Review article
The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review

https://doi.org/10.1016/j.jad.2018.02.005Get rights and content

Highlights

  • Comprehensive review of how polygenic risk for affective disorders is manifest.

  • Polygenic scores for BD and MDD are associated with multiple psychiatric phenotypes.

  • Both polygenic scores explained <2% of the variance in most phenotypes.

  • The PRS is not useful for prediction at present.

  • Larger discovery and target samples required for greater power and precision.

Abstract

Background

Identifying the phenotypic manifestations of increased genetic liability for depression (MDD) and bipolar disorder (BD) can enhance understanding of their aetiology. The polygenic risk score (PRS) derived using data from genome-wide-association-studies can be used to explore how genetic risk is manifest in different samples.

Aims

In this systematic review, we review studies that examine associations between the MDD and BD polygenic risk scores and phenotypic outcomes.

Methods

Following PRISMA guidelines, we searched EMBASE, Medline and PsycINFO (from August 2009 – 14th March 2016) and references of included studies. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate.

Results

Twenty-five studies were included. Overall, both polygenic risk scores were associated with other psychiatric disorders (not the discovery sample disorder) such as depression, schizophrenia and bipolar disorder, greater symptom severity of depression, membership of a creative profession and greater educational attainment. Both depression and bipolar polygenic risk scores explained small amounts of variance in most phenotypes (< 2%).

Limitations

Many studies did not report standardised effect sizes. This prevented us from conducting a meta-analysis.

Conclusions

Polygenic risk scores for BD and MDD are associated with a range of phenotypes and outcomes. However, they only explain a small amount of the variation in these phenotypes. Larger discovery and adequately powered target samples are required to increase power of the PRS approach. This could elucidate how genetic risk for bipolar disorder and depression is manifest and contribute meaningfully to stratified medicine.

Introduction

Mood disorders (major depressive disorder (MDD) and bipolar disorder (BD)) are common, highly heritable psychiatric conditions as evidenced by twin, adoption and family studies (Bienvenu et al., 2011, Oswald et al., 2003, Shih et al., 2004, Sullivan et al., 2000). Family history of a mood disorder is a strong risk factor for future development of a mood disorder. High-risk studies of offspring of parents with a mood disorder have shown that offspring have an increased lifetime risk for BD (Duffy et al., 2014) or MDD when compared to controls (Rice et al., 2002). Additionally, they are also at increased risk for developing other psychiatric disorders (Rasic et al., 2014). Previously, information about how genetic risk for these disorders was manifest in the population was obtained from high-risk studies that followed up offspring of parents with these disorders. However, a major limitation of these high-risk studies was the relatively small sample sizes, which meant studies were inadequately powered to detect small effect sizes.

The advent of genome-wide association studies (GWAS) has revolutionised identification of genetic variants contributing to psychiatric disorders. GWAS technology can examine many genetic variants in the genome simultaneously, without an a priori hypotheses. Approaches have been developed to harness this information, allowing us to study how individuals with different burdens of genetic risk differ from one another. Through GWAS, several risk variants associated with MDD and BD have been identified (Major Depressive Disorder Working Group of the Psychiatric Genetics Consortium et al., 2017, Sklar et al., 2011, Stahl et al., 2017, Sullivan, 2013). Though the number of risk variants is fewer than for schizophrenia (SZ) (Purcell et al., 2009, Ripke et al., 2014), this is likely due to the smaller discovery samples used in the GWAS analyses, and the lower heritability of MDD compared to schizophrenia (SZ). Whilst individual single nucleotide polymorphisms (SNPs) have very small effect on disease risk, summing the weighted allelic dosage across all SNPs, creating a single polygenic risk score (PRS) has enabled the exploration of how genetic risk is manifest directly in individuals across different populations (Fig. 1) (Wray et al., 2014).

Since the first GWAS were published, many studies have examined whether the MDD-PRS or BD-PRS are associated with a range of different phenotypes and outcomes. Though other methods such as linkage disequilibrium (LD) score regression or genomic residual maximum likelihood (GREML) analysis exist to examine genetic correlation, the focus of this systematic review was to identify and summarise studies that used the PRS approach to examine how genetic risk for MDD and BD is manifest in clinical and population-based samples.

Section snippets

Methods

We undertook a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al., 2009) (Supplementary table 1).

Results

This review includes 25 articles that examined associations between the MDD-PRS/BD-PRS and a measurable phenotype (see Table 1 for a summary of associations with broad phenotypic outcomes). Most studies derived their PRS from the same discovery sample: the first GWAS from the Psychiatric Genetics Consortium (PGC) for MDD and BD (Sklar et al., 2011, Sullivan, 2013). Individual studies used different p-value thresholds (PTs) to assess the relationship between genetic risk for the disorder and

Discussion

To the best of our knowledge, this is the first paper to systematically review how genetic risk for MDD and BD is associated with a broad range of phenotypic outcomes. Other reviews have focussed on the application of PRS methodology to psychiatric disorders, particularly SZ (Wray et al., 2014). More recently we have reported phenotypes associated with genetic risk for SZ (Mistry et al., 2017).

Higher MDD and BD polygenic risk scores were associated with increased risk of different

Acknowledgements

We would like to thank the Cardiff University librarians who assisted with our search strategy.

Funding

SM is funded by Mental Health Research UK. DJS is a Lister Institute Prize Fellow (2016–2021). JRH is funded by the Wellcome Trust GW4 Clinical Academic Training Fellowship. This study was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.

Role of funding source

SM is funded by Mental Health Research UK. DJS is a Lister Institute Prize Fellow (2016–2021). JRH is funded by the Wellcome Trust GW4 Clinical Academic Training Fellowship. SZ is supported by the NIHR Bristol Biomedical Research Centre. The views expressed in this paper are those of the authors and not necessarily the NIHR or any other funders.

References (67)

  • R.A. Power et al.

    Genome-wide association for major depression through age at onset stratification: major depressive disorder working group of the psychiatric genomics consortium

    (2017)
  • J. Verduijn et al.

    Using clinical characteristics to identify which patients with major depressive disorder have a higher genetic load for three psychiatric disorders

    Biol. Psychiatry

    (2017)
  • R. Vonk et al.

    Premorbid school performance in twins concordant and discordant for bipolar disorder

    J. Affect. Disord.

    (2012)
  • O.J. Bienvenu et al.

    Psychiatric 'diseases' versus behavioral disorders and degree of genetic influence

    Psychol. Med.

    (2011)
  • T.B. Bigdeli et al.

    Genome-wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness

    Am. J. Med. Genet. Part B Neuropsychiatr. Genet.

    (2015)
  • M. Boccia et al.

    Where do bright ideas occur in our brain? Meta-analytic evidence from neuroimaging studies of domainspecific creativity

    Front. Psychol.

    (2015)
  • B. Bulik-Sullivan et al.

    An atlas of genetic correlations across human diseases and traits

    Nat. Genet.

    (2015)
  • E.M. Byrne et al.

    Applying polygenic risk scores to postpartum depression

    Arch. Women’s Ment. Health

    (2014)
  • E.M. Byrne et al.

    Seasonality shows evidence for polygenic architecture and genetic correlation with schizophrenia and bipolar disorder

    J. Clin. Psychiatry

    (2015)
  • T.K. Clarke et al.

    Major depressive disorder and current psychological distress moderate the effect of polygenic risk for obesity on body mass index

    Transl. Psychiatry

    (2015)
  • C. Cross-Disorder Group of the Psychiatric Genomics

    Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis

    Lancet

    (2013)
  • A. Demirkan et al.

    Genetic risk profiles for depression and anxiety in adult and elderly cohorts

    Mol. Psychiatry

    (2011)
  • F. Dudbridge

    Power and predictive accuracy of polygenic risk scores

    PLOS Genet.

    (2013)
  • A. Duffy et al.

    The developmental trajectory of bipolar disorder

    Br. J. Psychiatry

    (2014)
  • C.R. Gale et al.

    Pleiotropy between neuroticism and physical and mental health: findings from 108038 men and women in UK Biobank

    Transl. Psychiatry

    (2016)
  • R. Goya-Maldonado et al.

    Differentiating unipolar and bipolar depression by alterations in large-scale brain networks

    Human. Brain Mapp.

    (2016)
  • C. Hakulinen et al.

    Personality and depressive symptoms: individual participant meta-analysis of 10 cohort studies

    Depress. Anxiety

    (2015)
  • M.-H. Hall et al.

    Genomewide association analyses of electrophysiological endophenotypes for schizophrenia and psychotic bipolar disorders: a preliminary report

    Am. J. Med. Genet. Part B Neuropsychiatr. Genet.

    (2015)
  • M.L. Hamshere et al.

    Shared polygenic contribution between childhood attention-deficit hyperactivity disorder and adult schizophrenia

    Br. J. Psychiatry

    (2013)
  • R.E. Jung et al.

    The structure of creative cognition in the human brain

    Front. Human. Neurosci.

    (2013)
  • K.C. Koenen et al.

    Childhood IQ and adult mental disorders: a test of the cognitive reserve hypothesis

    Am. J. Psychiatry

    (2009)
  • M.M. Kurtz et al.

    A meta-analytic investigation of neurocognitive deficits in bipolar illness: profile and effects of clinical state

    Neuropsychology

    (2009)
  • M.E. Levine et al.

    A polygenic risk score associated with measures of depressive symptoms among older adults

    Biodemography Social. Biol.

    (2014)
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