HJNO May/Jun 2022

DRUG ADDICTION accounts for 50% of the risk for this con- dition. Once whole genome sequencing is readily available, it is likely that it will be possible to identify most of that DNAvaria- tion. For clinical purposes, those polygenic scores will of course not replace an under- standing of the intricate web of biological and social factors that promote or prevent expression of addiction in an individual case; rather, they will add to it [49]. Mean- while, however, genome-wide association studies in addiction have already provided important information. For instance, they have established that the genetic under- pinnings of alcohol addiction only partially overlap with those for alcohol consump- tion, underscoring the genetic distinction between pathological and nonpathological drinking behaviors [50]. It thus seems that, rather than negating a rationale for a disease view of addiction, the important implication of the polygenic nature of addiction risk is a very different one. Genome-wide association studies of complex traits have largely confirmed the century old “infinitisemal model” in which Fisher reconciled Mendelian and polygenic traits [51]. A key implication of this model is that genetic susceptibility for a complex, polygenic trait is continuously distributed in the population. This may seem antitheti- cal to a view of addiction as a distinct dis- ease category, but the contradiction is only apparent, and one that has long been famil- iar to quantitative genetics. Viewing addic- tion susceptibility as a polygenic quan- titative trait, and addiction as a disease category is entirely in line with Falconer’s theorem, according to which, in a given set of environmental conditions, a certain level of genetic susceptibility will determine a threshold above which disease will arise. A brain disease? Then show me the brain lesion! The notion of addiction as a brain dis- ease is commonly criticized with the argu- ment that a specific pathognomonic brain lesion has not been identified. Indeed, brain imaging findings in addiction (perhaps with the exception of extensive neurotoxic gray matter loss in advanced alcohol addiction) are nowhere near the level of specificity and sensitivity required of clinical diagnostic tests. However, this criticism neglects the fact that neuroimaging is not used to diag- nose many neurologic and psychiatric dis- orders, including epilepsy, ALS, migraine, Huntington’s disease, bipolar disorder, or schizophrenia. Even among conditions not deterministic. However, as we will see below, in the case of addiction, it contrib- utes to large, consistent probability shifts towards maladaptive behavior. In dismissing the relevance of genetic risk for addiction, Hall writes that “a large number of alleles are involved in the genetic susceptibility to addiction and individually these alleles might very weakly predict a risk of addiction”. He goes on to conclude that “generally, genetic prediction of the risk of disease (even with whole-genome sequencing data) is unlikely to be informa- tive for most people who have a so-called average risk of developing an addiction disorder” [7]. This reflects a fundamental misunderstanding of polygenic risk. It is true that a large number of risk alleles are involved, and that the explanatory power of currently available polygenic risk scores for addictive disorders lags behind those for e.g., schizophrenia or major depression [47, 48]. The only implication of this, how- ever, is that low average effect sizes of risk alleles in addiction necessitate larger study samples to construct polygenic scores that account for a large proportion of the known heritability. However, a heritability of addiction of ~50% indicates that DNAsequence variation “THE MAIN OBJECTIVE OF IMAGING IN ADDICTION RESEARCH IS NOT TO DIAGNOSE ADDICTION, BUT RATHER TO IMPROVE OUR UNDERSTANDING OF MECHANISMS THAT UNDERLIE IT. THE HOPE IS THAT MECHANISTIC INSIGHTS WILL HELP BRING FORWARD NEW TREATMENTS, BY IDENTIFYING CANDIDATE TARGETS FOR THEM, BY POINTING TO TREATMENT- RESPONSIVE BIOMARKERS, OR BOTH.”