What Have We Learned About the Genetics of Obsessive-Compulsive and Related Disorders in Recent Years?

Obsessive-compulsive disorder (OCD) is a complex genetic disorder with a lifetime prevalence of 2%−3% (1). Onset of OCD symptoms usually begins in adolescence and early adulthood, with most individuals having onset in late adolescence. In up to one-half of all adult cases, a childhood onset has been reported (2). OCD is a chronic disorder across the lifespan and is one of the leading global causes of nonfatal illness burden (3). OCD seems to be equally prevalent among males and females in clinical samples, although studies in community samples suggest that OCD is more common among females (1). This lack of prevalence differences by gender in some international studies has also been noted. However, females may experience onset or worsening of symptoms during pregnancy or during the period before menstruation and males seem to show an earlier onset. Thus, more studies are warranted to explore potential gender differences in prevalence (1).

As we stated in a previous article (4), other disorders are closely related to OCD, as recognized in DSM-5 and by Goodman (3), who wrote

Similarly, ICD has introduced a chapter on OCRDs in its new revision (ICD-11), although hypochondriasis, olfactory reference syndrome, and Tourette syndrome (TS) are included in the grouping (5). Reclassification of these disorders in DSM-5 and ICD-11 not only recognizes shared symptom domains but also reflects slowly growing evidence coming from molecular studies. Comorbidity of OCRDs with anxiety disorders, depression, bipolar disorder, schizophrenia, substance use disorders, attention-deficit hyperactivity disorder (ADHD), and other impulse control disorders has also been recognized. However, little is known about shared genetic risks, and genome-wide association studies (GWASs) and other molecular studies only slowly start to paint a clear picture.

In this article, we summarize recent findings on the genetics of OCRDs. However, we also feel obligated, keeping with the tradition set by our earlier article (4), to provide context with regard to general concepts and study designs in order to give a broader readership the opportunity to follow this summary. Therefore, we updated and rephrased some parts of the original version; however, there are still many similarities, because the concepts have not changed much over time. Furthermore, we include information about recent findings in our summary—findings that were mentioned previously (4). This is the case when, to date, there is no additional or newer information available. We chose this option for the article in order to have all recent information available in one place.

OCRDS Are Complex Multifactorial Disorders

As noted previously (4), OCRDs, like all neuropsychiatric disorders (e.g., schizophrenia and major depression) and most common nonpsychiatric disorders (e.g., non–insulin-dependent diabetes and asthma), are viewed as genetically complex, multifactorial disorders. The term “complex” refers to the fact that it is unlikely that a major single genetic variation predisposes to or directly causes the disorder; rather, many changes in the genome may make minor contributions to disease risk, and the combination of such changes is likely to vary between individuals and populations. The term “multifactorial” refers to the fact that changes in the genetic code alone do not cause disease; rather, a combination of genetic and environmental (risk) factors most likely underlies causation.

Schizophrenia is a good example of a complex, multifactorial neuropsychiatric illness for which the genetic contribution is slowly being elucidated. Most recently, a whole-genome (i.e., all the DNA/genes in an organism) study identified approximately 150 different genomic regions as contributing to the disease (6). In almost all instances, the exact mutations in these regions have not yet been identified. Although these results are promising, the approximately 150 regions collectively explain only about 20% of the risk of schizophrenia. The remaining more than 80% may involve additional genes, genetic processes, or environmental or other shared or nonshared (random) risk factors. Some of these have recently been identified among so-called rare coding variants (7) and copy number variants (8), both representing a different group of genetic variation compared with so-called common variation (see below). The goal of all genetic studies is to tease out what proportion of the representation of illness (including risk of onset and other clinically relevant parameters) is likely to be genetic (as opposed to environmental or random) and, ultimately, to identify specific causative variations.

Historically, twin and family studies have been conducted to demonstrate that there are genetic contributions to a disorder. Genomic studies in which the DNA sequence is examined directly (or indirectly) are used to identify genomic regions shared by affected versus nonaffected relatives or, in studies of unrelated cases and unrelated controls, by cases more than controls. A case-control whole-genome design was used in the aforementioned schizophrenia study (6). In all such studies, the disease entity (i.e., phenotype) of interest must be specified. For example, some studies use only a narrow disease definition (e.g., a single disorder, such as OCD or TS), whereas others use a broad definition, often an entire spectrum (e.g., all OCRDs together). These types of studies not only can identify associated genes/regions for a specific disorder but also can help elucidate the relationship of genetic liability for one disorder to another (e.g., does TS share the same genes/regions as OCD?).

Another approach to phenotypic description involves specific features or disorder dimensions (e.g., neuropsychological, neuroanatomical, and neurocognitive) that cut across traditional disease boundaries and that are sometimes referred to as endophenotypes. The focus is on objective and heritable traits that are part of the etiology or representation of a trait but not necessarily specific to it. An endophenotype is presumed to be an intermediate in the causal chain between the observed behavioral phenotype and the underlying (biological) cause. For example, performance on neurocognitive tests may be used to tease out some of the differences that may be attributable to genetic variability between patients with OCD, their first-degree unaffected relatives, and unrelated healthy controls. These phenotypes will be an increasingly important component of genomic studies as more stable, heritable endophenotypic traits are identified (9).

Twin and family studies as well as genome-wide studies have been conducted in OCD, TS/chronic tics, and other related disorders. Most studies have been performed on the OCD or TS/chronic tics phenotypes (few studies using symptom dimensions or endophenotypic end points have been conducted to date). In addition to genome-wide studies, analyses of particular genes that may be plausibly involved in disease causation or that may influence the effectiveness of pharmacologic treatments (i.e., “candidate genes”) have been performed. Animal models derived from gene knockouts, biochemical manipulations, or innate characteristics (i.e., naturally occurring) have also been investigated. Excellent reviews of the literature on the genetics of OCD and TS, including twin, family, and genome-wide case-control studies, were recently published (10–12). Likewise, d’Angelo et al. (13) authored an excellent review of OCD animal models. Below we present a summary of recent findings.

Twin and Family Studies

As noted previously (4), twin and family studies are commonly used tools to describe and dissect the etiology of (common) disorders. Twin studies are used to study the question of nature versus nurture—i.e., what proportion of the phenotype variation is attributable to genetic factors in contrast to environmental factors? To do that, twin studies examine the concordance of disease in monozygotic (identical) twins versus dizygotic (fraternal) twins. Because monozygotic twins share all their genes and dizygotic twins share only one-half of their genes on average (similar to any other pair of siblings), rates of co-occurrence of disease in both monozygotic twins compared with dizygotic twins can be used to estimate heritability, i.e., the proportion of phenotypic variation that can be attributed to genetic factors. Family studies, on the other hand, are used to study recurrence risks in family members—i.e., the likelihood that a disease or trait present in one family member will occur again in other family members. Although inherently similar concepts, heritability and recurrence risk have different clinical utility.

Twin Studies (Monozygotic Versus Dizygotic Twins)

Most studies of monozygotic versus dizygotic twins have used only OCD as the phenotype, but some studies have included related disorders or specific OCD symptom dimensions. Almost all studies to date have used either data from questionnaires (such as the Obsessive-Compulsive Inventory, revised version, or the Yale-Brown Obsessive Compulsive Scale) or categorical phenotypes that preceded publication of DSM-5. OCD twin studies have consistently found heritability estimates around 50% (e.g., Mataix-Cols et al. [14])—i.e., around 50% of the phenotypic variation in OCD is attributable to genetic factors. Few studies have been performed on hoarding disorder (HD), BDD, trichotillomania (TTM), and skin-picking disorder (SPD) alone. For HD, the overall heritability was estimated to be 51% (15). For TTM, widely divergent estimates of heritability were derived, ranging from a high of 76% in one study (16) to only 32% in another report (15). SPD has an estimated heritability of approximately 40%−47% based on an initial study as well as a follow-up study (17). BDD heritability has also been estimated to be around 40%, although few studies have been performed (15). For TS, heritability was estimated to be as high as 80% (10). It should be noted that other approaches to calculate heritability sometimes arrive at significantly smaller estimates (18). Although some of these differences can be explained through factors that are inherent to the approaches, other factors still need to be identified. What these studies have in common, though, is that information about heritability does not tell the whole story. As outlined above, many (also nongenetic) factors contribute to disease risk, and a high amount of variation in phenotype explained through genetic factors does not imply a (genetic) determination (19). Furthermore, a large heritability does not (necessarily) imply genes with large effects but likely is related to the degree of polygenicity that a trait or disorder shows (19). In other words, a high heritability of a trait or disorder in complex trait genetics is likely rooted in the large number of genomic loci (with individually small effects) that additively act together to cause disease risk. This can be commonly found in psychiatric illnesses and is also the case for OCRDs.

Family Studies

For OCD, first-degree relatives (i.e., biological parents, full siblings, and offspring) who share on average 50% of their genomes have an estimated recurrence risk between 10% and 20% based on studies performed over the past decade or so that have used more modern disease criteria (studies in the early 1980s showed higher risks). Some studies used only OCD as the phenotype of interest, whereas others used a broader definition that included subdiagnostic OCD symptoms. In general, the broader the phenotype definition, the greater the recurrence risk (20). Researchers have particularly focused on the subset of patients with early-onset OCD. Higher recurrence risks of OCD in first-degree relatives of pediatric-onset versus adult-onset cases have been reported, but this finding is not consistent. In addition, some studies that reported increased risk to relatives of pediatric-onset versus adult-onset cases reported increases that were not statistically significant (20, 21).

As reviewed by Browne et al. (20), clustering of TS, chronic tics, TTM, and other disorders in families of individuals with OCD has also been documented. First-degree relatives of patients with OCD have been reported to have recurrence risks of 4%−14% for TS/chronic tics, up to 6% for BDD, 4% for TTM, and around 15% for other compulsive behaviors, such as pathologic skin picking or nail biting. A twin study involving >1,000 female twin pairs (i.e., >2,000 participants) reported substantial (64%) genetic influences between OCD and BDD, with even higher estimates (82%) when BDD and OCD symptom dimensions (and not diagnoses, per se) were analyzed (22). Reciprocal studies that examined the relatives of individuals with OCRDs but not OCD have shown increased risks of OCD for those relatives (20).

Genome-Wide Genetic Studies

After an era of so-called candidate gene studies that overall was found to be rather disappointing in terms of new insights into disease biology of OCRDs, genome-wide studies have become more popular, with decreasing costs and increasing technological advancements. As described above for the schizophrenia example, at least three different types of genetic variation are studied: common variation, copy number variation, and rare (coding) variation. Different study types have been used over the years to examine the different types of variation. Case-control study samples make use of cohorts of nonrelated individuals that are usually defined by presence (cases) or absence (controls) of a phenotype of interest. Family-based studies, on the other hand, are usually centered around a so-called index case (i.e., someone showing the phenotype of interest) and include that person’s relatives, who can either be affected by the disorder or who present themselves without the phenotype. A simple example for a family-based study sample is a so-called trio, an index case together with the parents. There are advantages and disadvantages to both types of studies. In brief, case-control studies allow for a cost-effective identification of disease-associated regions in the genome, whereas family-based studies are sometimes better suited to study disease pathophysiology through the eyes of inheritance. What is common to both approaches is that they usually do not come with a specific hypothesis about the involvement of particular genes or genomic regions; rather, these studies survey the genome for disease association. This is why they are sometimes referred to as “hypothesis-free approaches,” an unfortunate characterization of their nature, because they clearly test a hypothesis—that is, whether genetic markers are associated with disease status.

Common Variation

Although the term “genome-wide association study” (GWAS) technically does not indicate which type of genetic variation is studied, it has lately been mostly associated with studies looking into common variation. The technology that enables studies into common variants is called genotyping. Common variants are genetic markers with a frequency in the general population of >1%. These “markers,” typically so-called single-nucleotide polymorphisms (SNPs), can be used as figurative signposts on a roadway, suggesting that there is a nearby gene/variant that contributes to a difference in risk between individuals with disease and those without. In other words, the marker and the putative disease-associated variant are linked and thereby inherited together. For a marker to be considered statistically significant in a GWAS (usually referred to as being genome-wide significant), its p value needs to be below 5 × 10⁻⁸ corresponding to a correction for 1,000,000 independent tests in the genome.

The first OCD GWAS was recently performed by a broad collaborative group (International OCD Foundation Genetics Collaborative [IOCDFGC]) (23). This study involved 1,465 patients with OCD and 5,557 ancestry-matched controls (the case-control part of the study). The study also included 400 so-called trios composed of an affected child and parents or genetically related parental surrogates (the family-based part of the study). A second collaborative study, the OCD Collaborative Genetics Association Study (OCGAS), included 1,406 cases from 1,065 families; thus multiple affected members of the same family were included (24). Although neither of these two GWASs identified unequivocal findings, it is noteworthy that there was some overlap when the genes/markers with the best evidence of association in the IOCDFGC study were compared with the OCGAS analysis. This suggests that a subset of these markers/genes may truly be associated with OCD. Although this observation was confirmed in a recent meta-analysis of the two study samples (performed by the Psychiatric Genomics Consortium [PGC] TS/OCD working group), analyzing both studies still did not reveal a stable genome-wide significant genomic region (25). A new study enrolling around 15,000 individuals diagnosed as having OCD has reported a new genome-wide significant locus on chromosome 3p21.1 for OCD (Strom NI, Yu D, Gerring ZF, et al., unpublished manuscript, 2021).

A recent meta-analysis of an adult sample with obsessive-compulsive trait phenotypes and the samples of IOCDFGC study and OCGAS—i.e., samples with categorical OCD phenotypes—did not reveal a genome-wide significant association (26). In contrast, another recent study that used pediatric obsessive-compulsive trait phenotypes identified a genome-wide significant region in the genome that included the PTPRD gene, which had been previously highlighted in the OCGAS (27). Both studies (Smit et al. [26] and Burton et al. [27]), however, found that a substantial proportion of the genetic liability for the trait and categorical phenotypes overlapped (60%−70%). The PGC TS/OCD working group is currently working on GWASs on obsessive-compulsive trait phenotypes (including, among other traits, hoarding), which will be based on large national twin samples in Europe.

Other GWASs in the OCRD spectrum (see ICD-11) include GWASs on TS. The most recent GWAS by the PGC TS/OCD working group included 4,819 individuals diagnosed as having TS and 9,488 individuals without such a diagnosis (28). GWAS and gene-based analyses identified one genome-wide significant locus within FLT3, although this association was not replicated in a population-based sample comprising 706 cases and 6,068 controls (28). The PGC TS/OCD working group is currently working on a new TS GWAS that includes samples from large genetic consortia in Europe and the United States and that will include, for the first time, more than 10,000 cases. Other GWASs for OCRDs, e.g., for TTM, are currently being conducted, and results are expected to be published soon.

Copy Number Variation

In contrast to SNPs, copy number variants (CNVs) are regions in the genome that have more (duplication) or less (deletion) copies than an individual normally inherits from its parents (two copies, i.e., one copy from the mother and one copy from the father). CNVs often confer risk for more than one disorder and typically are less frequent—most of the time with a frequency below 1%. Similar to other mental illnesses, OCRDs are more common among individuals diagnosed as having rare genetic disorders associated with CNVs (e.g., the 22q11.2 microdeletion syndrome [29]). In recent years, studies specifically conducted to identify CNVs in OCRDs have identified, among others, a collagen gene (COL8A1) as well as a gene (NRXN1) that has been associated with other neurodevelopmental disorders (30). Further studies are necessary to verify and extend these findings.

Rare (Coding) Variation

Finally, rare (coding) variations are a class of genetic variation that has increasingly been found to be associated with OCRDs. In contrast to common variants, rare (coding) variants are less frequent in the general population (<1%). Typically, these variants are studied by using a technique that is called sequencing. Similar to CNVs, rare (coding) variations tend to be associated with more than one mental illness. A recent targeted rare (coding) variant study integrating evolutionary and regulatory information identified, among other genes, NRXN1 to be genome-wide significant (31). As mentioned above, NRXN1 has been previously implicated in the etiology of other neurodevelopmental disorders (see, for example, Gudmundsson et al. [32])

To date, sequencing studies at a genome-wide scale are less frequently conducted in OCRDs, compared with, for example, schizophrenia or autism spectrum disorder. Nevertheless, early studies have identified an enrichment of rare (coding) variants in individuals diagnosed as having OCD, compared with individuals without the diagnosis (e.g., Cappi et al. [33] and Halvorsen et al. [34]). Individual results pinpointing specific genes should still be interpreted with some caution until these findings have been replicated in larger studies. However, these findings match observations using data from GWAS data sets that suggest that some of the genetic risk of developing OCD comes from rare (coding) variants (35). The largest study to date, with around 1,300 individuals enrolled, among other findings, found that so-called de novo mutations—i.e., mutations that are not inherited from the parents but that occur “new” in the offspring—are significantly associated with OCD (34).

Observations similar to those for OCD have been made for other OCRDs. In TS, for example, recent studies have identified the first putative genetic locations (genes) that potentially harbor disease-causing mutations (36, 37). Although still waiting for replication in larger studies, these findings highlight the potential of studying rare (coding) variation in OCRDs.

Epigenetic Studies

As noted previously (4), in addition to direct changes in DNA sequence that may disrupt normal gene activity, other types of variation can affect how genes play their role in the etiology of some disorders (including OCRDs). The term “epigenetics” usually refers to external modifications to DNA that can alter when and how much of a gene’s product is produced (i.e., expressed). It is important to understand that epigenetic changes do not alter the actual DNA sequence itself but do affect gene regulation and expression. Types of epigenetic mechanisms are of long-term or short-term consequence and include, among others, X-chromosome inactivation, genomic imprinting, chromatin remodeling, and gene expression regulation through microRNAs. Among different types of chromatin remodeling are histone modifications. Similar to variations in the DNA sequence, epigenetic modifications can be heritability transmitted; however, in many cases they are the consequence of lifestyle factors (e.g., diet, smoking, and physical activity) and environmental influences (e.g., different kinds of pollution), as well as downstream consequences of other illnesses (e.g., inflammation). Data on epigenetic changes in OCRDs are emerging and suggest that expression of certain genes in the brains of patients with OCD may be affected, but no statistically significant, replicated findings have been published.

Studies Across Diagnostic Boundaries

In the above sections, we have focused on studies that were designed to identify disease-associated genetic markers with one disorder in mind. Although inherently capable of identifying genetic markers that are associated with more than one disorder, these studies typically focus on designs that include cases or family members with one specific disorder. Cross-disorder analyses, on the other hand, usually focus on more than one disorder and are designed to look across diagnostic boundaries. They achieve this by including either individuals who are diagnosed with more than one disorder (so called comorbid cases) or cohorts that are each focusing on a different disorder of interest. Cross-disorder analyses can be conducted with disorders that are closely related (e.g., OCRDs) or with disorders that have a known (clinical or epidemiological) relationship but are not closely related by means of a diagnostic manual (e.g., internalizing disorders and asthma). It is of note that results from current cross-disorder analyses typically do not take any causal relationship between disorders into account, nor can causal relationships in the genetic etiology for these disorders be typically inferred from the analyses. However, there is a growing trend to conduct studies employing approaches that allow for these interpretations (see end of section).

Cross-disorder analyses have been performed within the OCRD spectrum, most prominently for OCD and TS/chronic tics. The most recent analyses suggest a relationship in which there are shared but also distinct genetic components to each disorder (38, 39). This is an observation that has been shared across a variety of mental illnesses—i.e., many (closely related) disorders share part of their genetic risk architecture (see also above in the sections about CNVs and rare [coding] variants). However, their risk architecture also involves genetic loci that are uniquely associated and are not shared with other mental illnesses. For OCD and TS, the analysis by Yu et al. (39) showed that OCD with co-occurring TS or chronic tics may have a different underlying genetic susceptibility, compared with OCD alone. This is in line with a recent analysis in a Danish population-based sample that identified distinct patterns of genetic correlations for other disorders depending on whether individuals with an OCD diagnosis had also been diagnosed as having autism, ADHD, or major depressive disorder (40).

On a larger scale, recent cross-disorder analyses have tried to identify shared and unique associations across multiple mental illnesses, including OCRDs (usually OCD and TS). They have identified a number of genome-wide significant genetic loci that seem to be shared between mental illnesses, such as schizophrenia, autism, and ADHD, but also between OCD and TS (41). However, because of their own limited sample size (see above), the evidence for the association for OCD and TS with these loci still requires replication or at least future samples that include more individuals diagnosed as having OCRDs (see below). Nevertheless, one recent set of cross-disorder analyses borrowed its statistical approaches from other fields (such as epidemiology and sociology). The advantage of these approaches lies in their ability to model complex relationships between the genetic etiologies of the disorders under study, up to the point that the causal relationship in their respective genetic risk architectures can be inferred. An example of such an analysis was reported by Grotzinger et al. (42), who studied a compulsive disorder factor (among other factors) in their recent GWAS. One genome-wide significant genomic locus on chromosome 3p21.31 was identified to be associated with the compulsive disorder factor. This region was also among the genetic loci that the above-mentioned cross-disorder analyses (41) identified across multiple mental illnesses, including TS and OCD.

Need for Larger Sample Sizes

The complexity of OCD and its relationship to other OCRDs, such as TS/chronic tics, HD, BDD, TTM, and SPD, have been formally recognized in DSM-5; however, identifying the nature of the underlying genetic predisposition to these disorders may be both helped and hampered. Heterogeneity within and between the disorders (e.g., specific symptoms, symptom severity, comorbidities, and early versus late onset), population variation (e.g., sex and race-ethnicity), probable involvement of many genes (possibly hundreds) each with small effects (“polygenicity”) provide just some challenges for investigators. The interplay of known and unknown environmental factors with each other or with genetic factors (or both) creates additional hurdles for investigators. One clear principle, however, guides the field: the larger the sample and the more phenotypic descriptors available (e.g., comorbidity or endophenotypes), the more likely the identification of genetic contributions and ultimately the unraveling of the etiology. This has been demonstrated for schizophrenia, in that GWASs in recent years have found six genome-wide significant hits with approximately 10,000 cases, 62 hits with 25,000 cases, and 128 at the current 36,989 cases with schizophrenia (43–45). It must be noted, however, that although this relationship usually holds true across mental illnesses, the sample size at which successful identification of genome-wide significant loci is possible varies between disorders. The same is true for the pace (i.e., the number of genome-wide significant hits per added constant number of samples) at which we learn more about the genetic risk factors that influence risk the risk of developing a disorder of interest. For major depressive disorder, for example, an earlier GWAS with 9,240 cases was not able to identify a genome-wide significant association (46), and a recent analysis of 135,458 cases identified 44 genome-wide significant loci (47), falling significantly short of the 128 loci identified for schizophrenia, with a sample size roughly four times smaller. This is not to say that these disorders are, per se, less “genetic” (although that might be the case for some); it merely could mean that their “risk architecture” might be different and that other approaches—e.g., those looking for rare (coding) variation, CNVs, or epigenetic factors—might require an increase in sample size to learn more about the etiology of the respective disorder. The PGC TS/OCD working group and other groups around the globe are narrowing in on sample sizes that are required to identify genome-wide associated loci for OCRDs (TS, OCD, and others).

Current and Future Directions

Studies of the genetic underpinnings of OCRDs have come a long way in recent years. Although the field still needs to catch up with scientific efforts in phenotypes, such as schizophrenia, bipolar disorder, and major depressive disorder, much has happened. Coming from an era in which genetic research in OCRDs was badly underfunded, we now see multiple large-scale studies funded for common and rare variation (48, 49). These efforts, together with existing large-scale biobanks and cohort studies, will help us within the next year to reach approximately 60,000 cases enrolled in genetic studies of OCD and it is hoped within the next 5 years even 100,000 cases. This will also be made possible with an extension of efforts from U.S.- and Europe-centric data collections into South America and countries in South and East Asia as well as in Africa. Currently, some of these efforts are either on the brink of receiving funding or are funded through both institutional and national programs. This seems important not only because of cultural influences on phenotypes such as OCD (50) but also because of the necessity to make sure that we are not falling further behind on the principles of equity, diversity, and inclusion (EDI). Among other articles, a recent overview article has outlined that the principles of EDI are not self-serving but will mark the cornerstones of our efforts to translate current genetic findings into treatments and clinical care (51). This holds true not only for GWASs but also for studies that target rare (coding) variation, CNVs, epigenetic changes, and other risk factors for OCRDs.

With regard to these translation efforts, pharmacogenomics is leading the field in OCRDs. The influence of genetic markers on antidepressant response in OCD has long been demonstrated (52). Although earlier studies of treatment response prediction focused on well-described markers that are known to affect the metabolization of antidepressants (e.g., CYP2D6), newer studies focus on larger sets of markers (53). Beyond pharmacogenomic approaches, the interplay of genes and the environment has also been used to study the response to treatment in OCD (54). On the genetic side, so called polygenic risk scores (PRS) have been included in these studies (54). PRS are a measure of the genetic vulnerability a person carries to develop a certain phenotype. In contrast to single SNPs, the effects of which are usually small on their own, PRS represent the accumulated risk across a group of SNPs that are associated with a phenotype. We are only at the beginning of a long road that leads from PRS as a research tool to clinical instruments (55, 56), but some argue that this road leads to nowhere. First studies, however, suggest that although not informative in their own right, PRS might have the ability to aid decision making in settings where other sources of information (e.g., diagnostic tools, classical pharmacogenetic testing, and imaging) have already set the tone for downstream treatment and care (55). Before this can happen, however, at least two steps need to be taken or completed: diversification of current study samples and clarification of studied phenotypes.

We have discussed the need to follow EDI principles, but we would like to reiterate the importance of doing so. Without proper inclusion and diversification, we are at an increased risk of entering a new era of stigmatization and discrimination toward those in our society who are already at an increased risk of developing mental illnesses and a decreased likelihood of receiving proper care.

In an environment of classification systems and strict guidelines for diagnoses, the request for clarification of studied phenotypes might sound like a request for more accurate phenotypes—it is not. Generally, individuals who have been diagnosed as having an OCRD and who have been included in a genetic study do have an OCRD. However, this “diagnosis” of an OCRD is not the only characteristic of their illness. They might be mildly affected or severely affected, their illness might have started at a relatively early age or they might have developed their illness in adulthood, and they might have been diagnosed as having another mental illness or they might not show any comorbidities. All these characteristics of their illnesses have roots in their genes. As a consequence, results from studies that focus, for example, on individuals diagnosed as having severe OCD can likely in a new study distinguish those with more severe OCD from controls. However, such studies will be less well equipped to distinguish those with a milder form of OCD from controls. Recent studies have shown exactly this issue for other mental illnesses, such as schizophrenia (57) and major depressive disorder (47). Therefore, it seems of outmost importance to be clear on all characteristics of the case and control cohorts enrolled in a study. Furthermore, this issue of severity points to the need to carry out genetic research across the phenotypic spectrum in OCRDs and not only include individuals who are severely affected by the disorders. Studies of healthy individuals with trait phenotypes related to mental illnesses (e.g., captured through self-report questionnaires) are as important as studies into the most severely affected (e.g., patients without treatment response in need of deep brain stimulation) if we want to achieve our goals of early detection and prevention. First studies have been conducted on the overlap between obsessive-compulsive trait phenotypes and OCD (26, 27); more studies across the OCRD spectrum (and in diverse samples) will need to follow in order to bring us closer to personalized prevention, care, and medicine.

We encourage all clinicians to stay abreast of research efforts through organizations and worldwide research efforts, such as the International OCD Foundation and the PGC. Furthermore, we encourage clinicians to inform themselves and their patients of resources and research studies available through such organizations and efforts (www.iocdf.org and www.pgc-ts-ocd.info).