Predictive power of the ADHD GWAS 2019 polygenic risk scores in independent samples of bipolar patients with childhood ADHD

Abstract

Background: Although there is evidence of genetic correlation between bipolar disorder (BP) and ADHD, the extent of the shared genetic risk and whether childhood ADHD (cADHD) influences the characteristics of the adult BP remain unclear. Our objectives were: (i) to test the ability of polygenic risk scores (PRS) derived from the latest PGC ADHD-GWAS (Demontis et al., 2019) to predict the presence of cADHD in BP patients; (ii) to examine the hypothesis that BP preceded by cADHD is a BP subtype with particular clinical traits and (iii) partially shares its molecular basis with ADHD.Method: PRS derived from the ADHD-GWAS-2019 were tested in BP patients (N=942) assessed for cADHD with the Wender Utah Rating Scale and in controls from Romania and UK (N=1616). Results:The ADHD-PRS differentiated BP cases with cADHD from controls. Proband sex and BP age-of-onset significantly influenced the discriminative power of the ADHD-PRS. The ADHD-PRS predicted the cADHD score only in males and in BP cases with early age-of-onset (≤21 years). Bipolar patients with cADHD had a younger age-of-onset of mania/depression than patients without cADHD.The ADHD-PRS predicted the BP-affection status in the comparison of early-onset BP cases with controls suggesting a partial molecular overlap between early-onset BP and ADHD.Limitations: Retrospective diagnosis of cADHD, small sample size. Conclusions:The PRS-analysis indicated an acceptable predictive ability of the ADHD-SNP-set 2019 in independent BP samples. The best prediction of both cADHD and BP-affection status was found in the early-onset BP cases. The results may have impact on the individual disease monitoring.

Systematic Review: Molecular Studies of Common Genetic Variation in Child and Adolescent Psychiatric Disorders

“…38,77,79,114 ADHD PRS was also found to distinguish bipolar disorder cases with childhood ADHD from controls without bipolar disorder. 115 Genetic Relationship Matrix Restricted Maximum Likelihood and Linkage Disequilibrium Score Regression. Social communication problems, peer problems, and ADHD symptoms showed partly stable genetic effects across ages, with correlations between measures obtained from age 7 to 17 ranging from 0.1 to 1.…”

A principal component approach to improve association testing with polygenic risk scores

“…However, only PRS-PCA with K = 11 and K = 100 identified an additional two traits-PTSD and anxietywith higher genetic load in cases. All of these traits have been shown to have significant genetic correlation or PRS association with BD, in larger samples (Di Florio et al, 2020;Grigoroiu-Serbanescu et al, 2020;P. H. Lee et al, 2019;Nievergelt et al, 2019).…”

“…However, only PRS–PCA with K = 11 and K = 100 identified an additional two traits—PTSD and anxiety—with higher genetic load in cases. All of these traits have been shown to have significant genetic correlation or PRS association with BD, in larger samples (Di Florio et al, 2020; Grigoroiu‐Serbanescu et al, 2020; P. H. Lee et al, 2019; Nievergelt et al, 2019). In our analysis of the case‐only phenotype of manic psychosis, both the PRS–PCA ( K = 11) and the Opt‐Perm approaches reproduced our previous finding that the PRS for SCZ is higher in cases with a history of manic psychosis ( N = 336) than those without a history of psychosis ( N = 309; Markota et al, 2018).…”

“…Using simulations and analysis of the Mayo Clinic Bipolar Disorder (BD) Biobank data, we show that the PRS–PCA approach maintains correct Type I error and outperforms the other PRS strategies in most scenarios. With the increasing availability of GWAS summary statistics, application of PRS strategies to test for association between many different PRSs and multiple phenotypes is becoming common (Coombes et al, 2020; Grigoroiu‐Serbanescu et al, 2020; Zheutlin et al, 2019). The PRS–PCA approach can substantially reduce multiple testing without suffering loss of power and is easy to implement, making it especially beneficial in this context.…”

Quantitative Genetic Scoring, or how to put a number on an arbitrary genetic region

“…With increasing sample sizes and thus statistical power, genome-wide association studies (GWAS) have effectively replaced candidate gene studies for complex multifactorial conditions (Duncan et al, 2019). These GWAS show through estimation of SNP-wide explained variance that genetics can explain a significant portion of variance in these complex, multifactorial phenotypes, ranging from easily measurable traits such as height and body mass index (BMI) (Yengo et al, 2018) to complex psychiatric disorders such as schizophrenia (Pardiñas et al, 2018) and attention deficit/hyperactivity disorder (ADHD) (Grigoroiu-Serbanescu et al, 2020).…”