Psychiatric genetics and the structure of psychopathology

For over a century, psychiatric disorders have been defined by expert opinion and clinical observation. The modern DSM has relied on a consensus of experts to define categorical syndromes based on clusters of symptoms and signs, and, to some extent, external validators, such as longitudinal course and response to treatment. In the absence of an established etiology, psychiatry has struggled to validate these descriptive syndromes, and to define the boundaries between disorders and between normal and pathologic variation. Recent advances in genomic research, coupled with large-scale collaborative efforts like the Psychiatric Genomics Consortium, have identified hundreds of common and rare genetic variations that contribute to a range of neuropsychiatric disorders. At the same time, they have begun to address deeper questions about the structure and classification of mental disorders: To what extent do genetic findings support or challenge our clinical nosology? Are there genetic boundaries between psychiatric and neurologic illness? Do the data support a boundary between disorder and normal variation? Is it possible to envision a nosology based on genetically informed disease mechanisms? This review provides an overview of conceptual issues and genetic findings that bear on the relationships among and boundaries between psychiatric disorders and other conditions. We highlight implications for the evolving classification of psychopathology and the challenges for clinical translation

Integrative analysis of genomic and exposomic influences on youth mental health

Background: Understanding complex influences on mental health problems in young people is needed to inform early prevention strategies. Both genetic and environmental factors are known to influence youth mental health, but a more comprehensive picture of their interplay, including wide-ranging environmental exposures – that is, the exposome – is needed. We perform an integrative analysis of genomic and exposomic data in relation to internalizing and externalizing symptoms in a cohort of 4,314 unrelated youth from the Adolescent Brain and Cognitive Development (ABCD) Study. / Methods: Using novel GREML-based approaches, we model the variance in internalizing and externalizing symptoms explained by additive and interactive influences from the genome (G) and modeled exposome (E) consisting of up to 133 variables at the family, peer, school, neighborhood, life event, and broader environmental levels, including genome-by-exposome (G × E) and exposome-by-exposome (E × E) effects. / Results: A best-fitting integrative model with G, E, and G × E components explained 35% and 63% of variance in youth internalizing and externalizing symptoms, respectively. Youth in the top quintile of model-predicted risk accounted for the majority of individuals with clinically elevated symptoms at follow-up (60% for internalizing; 72% for externalizing). Of note, different domains of environmental exposures were most impactful for internalizing (life events) and externalizing (contextual including family, school, and peer-level factors) symptoms. In addition, variance explained by G × E contributions was substantially larger for externalizing (33%) than internalizing (13%) symptoms. / Conclusions: Advanced statistical genetic methods in a longitudinal cohort of youth can be leveraged to address fundamental questions about the role of ‘nature and nurture’ in developmental psychopathology

Morphometricity as a measure of the neuroanatomical signature of a trait

Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer’s disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques.National Institute for Biomedical Imaging and Bioengineering (U.S.) (R01EB006758)National Institute for Biomedical Imaging and Bioengineering (U.S.) (P41EB015896)National Institute for Biomedical Imaging and Bioengineering (U.S.) (R21EB018907)National Institute for Biomedical Imaging and Bioengineering (U.S.) (R01EB019956)National Institute on Aging (5R01AG008122)National Institute on Aging (R01AG016495)National Institute of Neurological Diseases and Stroke (U.S.) (R01NS0525851)National Institute of Neurological Diseases and Stroke (U.S.) (R21NS072652)National Institute of Neurological Diseases and Stroke (U.S.) (R01NS070963)National Institute of Neurological Diseases and Stroke (U.S.) (R01NS083534)National Institute of Neurological Diseases and Stroke (U.S.) (5U01NS086625)United States. National Institutes of Health (5U01-MH093765)United States. National Institutes of Health (R01NS083534)United States. National Institutes of Health (R01NS070963)United States. National Institutes of Health (R41AG052246)United States. National Institutes of Health (1K25EB013649-01

Dissociable Genetic Contributions to Error Processing: A Multimodal Neuroimaging Study

Background: Neuroimaging studies reliably identify two markers of error commission: the error-related negativity (ERN), an event-related potential, and functional MRI activation of the dorsal anterior cingulate cortex (dACC). While theorized to reflect the same neural process, recent evidence suggests that the ERN arises from the posterior cingulate cortex not the dACC. Here, we tested the hypothesis that these two error markers also have different genetic mediation. Methods: We measured both error markers in a sample of 92 comprised of healthy individuals and those with diagnoses of schizophrenia, obsessive-compulsive disorder or autism spectrum disorder. Participants performed the same task during functional MRI and simultaneously acquired magnetoencephalography and electroencephalography. We examined the mediation of the error markers by two single nucleotide polymorphisms: dopamine D4 receptor (DRD4) C-521T (rs1800955), which has been associated with the ERN and methylenetetrahydrofolate reductase (MTHFR) C677T (rs1801133), which has been associated with error-related dACC activation. We then compared the effects of each polymorphism on the two error markers modeled as a bivariate response. Results: We replicated our previous report of a posterior cingulate source of the ERN in healthy participants in the schizophrenia and obsessive-compulsive disorder groups. The effect of genotype on error markers did not differ significantly by diagnostic group. DRD4 C-521T allele load had a significant linear effect on ERN amplitude, but not on dACC activation, and this difference was significant. MTHFR C677T allele load had a significant linear effect on dACC activation but not ERN amplitude, but the difference in effects on the two error markers was not significant. Conclusions: DRD4 C-521T, but not MTHFR C677T, had a significant differential effect on two canonical error markers. Together with the anatomical dissociation between the ERN and error-related dACC activation, these findings suggest that these error markers have different neural and genetic mediation

A Cross-Sectional Study of Dietary and Genetic Predictors of Blood Folate Levels in Healthy Young Adults

Since 1998, the U.S. has mandated folic acid (FA) fortification of certain grain products to reduce the risk of neural tube defects. Folate intake and red blood cell (RBC) folate concentrations increased substantially post-intervention, although recent studies raise concerns about the level of ongoing benefit. This study investigated blood folate level determinants in healthy young adults, including intake of naturally occurring food folate, synthetic FA, and the interaction of naturally occurring food folate with a common missense variant in the FOLH1 gene thought to affect absorption. Participants (n = 265) completed the Diet History Questionnaire II, RBC folate testing, and were genotyped for the 484T>C FOLH1 variant. Men reported significantly greater intake of all folate sources except for supplemental FA, but RBC folate levels did not significantly differ by sex. Synthetic FA was a stronger predictor of RBC folate than naturally occurring food folate. In the largest racial group, synthetic FA and the interaction of FOLH1 genotype with naturally occurring food folate significantly predicted RBC folate, with the overall model accounting for 13.8% of the variance in RBC folate levels. Blood folate levels rely on a complex interaction of natural and synthetic folate intake as well as FOLH1 genotype

Multidimensional heritability analysis of neuroanatomical shape

In the dawning era of large-scale biomedical data, multidimensional phenotype vectors will play an increasing role in examining the genetic underpinnings of brain features, behaviour and disease. For example, shape measurements derived from brain MRI scans are multidimensional geometric descriptions of brain structure and provide an alternate class of phenotypes that remains largely unexplored in genetic studies. Here we extend the concept of heritability to multidimensional traits, and present the first comprehensive analysis of the heritability of neuroanatomical shape measurements across an ensemble of brain structures based on genome-wide SNP and MRI data from 1,320 unrelated, young and healthy individuals. We replicate our findings in an extended twin sample from the Human Connectome Project (HCP). Our results demonstrate that neuroanatomical shape can be significantly heritable, above and beyond volume, and can serve as a complementary phenotype to study the genetic determinants and clinical relevance of brain structure.National Institute for Biomedical Imaging and Bioengineering (U.S.) (P41EB015896)United States. National Institutes of Health (S10RR023043)United States. National Institutes of Health (S10RR023401)United States. National Institutes of Health (K25CA181632)United States. National Institutes of Health (K01MH099232)United States. National Institutes of Health (K99MH101367)United States. National Institutes of Health (R21AG050122-01A1)United States. National Institutes of Health (R41AG052246-01)United States. National Institutes of Health (1K25EB013649-01)United States. National Institutes of Health (K24MH094614)United States. National Institutes of Health (R01MH101486

Genome-wide association study of generalized anxiety symptoms in the Hispanic Community Health Study/Study of Latinos

Although generalized anxiety disorder (GAD) is heritable and aggregates in families, no genomic loci associated with GAD have been reported. We aimed to discover potential loci by conducting a genome-wide analysis of GAD symptoms in a large, population-based sample of Hispanic/Latino adults. Data came from 12,282 participants (aged 18–74) in the Hispanic Community Health Study/Study of Latinos. Using a shorted Spielberger Trait Anxiety measure, we analyzed: (1) a total trait anxiety score based on summing responses to all ten items; and (2) a GAD symptoms score restricted to the three items tapping diagnostic features of GAD as defined by DSM-V. We first calculated the heritability due to common variants (h2SNP) and then conducted a genome-wide association study (GWAS) of GAD symptoms. Replication was attempted in three independent Hispanic cohorts (Multi-Ethnic Study of Atherosclerosis, Women’s Health Initiative, Army STARRS). The GAD symptoms score showed evidence of modest heritability (7.2%; p=0.03), while the total trait anxiety score did not (4.97%; p=0.20). One genotyped SNP (rs78602344) intronic to Thrombospondin 2 (THBS2) was nominally associated (p=4.18×10−8) in the primary analysis adjusting for psychiatric medication use and significantly associated with the GAD symptoms score in the analysis excluding medication users (p=4.18×10−8). However, meta-analysis of the replication samples did not support this association. Although GWAS revealed a genome-wide significant locus in this sample, we were unable to replicate this finding. Evidence for heritability was also only detected for GAD symptoms, and not the trait anxiety measure, suggesting differential genetic influences within the domain of trait anxiety

Dopamine Genetic Risk Score Predicts Depressive Symptoms in Healthy Adults and Adults with Depression

Background: Depression is a common source of human disability for which etiologic insights remain limited. Although abnormalities of monoamine neurotransmission, including dopamine, are theorized to contribute to the pathophysiology of depression, evidence linking dopamine-related genes to depression has been mixed. The current study sought to address this knowledge-gap by examining whether the combined effect of dopamine polymorphisms was associated with depressive symptomatology in both healthy individuals and individuals with depression. Methods: Data were drawn from three independent samples: (1) a discovery sample of healthy adult participants (n = 273); (2) a replication sample of adults with depression (n = 1,267); and (3) a replication sample of healthy adult participants (n = 382). A genetic risk score was created by combining functional polymorphisms from five genes involved in synaptic dopamine availability (COMT and DAT) and dopamine receptor binding (DRD1, DRD2, DRD3). Results: In the discovery sample, the genetic risk score was associated with depressive symptomatology (β = −0.80, p = 0.003), with lower dopamine genetic risk scores (indicating lower dopaminergic neurotransmission) predicting higher levels of depression. This result was replicated with a similar genetic risk score based on imputed genetic data from adults with depression (β = −0.51, p = 0.04). Results were of similar magnitude and in the expected direction in a cohort of healthy adult participants (β = −0.86, p = 0.15). Conclusions: Sequence variation in multiple genes regulating dopamine neurotransmission may influence depressive symptoms, in a manner that appears to be additive. Further studies are required to confirm the role of genetic variation in dopamine metabolism and depression

Psychiatric manifestations of rare variation in medically actionable genes: a PheWAS approach

Background As genomic sequencing moves closer to clinical implementation, there has been an increasing acceptance of returning incidental findings to research participants and patients for mutations in highly penetrant, medically actionable genes. A curated list of genes has been recommended by the American College of Medical Genetics and Genomics (ACMG) for return of incidental findings. However, the pleiotropic effects of these genes are not fully known. Such effects could complicate genetic counseling when returning incidental findings. In particular, there has been no systematic evaluation of psychiatric manifestations associated with rare variation in these genes. Results Here, we leveraged a targeted sequence panel and real-world electronic health records from the eMERGE network to assess the burden of rare variation in the ACMG-56 genes and two psychiatric-associated genes (CACNA1C  and TCF4) across common mental health conditions in 15,181 individuals of European descent. As a positive control, we showed that this approach replicated the established association between rare mutations in LDLR and hypercholesterolemia with no visible inflation from population stratification. However, we did not identify any genes significantly enriched with rare deleterious variants that confer risk for common psychiatric disorders after correction for multiple testing. Suggestive associations were observed between depression and rare coding variation in PTEN (P = 1.5 × 10–4), LDLR (P = 3.6 × 10–4), and CACNA1S (P = 5.8 × 10–4). We also observed nominal associations between rare variants in KCNQ1 and substance use disorders (P = 2.4 × 10–4), and APOB and tobacco use disorder (P = 1.1 × 10–3). Conclusions Our results do not support an association between psychiatric disorders and incidental findings in medically actionable gene mutations, but power was limited with the available sample sizes. Given the phenotypic and genetic complexity of psychiatric phenotypes, future work will require a much larger sequencing dataset to determine whether incidental findings in these genes have implications for risk of psychopathology

Genomeâ wide analyses of psychological resilience in U.S. Army soldiers

Though a growing body of preclinical and translational research is illuminating a biological basis for resilience to stress, little is known about the genetic basis of psychological resilience in humans. We conducted genomeâ wide association studies (GWASs) of selfâ assessed (by questionnaire) and outcomeâ based (incident mental disorders from predeployment to postdeployment) resilience among European (EUR) ancestry soldiers in the Army study to assess risk and resilience in servicemembers. Selfâ assessed resilience (Nâ =â 11,492) was found to have significant commonâ variant heritability (h2 =â 0.162, seâ =â 0.050, pâ =â 5.37â Ã â 10â 4), and to be significantly negatively genetically correlated with neuroticism (rgâ =â â 0.388, pâ =â .0092). GWAS results from the EUR soldiers revealed a genomeâ wide significant locus on an intergenic region on Chr 4 upstream from doublecortinâ like kinase 2 (DCLK2) (four single nucleotide polymorphisms (SNPs) in LD; top SNP: rs4260523 [pâ =â 5.65â Ã â 10â 9] is an eQTL in frontal cortex), a member of the doublecortin family of kinases that promote survival and regeneration of injured neurons. A second gene, kelchâ like family member 36 (KLHL36) was detected at geneâ wise genomeâ wide significance [pâ =â 1.89â Ã â 10â 6]. A polygenic risk score derived from the selfâ assessed resilience GWAS was not significantly associated with outcomeâ based resilience. In very preliminary results, genomeâ wide significant association with outcomeâ based resilience was found for one locus (top SNP: rs12580015 [pâ =â 2.37â Ã â 10â 8]) on Chr 12 downstream from solute carrier family 15 member 5 (SLC15A5) in subjects (Nâ = 581) exposed to the highest level of deployment stress. The further study of genetic determinants of resilience has the potential to illuminate the molecular bases of stressâ related psychopathology and point to new avenues for therapeutic intervention.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149528/1/ajmgb32730.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149528/2/ajmgb32730_am.pd