There are several recent examples of adequately powered genome-wideassociation studies of endophenotypes. For example, impulsivity, which has been defined as “actions which are poorly conceived, prematurely expressed, unduly risky or inappropriate to the situation, and that often result is undesirable consequences”appears to meet the criteria for an endophenotype for multiple psychiatric disorders, including attentiondeficit/hyperactivity disorder and several substance use disorders . Numerous genetic studies have now shown that various measures of impulsivity and sensation seeking are heritable and that they are genetically correlated with both ADHD and various substance use related traits. In addition, risk tolerance , which has also been proposed as an endophenotype for both ADHD and substance use disorders, was recently measured in over one million individuals . Although risk tolerance was measured using a minimal phenotype , risk tolerance was clearly heritable and the large sample size allowed identification of 124 genome-wide significant loci. Some of these loci have also been implicated in clinically defined traits. Furthermore, risk tolerance was positively genetically correlated with numerous clinically relevant traits . This study illustrates the power of minimal phenotyping to capture an endophenotype that informs complex disorders and also conforms to the RDoC framework. In a third example, Ibrahim-Verbaas et al performed a GWAS for executive function, which can be considered an endophenotype for multiple psychiatric traits. Intriguingly, GWAS of sensation seeking, risk tolerance18 and executive function all identified a locus that included the gene CAMD2, which was subsequently associated with AUD9 . Whether all of these associations are due to a single locus or multiple loci is far from clear,drying room but the index SNPs for these studies are typically co-inherited , consistent with a single causal locus.

Another example of an intriguing endophenotype is self-reported loneliness , which is a strong predictor of mortality and life satisfaction and appears to precede the onset of MDD. Several recent GWAS of loneliness have identified several significant loci and shown that a genetic predisposition to loneliness is genetically correlated with psychiatric, cardiovascular, and metabolic disorders. By assigning polygenic risk scores to individuals for whom electronic medical records were also available, Dennis et al showed that genetic liability for loneliness increased the risk to develop coronary artery disease more robustly than MDD. Thus, loneliness is an endophenotype that is relevant to both MDD and a variety of somatic disorders. While some endophenotypes may be amenable to minimal phenotyping, others represent extremely deep and rich data types. For example, by passively collecting data from wearable devices and smartphones, certain endophenotypes relevant to psychiatric disorders can be measured. In a recent GWAS of circadian rhythm, wearable devices were used to gather objective measures of sleep timing, duration and quality. More recently, structural connectivity from fMRI was proposed as endophenotype for IQ. Elliott et al used 3,144 functional and structural brain imaging phenotypes from UKB to conduct GWAS that identified novel associations that included genes relevant to brain development, pathway signaling and plasticity.The approach we are proposing will be orthogonal to the efforts of the PGC because RDoC traits and endophenotypes “split” diagnostic categories into discrete units of analysis. The SUD field provides a good example of how a complex disorder can be split into smaller, more biologically meaningful units. SUD develop in accordance with an obligate longitudinal pattern: drug experimentation → regular use → harmful use → transition to compulsive use → quit attempts → relapse . Approaching SUD with a case control framework merges the genetic liability for each of these stages into a single phenotype, obscuring the distinct biological factors relevant at each stage.

In contrast, several recent projects have focused on individual stages of SUD, whichcan help to address this limitation. For example, GSCAN used data from almost 1 million individuals to examine a number of SUD-related traits, including smoking initiation48. In another example, the genetic relationship between alcohol consumption and AUD was explored using the AUDIT, a 10- item questionnaire that measures alcohol use and misuse. By dissecting the genetic contribution for alcohol consumption vs problematic use , Sanchez-Roige et al and Kranzler et al showed a surprisingly low correlation between alcohol consumption and AUD ; however, the correlation between problematic alcohol use and AUD was stronger. Even when the temporal stages of a psychiatric disorder cannot be so clearly delineated, it can be helpful to split diagnoses into endophenotypes that are associated with the disease of interest. For example, a recent GWAS of insomnia, which is a core symptom of multiple psychiatric disorders and a DSM criterion for MDD, identified 202 loci and showed strong genetic correlations with MDD and several other psychiatric conditions . Similarly, neuroticism, which shares a common genetic basis with MDD but can be more easily measured, could serve as a clinical stratifying factor for antidepressant actions. However, it can be difficult to determine what level of dissection is required; a recent study suggested that neuroticism reflected two genetic dimensions, one capturing depressed affect, and another capturing worry. Another example comes from several GWAS of impulsive personality, which has been proposed as an endophenotype for several psychiatric disorders including ADHD. The UPPS-P is a self-reported questionnaire that measures 5 different aspects of impulsive personality. Only two of those five were significantly associated with ADHD; in contrast, all three sub-scales of BIS-11, which is another impulsive personality questionnaire, were significantly associated with ADHD. These examples illustrate how disease phenotypes can be dissected into component parts.

Nonetheless, despite the original claim that endophenotypes would have a simpler genetic architecture, all studies conducted to date have shown that both disease diagnoses and endophenotypes are highly polygenic. Once the traits that reflect domains of normal function have been measured in genotyped cohorts, it becomes possible to explore their empirical relationships with one another beyond those that are already defined by traditional psychiatric nosology . Genomic SEM27 and related techniques are now being used in a number of such efforts. Luningham et al used genomic SEM to test multiple models of psychopathology among fourteen psychiatric disorders and related traits. They identified three factors , and an uncorrelated Neurodevelopmental Disorders factor. These factors showed distinct patterns of genetic correlations and accounted for substantial genetic variance. These empirically identified clusters may provide better targets for GWAS than individual disorders. In another example, Baselmans et al showed that it was possible to increase power by using Genomic SEM to integrate multiple traits into a measure of “well-being spectrum”. By aggregating data from different sources of correlated traits, they reached a sample size of over 2.3 million individuals, which allowed them to identify 304 independent signals associated with well-being; a similar analysis suggested a two factor model that distinguishes “lower end” and “higher end” well-being factors. In a third example, Thorp et al used Genomic SEM to identify two factors, which they referred to as “psychological” and “somatic” from the 9-item Patient Health Questionnaire . Recently, several related methods have been developed . Using RGWAS, Dahl et al proposed a stress sub-type in MDD, and identified three novel sub-types of metabolic traits. Using BUHMBOX , Han et al found that seropositive and seronegative rheumatoid arthritis could be subdivided to form a new subgroup within seronegative-like cases. Conversely, they identified a genetic correlation between MDD and SCZ, but there was no evidence that this correlation was due to subgroup heterogeneity.Clumping has been used to test the hypothesis, originally suggested by twin studies,trimming marijuana plants that psychiatric disorders share a single common genetic factor. One of the earliest studies to use GWAS data to test this hypothesis showed that SNPs associated with schizophrenia were also associated with bipolar disorder. Specific genes have been identified that confer risk for multiple psychiatric disorders . Evidence that the risk for substance abuse is shared across multiple substances is also consistent with earlier results from twin studies showing both substance-specific and substance-independent genetic risk. An example of this genetic overlap is the gene CADM2, which has been associated several substances and risky behavior. Joint analysis of correlated traits may outperform that of single phenotypes and allows the possibility to disentangle genetic effects that are specific to each trait from those that capture a latent construct . Clumping can also lead to new splits. For example, Bansal et al used GWAS results from two correlated traits: schizophrenia and educational attainment to propose two distinct etiologies of schizophrenia, one that resembled bipolar disorder and was characterized by high education, and another that reflected a cognitive disorder and was independent of education. Studies like this one provide greater flexibility to explore the phenotypic space, which can lead to novel insights and challenge established nosologies.Throughout this perspective, we have alluded to GWAS producing novel biological insights; however GWAS have numerous limitations65 and do not themselves produce actionable new knowledge.Indeed, a recent meta-analysis indicated that among those with ED, the lifetime prevalence rate of a comorbid SUD was 21.9% . Tobacco, caffeine, and alcohol are reported as the most prevalent SUDs for individuals with EDs . Sedatives, cannabis, stimulants, and over-the-counter products such as laxatives, diuretics, and diet pills are also commonly abused . Research suggests that ED patients with co-occurring SUDs experience lower rates of treatment response, higher relapse rates, more severe medical complications, greater impairment, poorer long-term outcome, and are at higher risk of early mortality .

Given the high-risk nature of individuals with co-occurring EDs and SUDs , and poor outcomes associated with their treatment, it is important to identify whether effective treatment interventions for this population. A major barrier to identifying treatment targets for ED-SUD is the paucity of research comprehensively characterizing the treatment-seeking ED-SUD patient population. Below, we outline the existing literature characterizing ED-SUD and associated features.Separately, EDs and SUDs have the highest and second-highest mortality rates of all psychological disorders . Both EDs and SUDs often present with comorbid mood disorders, anxiety disorders, post traumatic stress disorder , and borderline personality disorder . Becker and Grilo found that among patients with binge eating disorder , those with both mood and substance use disorders had the most severe ED symptoms, and higher rates of personality disorders. In a retrospective chart review, Kirkpatrick et al. found that for adolescents with ED, those with comorbid SUD had higher rates of self-harm and purging, and had a higher BMI at intake. Finally, a small study of an inpatient sample showed that those with ED-SUD were more likely to be diagnosed with a Cluster B personality disorder compared with those with ED alone . ED Diagnosis. Several studies have investigated whether co-occurring SUD is more common in anorexia nervosa-restricting type , anorexia nervosabinge-purge type , or bulimia nervosa. Theoretically, it is believed that binge-purge behaviors are more closely linked to substance abuse, as there is evidence for an increased association between these behaviors and impulsivity and emotion regulation difficulties . One large study found that within ED patients, BN, and AN-BP patients had the highest prevalence of comorbid substance use, whereas AN-R participants generally had the lowest . Root et al. found that across eating disorder groups, the BN and AN-BP groups were more likely to report alcohol abuse and diet pill use relative to the AN group, and the AN-BP group was more likely than the AN-R group to have alcohol abuse, use diet pills, stimulants, and engage in polysubstance abuse. Along the same lines, Fouladi et al. found patients with BN used substances with higher frequencies compared to patients with ANR, BED, and EDNOS, and those with AN-BP were more likely to use substances than those with AN-R. Moreover, higher frequencies of binge eating and purging were associated with higher frequencies of substance use. Finally, a meta-analysis on this topic by Bahji et al. revealed that prevalence rates of SUD were significantly higher among individuals with binge-purge behaviors than those with only restrictive behaviors.Temperament and underlying emotion regulation difficulties serve as common risk and maintenance factors for EDs and SUDs. Recent research provides compelling support for theories of emotion regulation to explain the co-occurrence of disordered eating and substance abuse . Specifically, these theories posit that individuals engage in these maladaptive coping strategies to alleviate negative affect . In support of this, existing findings indicate that affective instability, impulsivity, negative urgency, and novelty seeking are common in individuals with EDs who engage in substance abuse . For example, a study investigating temperament found that binge eating was associated with increased impulsivity and risky decision-making .