Phenome-wide analysis of genome-wide polygenic scores

Cross-Disorder Psychiatric Genomics

PURPOSE OF REVIEW

The following review provides some description of the movement in cross-disorder psychiatric genomics toward addressing both comorbidity and polygenicity.

RECENT FINDINGS

We attempt to show how dimensional approaches to the phenotype have led to further addressing the problem of comorbidity of psychiatric diagnoses. And we also attempt to show how a dimensional approach to the genome, with different statistical methods from traditional genome-wide association analyses, has begun to resolve the problem of massive polygenicity.

SUMMARY

Cross-disorder research, of any area in psychiatry, arguably has the most potential to inform clinical diagnosis, early detection and prevention strategies, and pharmacological treatment research. Future research might leverage what we now know to inform developmental studies of risk and resilience.

Familiality of Psychotic Disorders: A Polynosologic Study in Multiplex Families

INTRODUCTION

Phenotype definition of psychotic disorders has a strong impact on the degree of familial aggregation. Nevertheless, the extent to which distinct classification systems affect familial aggregation (ie, familiality) remains an open question. This study was aimed at examining the familiality associated with 4 nosologic systems of psychotic disorders (DSM-IV, ICD-10, Leonhard's classification and a data-driven approach) and their constituting diagnoses in a sample of multiplex families with psychotic disorders.

METHODS

Participants were probands with a psychotic disorder, their parents and at least one first-degree relative with a psychotic disorder. The sample was made of 441 families comprising 2703 individuals, of whom 1094 were affected and 1709 unaffected.

RESULTS

The Leonhard classification system had the highest familiality (h (2) = 0.64), followed by the empirical (h (2) = 0.55), DSM-IV (h (2) = 0.50), and ICD-10 (h (2) = 0.48). Familiality estimates for individual diagnoses varied considerably (h (2) = 0.25-0.79). Regarding schizophrenia diagnoses, Leonhard's systematic schizophrenia (h (2) = 0.78) had the highest familiality, followed by latent class core schizophrenia (h (2) = 0.74), DSM-IV schizophrenia (h (2) = 0.48), and ICD-10 schizophrenia (h (2) = 0.41). Psychotic mood disorders showed substantial familiality across nosologic systems (h (2) = 0.60-0.77). Domains of psychopathology other than reality-distortion symptoms showed moderate familiality irrespective of diagnosis (h (2) = 0.22-0.52) with the deficit syndrome of schizophrenia showing the highest familiality (h (2) = 0.66).

CONCLUSIONS

While affective psychoses showed relatively high familiality estimates across classification schemes, those of nonaffective psychoses varied markedly as a function of the diagnostic scheme with a narrow schizophrenia phenotype maximizing its familial aggregation. Leonhard's classification of psychotic disorders may be better suited for molecular genetic studies than the official diagnostic systems.

Genetics affects choice of academic subjects as well as achievement

We have previously shown that individual differences in educational achievement are highly heritable throughout compulsory education. After completing compulsory education at age 16, students in England can choose to continue to study for two years (A-levels) in preparation for applying to university and they can freely choose which subjects to study. Here, for the first time, we show that choosing to do A-levels and the choice of subjects show substantial genetic influence, as does performance after two years studying the chosen subjects. Using a UK-representative sample of 6584 twin pairs, heritability estimates were 44% for choosing to do A-levels and 52-80% for choice of subject. Achievement after two years was also highly heritable (35-76%). The findings that DNA differences substantially affect differences in appetites as well as aptitudes suggest a genetic way of thinking about education in which individuals actively create their own educational experiences in part based on their genetic propensities.

Phenotypic Manifestation of Genetic Risk for Schizophrenia During Adolescence in the General Population

IMPORTANCE

Schizophrenia is a highly heritable, polygenic condition characterized by a relatively diverse phenotype and frequent comorbid conditions, such as anxiety and depression. At present, limited evidence explains how genetic risk for schizophrenia is manifest in the general population.

OBJECTIVE

To investigate the extent to which genetic risk for schizophrenia is associated with different phenotypes during adolescence in a population-based birth cohort.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used data from the Avon Longitudinal Study of Parents and Children (ALSPAC). Of 14,062 children in the birth cohort, genetic data were available for 9912 adolescents. Data were collected periodically from September 6, 1990, and collection is ongoing. Data were analyzed from March 4 to August 13, 2015.

EXPOSURES

Polygenic risk scores (PRSs) for schizophrenia generated for individuals in the ALSPAC cohort using results of the second Psychiatric Genomics Consortium Schizophrenia genome-wide association study as a training set.

MAIN OUTCOMES AND MEASURES

Logistic regression was used to assess associations between the schizophrenia PRS and (1) psychotic experiences (Psychosis-Like Symptom Interview at 12 and 18 years of age), (2) negative symptoms (Community Assessment of Psychic Experiences at 16.5 years of age), (3) depressive disorder (Development and Well-Being Assessment at 15.5 years of age), and (4) anxiety disorder (Development and Well-Being Assessment at 15.5 years of age) in adolescence.

RESULTS

Of the 8230 ALSPAC participants whose genetic data passed quality control checks (51.2% male, 48.8% female), 3676 to 5444 participated in assessments from 12 to 18 years of age. The PRSs created using single-nucleotide polymorphisms with a training-set P ≤ .05 threshold were associated with negative symptoms (odds ratio [OR] per SD increase in PRS, 1.21; 95% CI, 1.08-1.36; R(2) = 0.007) and anxiety disorder (OR per SD increase in PRS, 1.17; 95% CI, 1.06- 1.29; R(2) = 0.005). No evidence was found of an association between schizophrenia PRS and psychotic experiences (OR per SD increase in PRS, 1.08; 95% CI, 0.98-1.19; R(2) = 0.001) or depressive disorder (OR per SD increase in PRS, 1.02; 95% CI, 0.91-1.13; R(2) = 0.00005). Results were mostly consistent across different training-set P value thresholds and using different cutoffs and measures of the psychopathological outcomes.

CONCLUSIONS AND RELEVANCE

This study demonstrates polygenic overlaps between common genetic polymorphisms associated with schizophrenia and negative symptoms and anxiety disorder but not with psychotic experiences or depression. Because the genetic risk for schizophrenia appears to be manifest as anxiety and negative symptoms during adolescence, a greater focus on these phenotypes rather than on psychotic experiences might be required for prediction of transition in at-risk samples.

Top 10 Replicated Findings From Behavioral Genetics

In the context of current concerns about replication in psychological science, we describe 10 findings from behavioral genetic research that have replicated robustly. These are "big" findings, both in terms of effect size and potential impact on psychological science, such as linearly increasing heritability of intelligence from infancy (20%) through adulthood (60%). Four of our top 10 findings involve the environment, discoveries that could have been found only with genetically sensitive research designs. We also consider reasons specific to behavioral genetics that might explain why these findings replicate.