Tuesday, April 13, 2021

Addictions do have a genetic component, but genome-wide association studies indicate that it consists of many genetic factors with small additive effects - and of different genes than those originally suspected

The Streetlight Effect: Reappraising the Study of Addiction in Light of the Findings of Genome-wide Association Studies. Hall F.S. · Chen Y. · Resendiz-Gutierrez F. Brain, Behavior and Evolution, . https://doi.org/10.1159/000516169

Rolf Degen's take: https://twitter.com/DegenRolf/status/1381911439565283336

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.

Keywords: Drug dependenceCandidate gene studiesGenome-wide association studies


Moving Forward in the Post-GWAS Era

This review has considered several important transitions in approaches to studying the genetic basis of addiction. In particular, this review has used the streetlight analogy to illustrate how initial attempts to understand addiction were biased by our choice of gene targets to study. GWAS overcame this initial bias but came with a separate set of problems. GWAS moved the field forward in many ways, but to continue to move the field forward it will be necessary to once again step back and consider what preconceptions continue to limit progress. One of the core assumptions that was necessary for GWAS was that the genetic effects are additive. A deeper understanding of the genetic basis of addiction will require considering gene × gene and gene × environment interactions and developing methods for doing so. Recent analytical and technical advancements are beginning to allow us to look not just at highly interactive genetic effects [Joubert et al., 2018, 2019], but also at multiple “omic” levels simultaneously [Weighill et al., 2019]. These multiple omic levels include the genome, the epigenome, the transcriptome, and the proteome, among others. Some of the inconsistency in genetic findings from candidate gene and GWAS approaches probably results not only from allelic heterogeneity, but also from the fact that the genetic “signal” is obscured by a heterogeneous set of complex genetic and environmental interactions that should be observable in alterations at other levels, including the epigenome and transcriptome. Moreover, it has become clear that many of the underlying mechanisms mediating drug dependence liability involve changes in gene expression that are highly tissue and cell specific [Gallagher and Chen-Plotkin, 2018]. This of course means that a single transcriptome analysis will not provide a full explanation of the underlying mechanisms. In the coming years newer approaches to the study of drug dependence, and other complex diseases, will be able to specify the genetic contributions to addiction that have been missed so far by examining gene × gene and gene × environment interactions, and how they affect multiple functional levels in a cell type- and tissue-specific manner. This will allow a much clearer view of the etiology and biology of addiction, as well as identifying more critical points that can be used in the developing addiction therapeutics. 

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