substance dependence. 13 Genetic factors have been reported to account for 40% and 48% of the total variance in the initiation of cannabis use among women and men, respectively. 14 In the cannabinoid receptor gene, some single nucleotide polymorphisms-the rs806368, rs806380, and rs1049353 have been found to be associated with cannabis dependence.…”

Identification of the Risk Genes Associated With Vulnerability to Addiction: Major Findings From Transgenic Animals

“…While genetic linkage and association approaches such as Genome-Wide Association Studies (GWAS) have been widely used to identify candidate genes in humans ( Hall et al, 2013 , 2020 ; Serafine et al, 2021 ), to date few genes identified by GWAS have been verified by clinical or preclinical studies. Another major approach used to identify specific risk genes has been the examination of candidate genes that encode proteins that are critically involved in the pharmacological action of misused drugs, such as genes related to brain dopaminergic, GABAergic, opioid, and cholinergic systems ( Hall et al, 2013 ; Serafine et al, 2021 ).…”