Using polygenic scores in combination with symptom rating scales to identify attention-deficit/hyperactivity disorder.

BACKGROUND: The inclusion of biomarkers could improve diagnostic accuracy of attention-deficit/hyperactivity disorder (ADHD). One potential biomarker is the ADHD polygenic score (PGS), a measure of genetic liability for ADHD. This study aimed to investigate if the ADHD PGS can provide additional information alongside ADHD rating scales and examination of family history of ADHD to distinguish between ADHD cases and controls. METHODS: Polygenic scores were calculated for 576 adults with ADHD and 530 ethnically matched controls. ADHD PGS was used alongside scores from the Wender-Utah Rating Scale (WURS) and the Adult ADHD Self-Report Scale (ASRS) as predictors of ADHD diagnosis in a set of nested logistic regression models. These models were compared by likelihood ratio (LR) tests, Akaike information criterion corrected for small samples (AICc), and Lee R². These analyses were repeated with family history of ADHD as a covariate in all models. RESULTS: The ADHD PGS increased the variance explained of the ASRS by 0.58% points (pp) (R2ASRS = 61.11%, R2ASRS + PGS=61.69%), the WURS by 0.61pp (R2WURS = 77.33%, R2WURS + PGS= 77.94%), of ASRS and WURS together by 0.57pp (R2ASRS + WURS=80.84%, R2ASRS + WURS+PGS=81.40%), and of self-reported family history by 1.40pp (R2family = 28.06%, R2family + PGS=29.46%). These increases were statistically significant, as measured by LR tests and AICc. CONCLUSION: We found that the ADHD PGS contributed additional information to common diagnostic aids. However, the increase in variance explained was small, suggesting that the ADHD PGS is currently not a clinically useful diagnostic aid. Future studies should examine the utility of ADHD PGS in ADHD prediction alongside non-genetic risk factors, and the diagnostic utility of the ADHD PGS should be evaluated as more genetic data is accumulated and computational tools are further refined.

Deliberate self-harm in adolescents screening positive for attention-deficit / hyperactivity disorder: a population-based study.

BACKGROUND: Adolescents with attention-deficit / hyperactivity disorder (ADHD) have an increased risk of self-harm. The risk of self-harm among adolescents who display an elevated level of ADHD symptoms, but without a formal diagnosis, is not well-studied and understood. OBJECTIVE: To investigate the relationship between self-reported symptoms of ADHD and self-harm in a population-based sample of adolescents. METHODS: Adolescents in the population-based youth@hordaland study were invited to complete the Adult ADHD Self-Report Scale (ASRS) and the Short Mood and Feelings Questionnaire (SMFQ). They were asked whether they ever deliberately have taken an overdose or tried to harm themselves on purpose, once or multiple times, defined according to the code used in the Child and Adolescent Self-harm in Europe (CASE) Study. Adolescents reporting severe problems on ≥ four of six selected items on the ASRS-v 1.1 screener were defined as ADHD-screen positive (ADHD-SC+), and the remaining sample as ADHD-screen negative (ADHD-SC-). SMFQ score ≥ 12 was used to define a high level of depressive symptoms. RESULTS: A total of 9692 adolescents (mean age 17.4 years, 53.1% females) participated in the study, of which 2390 (24.7%) screened positive on the ASRS. ADHD-SC+ adolescents engaged in self-harm more often than the ADHD-SC- group (14.6% vs. 5.4%, OR = 3.02, 95%CI [2.57-3.24]). This remained significant after adjustment for demographic variables, SMFQ score ≥ 12, symptoms of conduct disorder and familial history of self-harm and suicide attempts (OR = 1.58, 95%CI [1.31-1.89]). They were also more likely to report an overdose as their method of self-harm (OR = 1.52, 95%CI [1.05-2.23]). Within the ADHD-SC+ group female sex, high levels of inattention and hyperactivity/impulsivity symptoms, SMFQ score ≥ 12, symptoms indicating conduct disorder and familial history of self-harm and suicide attempts increased the likelihood of engaging in deliberate self-harm. CONCLUSION: Adolescents who screened positive for ADHD had increased risk of engaging in self-harm. Clinicians should consider the increased risk of such engagement in adolescents who present with high level of ADHD symptoms, even in the absence of a clinical ADHD diagnosis.

A Burden of Rare Copy Number Variants in Obsessive-Compulsive Disorder.

Current genetic research on obsessive-compulsive disorder (OCD) supports contributions to risk specifically from common single nucleotide variants (SNVs), along with rare coding SNVs and small insertion-deletions (indels). The contribution to OCD risk from large, rare copy number variants (CNVs), however, has not been formally assessed at a similar scale. Here we describe an analysis of rare CNVs called from genotype array data in 2,248 deeply phenotyped OCD cases and 3,608 unaffected controls from Sweden and Norway. We found that in general cases carry an elevated burden of large (>30kb, at least 15 probes) CNVs (OR=1.12, P=1.77×10-3). The excess rate of these CNVs in cases versus controls was around 0.07 (95% CI 0.02-0.11, P=2.58×10-3). This signal was largely driven by CNVs overlapping protein-coding regions (OR=1.19, P=3.08×10-4), particularly deletions impacting loss-of-function intolerant genes (pLI>0.995, OR=4.12, P=2.54×10-5). We did not identify any specific locus where CNV burden was associated with OCD case status at genome-wide significance, but we noted non-random recurrence of CNV deletions in cases (permutation P = 2.60×10-3). In cases where sufficient clinical data were available (n=1612) we found that carriers of neurodevelopmental duplications were more likely to have comorbid autism (P<0.001), and that carriers of deletions overlapping neurodevelopmental genes had lower treatment response (P=0.02). The results demonstrate a contribution of large, rare CNVs to OCD risk, and suggest that studies of rare coding variation in OCD would have increased power to identify risk genes if this class of variation were incorporated into formal tests.

Maternal Fiber Intake During Pregnancy and Development of Attention-Deficit/Hyperactivity Disorder Symptoms Across Childhood: The Norwegian Mother, Father, and Child Cohort Study.

BACKGROUND: Epidemiological studies suggest that maternal diet quality during pregnancy may influence the risk of neurodevelopmental disorders in offspring. Here, we investigated associations between maternal intake of dietary fiber and attention-deficit/hyperactivity disorder (ADHD) symptoms in early childhood. METHODS: We used longitudinal data of up to 21,852 mother-father-child trios (49.2% female offspring) from MoBa (the Norwegian Mother, Father, and Child Cohort Study). The relationships between maternal fiber intake during pregnancy and offspring ADHD symptoms at ages 3, 5, and 8 years were examined using 1) multivariate regression (overall levels of ADHD symptoms), 2) latent class analysis (subclasses of ADHD symptoms by sex at each age), and 3) latent growth curves (longitudinal change in offspring ADHD symptoms). Covariates were ADHD polygenic scores in child and parents, total energy intake and energy-adjusted sugar intake, parental ages at birth of the child, and sociodemographic factors. RESULTS: Higher maternal prenatal fiber intake was associated with lower offspring ADHD symptom scores at all ages (Bage3 = -0.14 [95% CI, -0.18 to -0.10]; Bage5 = -0.14 [95% CI, -0.19 to -0.09]; Bage8 = -0.14 [95% CI, -0.20 to -0.09]). Of the derived low/middle/high subclasses of ADHD symptoms, fiber was associated with lower risk of belonging to the middle subclass for boys and girls and to the high subclass for girls only (middle: odds ratioboys 0.91 [95% CI, 0.86 to 0.97]/odds ratiogirls 0.86 [95% CI, 0.81 to 0.91]; high: odds ratiogirls 0.82 [95% CI, 0.72 to 0.94]). Maternal fiber intake and rate of change in child ADHD symptoms across ages were not associated. CONCLUSIONS: Low prenatal maternal fiber intake may increase symptom levels of ADHD in offspring during childhood, independently of genetic predisposition to ADHD, unhealthy dietary exposures, and sociodemographic factors.

Local patterns of genetic sharing challenge the boundaries between neuropsychiatric and insulin resistance-related conditions.

The co-occurrence of insulin resistance (IR)-related metabolic conditions with neuropsychiatric disorders is a complex public health challenge. Evidence of the genetic links between these phenotypes is emerging, but little is currently known about the genomic regions and biological functions that are involved. To address this, we performed Local Analysis of [co]Variant Association (LAVA) using large-scale (N=9,725-933,970) genome-wide association studies (GWASs) results for three IR-related conditions (type 2 diabetes mellitus, obesity, and metabolic syndrome) and nine neuropsychiatric disorders. Subsequently, positional and expression quantitative trait locus (eQTL)-based gene mapping and downstream functional genomic analyses were performed on the significant loci. Patterns of negative and positive local genetic correlations (|rg|=0.21-1, pFDR<0.05) were identified at 109 unique genomic regions across all phenotype pairs. Local correlations emerged even in the absence of global genetic correlations between IR-related conditions and Alzheimer's disease, bipolar disorder, and Tourette's syndrome. Genes mapped to the correlated regions showed enrichment in biological pathways integral to immune-inflammatory function, vesicle trafficking, insulin signalling, oxygen transport, and lipid metabolism. Colocalisation analyses further prioritised 10 genetically correlated regions for likely harbouring shared causal variants, displaying high deleterious or regulatory potential. These variants were found within or in close proximity to genes, such as SLC39A8 and HLA-DRB1, that can be targeted by supplements and already known drugs, including omega-3/6 fatty acids, immunomodulatory, antihypertensive, and cholesterol-lowering drugs. Overall, our findings underscore the complex genetic landscape of IR-neuropsychiatric multimorbidity, advocating for an integrated disease model and offering novel insights for research and treatment strategies in this domain.

Genome-wide association study identifies new loci associated with OCD.

To date, four genome-wide association studies (GWAS) of obsessive-compulsive disorder (OCD) have been published, reporting a high single-nucleotide polymorphism (SNP)-heritability of 28% but finding only one significant SNP. A substantial increase in sample size will likely lead to further identification of SNPs, genes, and biological pathways mediating the susceptibility to OCD. We conducted a GWAS meta-analysis with a 2-3-fold increase in case sample size (OCD cases: N = 37,015, controls: N = 948,616) compared to the last OCD GWAS, including six previously published cohorts (OCGAS, IOCDF-GC, IOCDF-GC-trio, NORDiC-nor, NORDiC-swe, and iPSYCH) and unpublished self-report data from 23andMe Inc. We explored the genetic architecture of OCD by conducting gene-based tests, tissue and celltype enrichment analyses, and estimating heritability and genetic correlations with 74 phenotypes. To examine a potential heterogeneity in our data, we conducted multivariable GWASs with MTAG. We found support for 15 independent genome-wide significant loci (14 new) and 79 protein-coding genes. Tissue enrichment analyses implicate multiple cortical regions, the amygdala, and hypothalamus, while cell type analyses yielded 12 cell types linked to OCD (all neurons). The SNP-based heritability of OCD was estimated to be 0.08. Using MTAG we found evidence for specific genetic underpinnings characteristic of different cohort-ascertainment and identified additional significant SNPs. OCD was genetically correlated with 40 disorders or traits-positively with all psychiatric disorders and negatively with BMI, age at first birth and multiple autoimmune diseases. The GWAS meta-analysis identified several biologically informative genes as important contributors to the aetiology of OCD. Overall, we have begun laying the groundwork through which the biology of OCD will be understood and described.

GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis.

Essential tremor (ET) is a prevalent neurological disorder with a largely unknown underlying biology. In this genome-wide association study meta-analysis, comprising 16,480 ET cases and 1,936,173 controls from seven datasets, we identify 12 sequence variants at 11 loci. Evaluating mRNA expression, splicing, plasma protein levels, and coding effects, we highlight seven putative causal genes at these loci, including CA3 and CPLX1. CA3 encodes Carbonic Anhydrase III and carbonic anhydrase inhibitors have been shown to decrease tremors. CPLX1, encoding Complexin-1, regulates neurotransmitter release. Through gene-set enrichment analysis, we identify a significant association with specific cell types, including dopaminergic and GABAergic neurons, as well as biological processes like Rho GTPase signaling. Genetic correlation analyses reveals a positive association between ET and Parkinson's disease, depression, and anxiety-related phenotypes. This research uncovers risk loci, enhancing our knowledge of the complex genetics of this common but poorly understood disorder, and highlights CA3 and CPLX1 as potential therapeutic targets.

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.