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

The Genetic Architecture of Differentiating Behavioral and Emotional Problems in Early Life

BACKGROUND

Early in life, behavioral and cognitive traits associated with risk for developing a psychiatric condition are broad and undifferentiated. As children develop, these traits differentiate into characteristic clusters of symptoms and behaviors that ultimately form the basis of diagnostic categories. Understanding this differentiation process-in the context of genetic risk for psychiatric conditions, which is highly generalized-can improve early detection and intervention.

METHODS

We modeled the differentiation of behavioral and emotional problems from age 1.5 to 5 years (behavioral problems - emotional problems = differentiation score) in a preregistered study of ∼79,000 children from the population-based Norwegian Mother, Father, and Child Cohort Study. We used genomic structural equation modeling to identify genetic signal in differentiation and total problems, investigating their links with 11 psychiatric and neurodevelopmental conditions. We examined associations of polygenic scores (PGS) with both outcomes and assessed the relative contributions of direct and indirect genetic effects in ∼33,000 family trios.

RESULTS

Differentiation was primarily genetically correlated with psychiatric conditions via a neurodevelopmental factor. Total problems were primarily associated with the neurodevelopmental factor and p-factor. PGS analyses revealed an association between liability to attention-deficit/hyperactivity disorder and differentiation (β = 0.11; 95% CI, 0.10 to 0.12) and a weaker association with total problems (β = 0.06; 95% CI, 0.04 to 0.07). Trio-PGS analyses showed predominantly direct genetic effects on both outcomes.

CONCLUSIONS

We uncovered genomic signal in the differentiation process, mostly related to common variants associated with neurodevelopmental conditions. Investigating the differentiation of early-life behavioral and emotional problems may enhance our understanding of the developmental emergence of different psychiatric and neurodevelopmental conditions.

Incidence and Genetic Risk of Juvenile Idiopathic Arthritis in Norway by Latitude

OBJECTIVE

We aimed to investigate the incidence of juvenile idiopathic arthritis (JIA) in the three geographic regions of Norway and whether potential regional incidence differences are explained by environmental or genetic factors across regions.

METHODS

We conducted a register-based cohort study including all Norwegian children born from 2004 to 2019, with follow-up throughout 2020. The JIA diagnosis, defined by at least two International Classification of Diseases, Tenth Revision codes for JIA, was validated against medical records. The incidence rate (IR) and hazard ratio (HR) for JIA were estimated for all Norway and for the North, Mid, and South regions. In a subsample from the Norwegian Mother, Father, and Child Cohort Study (MoBa), the genetic risk for JIA was assessed in the three regions.

RESULTS

After median 9.1 (range 0.3-16.0) years of follow-up, we identified 1,184 patients with JIA and 910,058 controls. The IR for JIA/100,000 person-years was 14.4 in all of Norway, 25.9 in the North region, 17.9 in the Mid region, and 12.5 in the South region. The HR (95% confidence interval [CI]) of JIA in the North region was 2.07 (1.77-2.43) and in the Mid region HR 1.43 (95% CI 1.23-1.67) compared with the South region. Adjustments for perinatal factors, socioeconomic status, and early antibiotic exposure did not change our estimates substantially. In MoBa (238 patients with JIA, 57,392 controls), the association between JIA and region of birth was no longer significant when adjusting for genetic factors.

CONCLUSION

We found a higher incidence of JIA with increasing latitude without evidence for available environmental factors explaining the observed gradient. In contrast, genetic factors modified the association, but further studies are warranted.

Unsupervised Ensemble Learning for Efficient Integration of Pre-trained Polygenic Risk Scores

The growing availability of pre-trained polygenic risk score (PRS) models has enabled their integration into real-world applications, reducing the need for extensive data labeling, training, and calibration. However, selecting the most suitable PRS model for a specific target population remains challenging, due to issues such as limited transferability, data heterogeneity, and the scarcity of observed phenotype in real-world settings. Ensemble learning offers a promising avenue to enhance the predictive accuracy of genetic risk assessments, but most existing methods often rely on observed phenotype data or additional genome-wide association studies (GWAS) from the target population to optimize ensemble weights, limiting their utility in real-time implementation. Here, we present the UNSupervised enSemble PRS (UNSemblePRS), an unsupervised ensemble learning framework, that combines pre-trained PRS models without requiring phenotype data or summaries from the target population. Unlike traditional supervised approaches, UNSemblePRS aggregates models based on prediction concordance across a curated subset of candidate PRS models. We evaluated UNSemblePRS using both continuous and binary traits in the All of Us database, demonstrating its scalability and robust performance across diverse populations. These results underscore UNSemblePRS as an accessible tool for integrating PRS models into real-world contexts, offering broad applicability as the availability of PRS models continues to expand.

Unsupervised Ensemble Learning for Efficient Integration of Pre-trained Polygenic Risk Scores

The growing availability of pre-trained polygenic risk score (PRS) models has enabled their integration into real-world applications, reducing the need for extensive data labeling, training, and calibration. However, selecting the most suitable PRS model for a specific target population remains challenging, due to issues such as limited transferability, data heterogeneity, and the scarcity of observed phenotype in real-world settings. Ensemble learning offers a promising avenue to enhance the predictive accuracy of genetic risk assessments, but most existing methods often rely on observed phenotype data or additional genome-wide association studies (GWAS) from the target population to optimize ensemble weights, limiting their utility in real-time implementation. Here, we present the UN supervised en Semble PRS ( UNSemblePRS ), an unsupervised ensemble learning framework, that combines pre-trained PRS models without requiring phenotype data or summaries from the target population. Unlike traditional supervised approaches, UNSemblePRS aggregates models based on prediction concordance across a curated subset of candidate PRS models. We evaluated UNSemblePRS using both continuous and binary traits in the All of Us database, demonstrating its scalability and robust performance across diverse populations. These results underscore UNSemblePRS as an accessible tool for integrating PRS models into real-world contexts, offering broad applicability as the availability of PRS models continues to expand.

Polygenic risk scores and help-seeking behaviour in young people with recent onset of mood and psychotic disorders

OBJECTIVES

We examined associations between polygenic risk scores (PRS) for depression (PRS-MDD), psychosis (PRS-SCZ), bipolar disorders (PRS-BD) and neuroticism (PRS-NEU) and (i) help-seeking, and (ii) new onset cases of full-threshold mood or psychotic disorders in youth.

METHODS

Help-seeking for mental health problems was assessed by self-report and mood and psychotic disorders were identified using the Composite International Diagnostic Interview. A principal component analysis of the four selected PRS identified two dimensions (BD-SCZ; MDD-NEU) that accounted for 69.9 % of the explained variance. We explored the associations between these PRS dimensions and help-seeking and diagnostic subgroup using analyses of co-variance (ANCOVA) adjusted for variables of influence (such as age, sex, twin status).

RESULTS

Almost 30 % (409 of 1473) of study participants met CIDI criteria for ≥ 1 mood or psychotic disorder. Overall, 60 % (n = 245) of CIDI cases sought help, ranging from 35 % for psychosis to 77 % for mania. Furthermore, 143 help-seekers did not have a CIDI diagnosis of mood or psychotic disorders. The BD-SCZ dimension showed associations with help-seeking behaviour and diagnostic groups, but the MDD-NEU dimension only showed associations with help-seeking.

LIMITATIONS

Some diagnoses could not be studied in detail (i.e., schizophreniform disorders) due to the small size of subgroups and planned analyses needed to be adjusted for the presence of twins and non-twin siblings.

CONCLUSIONS

Signals of genetic liability are higher in young people who seek help from health services whether or not the problem they are seeking help for meets full-threshold diagnostic criteria for a major mental disorder.

Autism spectrum disorder common variants associated with regional lobe volume variations at birth: cross-sectional study in 273 European term neonates in developing human connectome project

Increasing lines of evidence suggest cerebral overgrowth in autism spectrum disorder (ASD) children in early life, but few studies have examined the effect of ASD common genetic variants on brain volumes in a general paediatric population. This study examined the association between ASD polygenic risk score (PRS) and volumes of the frontal, temporal, parietal, occipital, fronto-temporal and parieto-occipital lobes in 273 term-born infants of European ancestry in the developing Human Connectome Project. ASD PRS was positively associated with frontal (β = 0.027, pFDR = 0.04) and fronto-temporal (β = 0.024, pFDR = 0.01) volumes, but negatively with parietal (β = -0.037, pFDR = 0.04) and parieto-occipital (β = -0.033, pFDR = 0.01) volumes. This preliminary result suggests the potential involvement of ASD common genetic variants in early structural variations linked to ASD.

Prenatal maternal stress: triangulating evidence for intrauterine exposure effects on birth and early childhood outcomes across multiple approaches

BACKGROUND

Maternal stress during pregnancy may impact offspring development via changes in the intrauterine environment. However, genetic and environmental factors shared between mothers and children might skew our understanding of this pathway. This study assesses whether prenatal maternal stress has causal links to offspring outcomes: birthweight, gestational age, or emotional and behavioral difficulties, triangulating across methods that account for various measured and unmeasured confounders.

METHODS

We used data from the Norwegian Mother, Father, and Child Cohort Study (MoBa), including maternal reports on prenatal stress at work, at home, and via stressful life events as exposures. Outcomes were children's birthweight and gestational age, from the Medical Birth Registry of Norway, and maternal reports on early offspring emotional and behavioral difficulties. We assessed associations using four approaches: sibling control analyses, gene-environment interaction analyses, intergenerational Mendelian randomization (MR), and negative control (i.e., postnatal stress) analyses.

RESULTS

Maternal prenatal stress was observationally associated with offspring lower birthweight (e.g., βwork = - 0.01 [95%CI: - 0.02, - 0.01]), earlier birth (e.g., βwork = - 0.04 [95%CI: - 0.04, - 0.03])), and more emotional (e.g., βevents = 0.08 [95%CI: 0.07, 0.09]) and behavioral difficulties (e.g., βrelationship = 0.08 [95%CI: 0.07, 0.09]) in the full sample (N = 112,784). However, sibling control analyses (N = 36,511) revealed substantial attenuation of all associations after accounting for familial factors. Gene-environment interaction models (N = 76,288) showed no clear evidence of moderation of associations by mothers' polygenic scores for traits linked to stress sensitivity. Intergenerational MR analyses (N = 29,288) showed no clear evidence of causal effects of maternal plasma cortisol on any offspring outcomes. Negative control exposure analyses revealed similar effect sizes whether exposures were measured prenatally or postnatally.

CONCLUSIONS

Our results indicate that links between prenatal maternal stress and variation in early offspring outcomes are more likely to be confounded than causal. While no observational study can rule out causality, the consistency of our findings across different approaches is striking. Other sources of prenatal stress or more extreme levels may represent intrauterine causal risk factors for offspring development. Nonetheless, our research contributes to identifying boundary conditions of the fetal programming and developmental origins of health and disease hypotheses, which may not be as universal as sometimes assumed.

Maternal seafood intake, dietary contaminant exposure, and risk of juvenile idiopathic arthritis: exploring gene-environment interactions

Objectives

Juvenile idiopathic arthritis (JIA) originates from a complex interplay between genetic and environmental factors. We investigated the association between seafood intake and dietary contaminant exposure during pregnancy and JIA risk, to identify sex differences and gene-environment interactions.

Methods

We used the Norwegian Mother, Father, and Child Cohort Study (MoBa), a population-based prospective pregnancy cohort (1999-2008). JIA patients were identified through the Norwegian Patient Registry, with remaining mother-child pairs serving as controls. We assessed maternal seafood intake and dietary contaminants typically found in seafood using a food frequency questionnaire completed during pregnancy, mainly comparing high (≥90th percentile, P90) vs low (

Results

We identified 217 JIA patients and 71,884 controls. High vs low maternal intake of lean/semi-oily fish was associated with JIA (aOR 1.51, 95% CI 1.02-2.22), especially among boys (aOR 2.13, 95% CI 1.21-3.75). A significant gene-environment interaction was observed between total fish intake and PRS, with high fish intake associated with JIA primarily in those with low PRS (p<0.03). We found no associations between high vs low exposure to other types of seafood or environmental contaminants and JIA.

Conclusions

We found a modestly increased risk of JIA associated with high intake of lean/semi-oily fish during pregnancy, not explained by estimated exposure to dietary contaminants. Our data suggest a more pronounced association in children with a lower genetic predisposition for JIA.

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Key Words

• MoBa
• contaminants
• fish
• gene-environment interaction
• heavy metals
• juvenile idiopathic arthritis (JIA)
• polygenic risk score
• sex differences

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MESH Headings

• Humans
• Female
• Seafood/adverse effects
• Male
• Gene-Environment Interaction
• Pregnancy
• Arthritis, Juvenile/epidemiology
• Arthritis, Juvenile/etiology
• Arthritis, Juvenile/genetics
• Norway/epidemiology
• Food Contamination
• Adult
• Prenatal Exposure Delayed Effects
• Risk Factors
• Prospective Studies
• Maternal Exposure/adverse effects
• Child
• Child, Preschool
• Genetic Predisposition to Disease
• Adolescent
• Dietary Exposure/adverse effects

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Affiliation(s)

Vilde Øverlien Dåstøl Department of Rheumatology, Oslo University Hospital, Oslo, Norway Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
Kristine Løkås Haftorn Department of Rheumatology, Oslo University Hospital, Oslo, Norway
Hamid Khoshfekr Rudsari Department of Rheumatology, Oslo University Hospital, Oslo, Norway
Piotr Pawel Jaholkowski Center for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
Ketil Størdal Department of Pediatric Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway Department of Pediatric and Adolescent Medicine, Oslo University Hospital, Oslo, Norway
Siri Eldevik Håberg Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
Clarice R. Weinberg Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, United States
Lisa G. Rider Environmental Autoimmunity Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Bethesda, MD, United States
Ole A. Andreassen Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway Center for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
Anne Lise Brantsæter Department of Food Safety and Centre for Sustainable Diets, Norwegian Institute of Public Health, Oslo, Norway
Ida Henriette Caspersen Department of Rheumatology, Oslo University Hospital, Oslo, Norway Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
Helga Sanner Department of Rheumatology, Oslo University Hospital, Oslo, Norway Oslo New University College, Oslo, Norway

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Identification of novel genomic loci for anxiety symptoms and extensive genetic overlap with psychiatric disorders

AIMS

Anxiety disorders are prevalent and anxiety symptoms (ANX) co-occur with many psychiatric disorders. We aimed to identify genomic loci associated with ANX, characterize its genetic architecture, and genetic overlap with psychiatric disorders.

METHODS

We included a genome-wide association study of ANX (meta-analysis of UK Biobank and Million Veterans Program, n = 301,732), schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), and validated the findings in the Norwegian Mother, Father, and Child Cohort (n = 95,841). We employed the bivariate causal mixture model and local analysis of covariant association to characterize the genetic architecture including overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of loci associated with anxiety and shared with psychiatric disorders.

RESULTS

Anxiety was polygenic with 12.9k genetic variants and overlapped extensively with psychiatric disorders (4.1k-11.4k variants) with predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 119 novel loci for anxiety by conditioning on the psychiatric disorders, and loci shared between anxiety and MDn = 47 , BIPn = 33 , SCZn = 71 , ADHDn = 20 , and ASDn = 5 . Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways including cell adhesion and neurofibrillary tangle compared with genes annotated to the shared loci.

CONCLUSIONS

Anxiety is highly polygenic phenotype with extensive genetic overlap with psychiatric disorders, and we identified novel loci for anxiety implicating new molecular pathways. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified molecular underpinnings may lead to potential drug targets.

Charting the shared genetic architecture of Alzheimer's disease, cognition, and educational attainment, and associations with brain development

The observation that the risk of developing Alzheimer's disease is reduced in individuals with high premorbid cognitive functioning, higher educational attainment, and occupational status has led to the 'cognitive reserve' hypothesis. This hypothesis suggests that individuals with greater cognitive reserve can tolerate a more significant burden of neuropathological changes before the onset of cognitive decline. The underpinnings of cognitive reserve remain poorly understood, although a shared genetic basis between measures of cognitive reserve and Alzheimer's disease has been suggested. Using the largest samples to date and novel statistical tools, we aimed to investigate shared genetic variants between Alzheimer's disease, and measures of cognitive reserve; cognition and educational attainment to identify molecular and neurobiological foundations. We applied the causal mixture model (MiXeR) to estimate the number of trait-influencing variants shared between Alzheimer's disease, cognition, and educational attainment, and condFDR/conjFDR to identify shared loci. To provide biological insights loci were functionally characterized. Subsequently, we constructed a Structural Equation Model (SEM) to determine if the polygenic foundation of cognition has a direct impact on Alzheimer's disease risk, or if its effect is mediated through established risk factors for the disease, using a case-control sample from the UK Biobank. Univariate MiXeR analysis (after excluding chromosome 19) revealed that Alzheimer's disease was substantially less polygenic (450 trait-influencing variants) compared to cognition (11,100 trait-influencing variants), and educational attainment (12,700 trait-influencing variants). Bivariate MiXeR analysis estimated that Alzheimer's disease shared approximately 70 % of trait-influencing variants with cognition, and approximately 40 % with educational attainment, with mixed effect directions. Using condFDR analysis, we identified 18 loci jointly associated with Alzheimer's disease and cognition and 6 loci jointly associated with Alzheimer's disease and educational attainment. Genes mapped to shared loci were associated with neurodevelopment, expressed in early life, and implicated the dendritic tree and phosphatidylinositol phosphate binding mechanisms. Spatiotemporal gene expression analysis of the identified genes showed that mapped genes were highly expressed during the mid-fetal period, further suggesting early neurodevelopmental stages as critical periods for establishing cognitive reserve which affect the risk of Alzheimer's disease in old age. Furthermore, our SEM analysis showed that genetic variants influencing cognition had a direct effect on the risk of developing Alzheimer's disease, providing evidence in support of the neurodevelopmental hypothesis of the disease.

Shared genetic architecture and causality between autism spectrum disorder and irritable bowel syndrome, multisite pain, and fatigue

Autism spectrum disorder (ASD) often co-occurs with functional somatic syndromes (FSS), such as irritable bowel syndrome (IBS), multisite pain, and fatigue. However, the underlying genetic mechanisms and causality have not been well studied. Using large-scale genome-wide association study (GWAS) data, we investigated the shared genetic architecture and causality between ASD and FSS. Specifically, we first estimated genetic correlations and then conducted a multi-trait analysis of GWAS (MTAG) to detect potential novel genetic variants for single traits. Afterwards, polygenic risk scores (PRS) of ASD were derived from GWAS and MTAG to examine the associations with phenotypes in the large Dutch Lifelines cohort. Finally, we performed Mendelian randomization (MR) to evaluate the causality. We observed positive genetic correlations between ASD and FSS (IBS: rg = 0.27, adjusted p = 2.04 × 10-7; multisite pain: rg = 0.13, adjusted p = 1.10 × 10-3; fatigue: rg = 0.33, adjusted p = 5.21 × 10-9). Leveraging these genetic correlations, we identified 3 novel genome-wide significant independent loci for ASD by conducting MTAG, mapped to NEDD4L, MFHAS1, and RP11-10A14.4. PRS of ASD derived from both GWAS and MTAG were associated with ASD and FSS in Lifelines, and MTAG-derived PRS showed a bigger effect size, larger explained variance, and smaller p-values. We did not observe significant causality using MR. Our study found genetic associations between ASD and FSS, specifically with IBS, multisite pain, and fatigue. These findings suggest that a shared genetic architecture may partly explain the co-occurrence between ASD and FSS. Further research is needed to investigate the causality between ASD and FSS due to current limited statistical power of the GWASs.

Polygenic score analyses on antidepressant response in late-life depression, results from the IRL-GRey study

Late-life depression (LLD) is often accompanied by medical comorbidities such as psychiatric disorders and cardiovascular diseases, posing challenges to antidepressant treatment. Recent studies highlighted significant associations between treatment-resistant depression (TRD) and polygenic risk score (PRS) for attention deficit hyperactivity disorder (ADHD) in adults as well as a negative association between antidepressant symptom improvement with both schizophrenia and bipolar. Here, we sought to validate these findings with symptom remission in LLD. We analyzed the Incomplete Response in Late Life Depression: Getting to Remission (IRL-GRey) sample consisting of adults aged 60+ with major depression (N = 342) treated with venlafaxine for 12 weeks. We constructed PRSs for ADHD, depression, schizophrenia, bipolar disorder, neuroticism, general intelligence, antidepressant symptom remission and antidepressant percentage symptom improvement using summary statistics from the Psychiatric Genomics Consortium and the GWAS Catalog. Logistic regression was used to test the association of PRSs with venlafaxine symptom remission and percentage symptom improvement, co-varying for the genomic principal components, age, sex and depressive symptoms severity at baseline. We found a nominal (i.e., p value ≤ 0.05) association between symptom remission and both PRS for ADHD and (OR = 1.36 [1.07, 1.73], p = 0.011) and PRS for bipolar disorder (OR = 0.75 [0.58, 0.97], p = 0.031), as well as between percentage symptom improvement and PRS for general intelligence (beta = 6.81 (SE = 3.122), p = 0.03). However, the ADHD association was in the opposite direction as expected, and both associations did not survive multiple testing corrections. Altogether, these findings suggest that previous findings regarding ADHD PRS and antidepressant response (measured with various outcomes) do not replicate in older adults.

Comorbidity alters the genetic relationship between anxiety disorders and major depression

Importance-

There is extensive comorbidity between anxiety disorders (ANX) and major depression (MD). Most studies on the genetics of ANX do not exclude comorbid cases of MD, and vice versa, therefore confounding genetic association analyses. Disorder-specific analysis of genomic data may reveal more precise biological pathways and causal relationships.

Objective-

To investigate the genetic relationship between disorder-specific ANX and MD compared to samples with comorbidity, including their causal relationship.

Design Setting and Participants-

Data from UK Biobank was used to perform genome-wide association studies (GWAS) of ANX-only and MD-only, and generate disorder-specific polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa) was used to test the associations of PRS with diagnosis and symptoms. MD and ANX GWAS data including comorbidities (MD-co and ANX-co) were used as comparators. Genetic correlation was assessed using LDSC, and Mendelian randomization was employed to infer causal relationships.

Main Outcomes and Measures

GWAS of ICD-10 diagnoses of ANX, MD, or both. Genetic correlations between pairs of ANX and MD phenotypes. PRS associations with diagnoses of ANX, MD, and their comorbid states, and anxiety or depressive symptoms.

Results-

The GWAS of ANX-only (9,980 cases and 179,442 controls) and MD-only (15,301 cases and 179,038 controls) showed a lower genetic correlation (0.53) than the one between ANX-co and MD-co (0.90). ANX-only showed a causal relationship with MD-only (PFDR=1.5e-02), but not vice versa, while comorbid cases showed a significant bidirectional causal relationship (PFDR=2.9e-12, PFDR =9.3e-06). The PRS-MD-only were differentially associated with MD-only compared to ANX-only cases (β= -0.08; 95%CI: -0.11, -0.03); however, this differential association was not observed for the PRS-MD-co. A similar pattern of differential association with anxiety and depressive symptoms was observed for PRS-ANX-only, but not for PRS-MD-co.

Conclusions and Relevance-

The genetics and underlying biology of ANX and MD are more distinct when comorbid cases are excluded from analyses and reveals that ANX may be causal for MD. This confounding of genetic relationships as a result of comorbidity is likely to apply to other psychiatric disorders. Disorder-specific genetic studies may help uncover more relevant biological mechanisms and guide more targeted clinical interventions.

The contribution of attention-deficit/hyperactivity disorder polygenic load to metabolic and cardiovascular health outcomes: a large-scale population and sibling study

Emerging evidence suggests that ADHD is associated with increased risk for metabolic and cardiovascular (cardiometabolic) diseases. However, an understanding of the mechanisms underlying these associations is still limited. In this study we estimated the associations of polygenic scores (PGS) for ADHD with several cardiometabolic diseases and biomarkers. Furthermore, we investigated to what extent the PGS effect was influenced by direct and indirect genetic effects (i.e., shared familial effects). We derived ADHD-PGS in 50,768 individuals aged 18-90 years from the Dutch Lifelines Cohort study. Using generalised estimating equations, we estimated the association of PGS with cardiometabolic diseases, derived from self-report and several biomarkers measured during a physical examination. We additionally ran within-sibling PGS analyses, using fixed effects models, to disentangle direct effects of individuals' own ADHD genetic risk from confounding due to indirect genetic effects of relatives, as well as population stratification. We found that higher ADHD-PGS were statistically significantly associated with several cardiometabolic diseases (R-squared [R2] range = 0.03-0.50%) and biomarkers (related to inflammation, blood pressure, lipid metabolism, amongst others) (R2 range = 0.01-0.16%) (P < 0.05). Adjustment for shared familial factors attenuated the associations between ADHD-PGS and cardiometabolic outcomes (on average 56% effect size reduction), and significant associations only remained for metabolic disease. Overall our findings suggest that increased genetic liability for ADHD confers a small but significant risk increase for cardiometabolic health outcomes in adulthood. These associations were observable in the general population, even in individuals without ADHD diagnosis, and were partly explained by familial factors shared among siblings.

Genetic risk factors underlying white matter hyperintensities and cortical atrophy

White matter hyperintensities index structural abnormalities in the cerebral white matter, including axonal damage. The latter may promote atrophy of the cerebral cortex, a key feature of dementia. Here, we report a study of 51,065 individuals from 10 cohorts demonstrating that higher white matter hyperintensity volume associates with lower cortical thickness. The meta-GWAS of white matter hyperintensities-associated cortical 'atrophy' identifies 20 genome-wide significant loci, and enrichment in genes specific to vascular cell types, astrocytes, and oligodendrocytes. White matter hyperintensities-associated cortical 'atrophy' showed positive genetic correlations with vascular-risk traits and plasma biomarkers of neurodegeneration, and negative genetic correlations with cognitive functioning. 15 of the 20 loci regulated the expression of 54 genes in the cerebral cortex that, together with their co-expressed genes, were enriched in biological processes of axonal cytoskeleton and intracellular transport. The white matter hyperintensities-cortical thickness associations were most pronounced in cortical regions with higher expression of genes specific to excitatory neurons with long-range axons traversing through the white matter. The meta-GWAS-based polygenic risk score predicts vascular and all-cause dementia in an independent sample of 500,348 individuals. Thus, the genetics of white matter hyperintensities-related cortical atrophy involves vascular and neuronal processes and increases dementia risk.

History of childhood maltreatment associated with hospitalization or death due to COVID-19: a cohort study

BACKGROUND

Childhood maltreatment (CM) has been indicated in adverse health outcomes across the lifespan, including severe infection-related outcomes. Yet, data are scarce on the potential role of CM in severe COVID-19-related outcomes as well as on mechanisms underlying this association.

METHODS

We included 151,427 individuals in the UK Biobank who responded to questions on the history of CM in 2016 and 2017 and were alive on January 31, 2020. Binomial logistic regression models were performed to estimate the association between a history of CM and severe COVID-19 outcomes (i.e. hospitalization or death due to COVID-19), as well as COVID-19 diagnosis and vaccination as secondary outcomes. We then explored the potential mediating roles of socio-economic status, lifestyle and pre-pandemic comorbidities, and the effect modification by polygenic risk score for severe COVID-19 outcomes.

RESULTS

The mean age of the study population at the start of the pandemic was 67.7 (SD = 7.72) years, and 56.5% were female. We found the number of CM types was associated with the risk of severe COVID-19 outcomes in a graded manner (pfor trend < 0.01). Compared to individuals with no history of CM, individuals exposed to any CM were more likely to be hospitalized or die due to COVID-19 (odds ratio [OR] = 1.54 [95%CI 1.31-1.81]), particularly after physical neglect (2.04 [1.57-2.62]). Largely comparable risk patterns were observed across groups of high vs. low genetic risks for severe COVID-19 outcomes (pfor difference > 0.05). Mediation analysis revealed that 50.9% of the association between CM and severe COVID-19 outcomes was explained by suboptimal socio-economic status, lifestyle, and pre-pandemic diagnosis of psychiatric disorders or other chronic medical conditions. In contrast, any CM exposure was only weakly associated with COVID-19 diagnosis (1.06 [1.01-1.12]) while significantly associated with not being vaccinated for COVID-19 (1.21 [1.13-1.29]).

CONCLUSIONS

Our results add to the growing knowledge base indicating the role of childhood maltreatment in negative health outcomes across the lifespan, including severe COVID-19-related outcomes. The identified factors underlying this association represent potential intervention targets for mitigating the harmful effects of childhood maltreatment in COVID-19 and similar future pandemics.

Sex effects on DNA methylation affect discovery in epigenome-wide association study of schizophrenia

Sex differences in the epidemiology and clinical characteristics of schizophrenia are well-known; however, the molecular mechanisms underlying these differences remain unclear. Further, the potential advantages of sex-stratified meta-analyses of epigenome-wide association studies (EWAS) of schizophrenia have not been investigated. Here, we performed sex-stratified EWAS meta-analyses to investigate whether sex stratification improves discovery, and to identify differentially methylated regions (DMRs) in schizophrenia. Peripheral blood-derived DNA methylation data from 1519 cases of schizophrenia (male n = 989, female n = 530) and 1723 controls (male n = 997, female n = 726) from three publicly available datasets, and the TOP cohort were meta-analyzed to compare sex-specific, sex-stratified, and sex-adjusted EWAS. The predictive power of each model was assessed by polymethylation score (PMS). The number of schizophrenia-associated differentially methylated positions identified was higher for the sex-stratified model than for the sex-adjusted one. We identified 20 schizophrenia-associated DMRs in the sex-stratified analysis. PMS from sex-stratified analysis outperformed that from sex-adjusted analysis in predicting schizophrenia. Notably, PMSs from the sex-stratified and female-only analyses, but not those from sex-adjusted or the male-only analyses, significantly predicted schizophrenia in males. The findings suggest that sex-stratified EWAS meta-analyses improve the identification of schizophrenia-associated epigenetic changes and highlight an interaction between sex and schizophrenia status on DNA methylation. Sex-specific DNA methylation may have potential implications for precision psychiatry and the development of stratified treatments for schizophrenia.

Association of whole-person eigen-polygenic risk scores with Alzheimer's disease

Late-Onset Alzheimer's Disease (LOAD) is a heterogeneous neurodegenerative disorder with complex etiology and high heritability. Its multifactorial risk profile and large portions of unexplained heritability suggest the involvement of yet unidentified genetic risk factors. Here we describe the "whole person" genetic risk landscape of polygenic risk scores for 2218 traits in 2044 elderly individuals and test if novel eigen-PRSs derived from clustered subnetworks of single-trait PRSs can improve the prediction of LOAD diagnosis, rates of cognitive decline, and canonical LOAD neuropathology. Network analyses revealed distinct clusters of PRSs with clinical and biological interpretability. Novel eigen-PRSs (ePRS) from these clusters significantly improved LOAD-related phenotypes prediction over current state-of-the-art LOAD PRS models. Notably, an ePRS representing clusters of traits related to cholesterol levels was able to improve variance explained in a model of the brain-wide beta-amyloid burden by 1.7% (likelihood ratio test P = 9.02 × 10-7). All associations of ePRS with LOAD phenotypes were eliminated by the removal of APOE-proximal loci. However, our association analysis identified modules characterized by PRSs of high cholesterol and LOAD. We believe this is due to the influence of the APOE region from both PRSs. We found significantly higher mean SNP effects for LOAD in the intersecting APOE region SNPs. Combining genetic risk factors for vascular traits and dementia could improve current single-trait PRS models of LOAD, enhancing the use of PRS in risk stratification. Our results are catalogued for the scientific community, to aid in generating new hypotheses based on our maps of clustered PRSs and associations with LOAD-related phenotypes.

Genetic and phenotypic heterogeneity in early neurodevelopmental traits in the Norwegian Mother, Father and Child Cohort Study

BACKGROUND

Autism and different neurodevelopmental conditions frequently co-occur, as do their symptoms at sub-diagnostic threshold levels. Overlapping traits and shared genetic liability are potential explanations.

METHODS

In the population-based Norwegian Mother, Father, and Child Cohort study (MoBa), we leverage item-level data to explore the phenotypic factor structure and genetic architecture underlying neurodevelopmental traits at age 3 years (N = 41,708-58,630) using maternal reports on 76 items assessing children's motor and language development, social functioning, communication, attention, activity regulation, and flexibility of behaviors and interests.

RESULTS

We identified 11 latent factors at the phenotypic level. These factors showed associations with diagnoses of autism and other neurodevelopmental conditions. Most shared genetic liabilities with autism, ADHD, and/or schizophrenia. Item-level GWAS revealed trait-specific genetic correlations with autism (items rg range = - 0.27-0.78), ADHD (items rg range = - 0.40-1), and schizophrenia (items rg range = - 0.24-0.34). We find little evidence of common genetic liability across all neurodevelopmental traits but more so for several genetic factors across more specific areas of neurodevelopment, particularly social and communication traits. Some of these factors, such as one capturing prosocial behavior, overlap with factors found in the phenotypic analyses. Other areas, such as motor development, seemed to have more heterogenous etiology, with specific traits showing a less consistent pattern of genetic correlations with each other.

CONCLUSIONS

These exploratory findings emphasize the etiological complexity of neurodevelopmental traits at this early age. In particular, diverse associations with neurodevelopmental conditions and genetic heterogeneity could inform follow-up work to identify shared and differentiating factors in the early manifestations of neurodevelopmental traits and their relation to autism and other neurodevelopmental conditions. This in turn could have implications for clinical screening tools and programs.

Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Identification of Novel Genomic Loci for Anxiety and Extensive Genetic Overlap with Psychiatric Disorders

Background

Anxiety disorders are prevalent and anxiety symptoms co-occur with many psychiatric disorders. We aimed to identify genomic risk loci associated with anxiety, characterize its genetic architecture, and genetic overlap with psychiatric disorders.

Methods

We used the GWAS of anxiety symptoms, schizophrenia, bipolar disorder, major depression, and attention deficit hyperactivity disorder (ADHD). We employed MiXeR and LAVA to characterize the genetic architecture and genetic overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of genomic loci associated with anxiety and those shared with psychiatric disorders. Gene annotation and gene set analyses were conducted using OpenTargets and FUMA, respectively.

Results

Anxiety was polygenic with 12.9k estimated genetic risk variants and overlapped extensively with psychiatric disorders (4.1-11.4k variants). MiXeR and LAVA revealed predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 114 novel loci for anxiety by conditioning on the psychiatric disorders. We also identified loci shared between anxiety and major depression (n = 47), bipolar disorder (n = 33), schizophrenia (n = 71), and ADHD (n = 20). Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways and differential tissue expression in more diverse tissues than those annotated to the shared loci.

Conclusions

Anxiety is a highly polygenic phenotype with extensive genetic overlap with psychiatric disorders. These genetic overlaps enabled the identification of novel loci for anxiety. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified genetic loci implicate molecular pathways that may lead to potential drug targets.

Conduct disorder - a comprehensive exploration of comorbidity patterns, genetic and environmental risk factors

Conduct disorder (CD), a common mental disorder in children and adolescents, is characterized by antisocial behavior. Despite similarities with antisocial personality disorder (ASPD) and possible diagnostic continuity, CD has been shown to precede a range of adult-onset mental disorders. Additionally, little is known about the putative shared genetic liability between CD and adult-onset mental disorders and the underlying gene-environment interplay. Here, we interrogated comorbidity between CD and other mental disorders from the Norwegian Mother, Father and Child Cohort Study (n = 114 500) and investigated how polygenic risk scores (PRS) for mental health traits were associated with CD/CD traits in childhood and adolescence. Gene-environment interplay patterns for CD was explored with data on bullying and parental education. We found CD to be comorbid with several child and adult-onset mental disorders. This phenotypic overlap corresponded with associations between PRS for mental disorders and CD. Additionally, our findings support an additive gene-environment model. Previously conceptualized as a precursor of ASPD, we found that CD was associated with polygenic risk for several child- and adult-onset mental disorders. High comorbidity of CD with other psychiatric disorders reflected on the genetic level should inform research studies, diagnostic assessments and clinical follow-up of this heterogenous group.

Genotype-environment interplay in associations between maternal drinking and offspring emotional and behavioral problems

BACKGROUND

While maternal at-risk drinking is associated with children's emotional and behavioral problems, there is a paucity of research that properly accounts for genetic confounding and gene-environment interplay. Therefore, it remains uncertain what mechanisms underlie these associations. We assess the moderation of associations between maternal at-risk drinking and childhood emotional and behavioral problems by common genetic variants linked to environmental sensitivity (genotype-by-environment [G × E] interaction) while accounting for shared genetic risk between mothers and offspring (GE correlation).

METHODS

We use data from 109 727 children born to 90 873 mothers enrolled in the Norwegian Mother, Father, and Child Cohort Study. Women self-reported alcohol consumption and reported emotional and behavioral problems when children were 1.5/3/5 years old. We included child polygenic scores (PGSs) for traits linked to environmental sensitivity as moderators.

RESULTS

Associations between maternal drinking and child emotional (β1 = 0.04 [95% confidence interval (CI) 0.03-0.05]) and behavioral (β1 = 0.07 [0.06-0.08]) outcomes attenuated after controlling for measured confounders and were almost zero when we accounted for unmeasured confounding (emotional: β1 = 0.01 [0.00-0.02]; behavioral: β1 = 0.01 [0.00-0.02]). We observed no moderation of these adjusted exposure effects by any of the PGS.

CONCLUSIONS

The lack of strong evidence for G × E interaction may indicate that the mechanism is not implicated in this kind of intergenerational association. It may also reflect insufficient power or the relatively benign nature of the exposure in this sample.

Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1% to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8% to 5.1% (SBP) and 4.7% to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs.

The impact of genetic risk for schizophrenia on eating disorder clinical presentations

A growing body of literature recognizes associations between eating disorders (EDs) and schizophrenia and suggests that familial liability to schizophrenia in individuals with anorexia nervosa (AN) reveals distinct patterns of clinical outcomes. To further investigate the influence of schizophrenia genetic liability among individuals with EDs, we evaluated the associations between schizophrenia polygenic risk scores (PRS) and clinical presentations of individuals with EDs including their overall health condition and ED-related symptoms. Using data from two previous studies of the genetics of EDs comprising 3,573 Anorexia Nervosa Genetics Initiative (ANGI) cases and 696 Binge Eating Genetics Initiative (BEGIN) cases born after 1973 and linked to the Swedish National Patient Register, we examined the association of schizophrenia PRS on ED clinical features, psychiatric comorbidities, and somatic and mental health burden. Among ANGI cases, higher schizophrenia PRS was statistically significantly associated with higher risk of major depressive disorder (MDD) measured by hazard ratio (HR) with 95% confidence interval (CI) (HR [95% CI]: 1.07 [1.02, 1.13]) and substance abuse disorder (SUD) (HR [95% CI]: 1.14 [1.03, 1.25]) after applying multiple testing correction. Additionally, higher schizophrenia PRS was associated with decreased clinical impairment assessment scores (-0.56, 95% CI: [-1.04, -0.08]) at the conventional significance level (p < 0.05). Further, in BEGIN cases, higher schizophrenia PRS was statistically significantly associated with earlier age at first ED symptom (-0.35 year, 95% CI: [-0.64, -0.06]), higher ED symptom scores (0.16, 95% CI: [0.04, 0.29]), higher risk of MDD (HR [95% CI]: 1.18 [1.04, 1.34]) and SUD (HR [95% CI]: 1.36 [1.07, 1.73]). Similar, but attenuated, patterns held in the subgroup of exclusively AN vs other eating disorder (OED) cases. These results suggest a similar pattern of influence of schizophrenia PRS for AN and OED cases in terms of psychiatric comorbidities, but a different pattern in terms of ED-related clinical features. The disparity of the effect of schizophrenia PRS on AN vs OED merits further investigation.

The genetic contribution to the comorbidity of depression and anxiety: a multi-site electronic health records study of almost 178 000 people

BACKGROUND

Depression and anxiety are common and highly comorbid, and their comorbidity is associated with poorer outcomes posing clinical and public health concerns. We evaluated the polygenic contribution to comorbid depression and anxiety, and to each in isolation.

METHODS

Diagnostic codes were extracted from electronic health records for four biobanks [N = 177 865 including 138 632 European (77.9%), 25 612 African (14.4%), and 13 621 Hispanic (7.7%) ancestry participants]. The outcome was a four-level variable representing the depression/anxiety diagnosis group: neither, depression-only, anxiety-only, and comorbid. Multinomial regression was used to test for association of depression and anxiety polygenic risk scores (PRSs) with the outcome while adjusting for principal components of ancestry.

RESULTS

In total, 132 960 patients had neither diagnosis (74.8%), 16 092 depression-only (9.0%), 13 098 anxiety-only (7.4%), and 16 584 comorbid (9.3%). In the European meta-analysis across biobanks, both PRSs were higher in each diagnosis group compared to controls. Notably, depression-PRS (OR 1.20 per s.d. increase in PRS; 95% CI 1.18-1.23) and anxiety-PRS (OR 1.07; 95% CI 1.05-1.09) had the largest effect when the comorbid group was compared with controls. Furthermore, the depression-PRS was significantly higher in the comorbid group than the depression-only group (OR 1.09; 95% CI 1.06-1.12) and the anxiety-only group (OR 1.15; 95% CI 1.11-1.19) and was significantly higher in the depression-only group than the anxiety-only group (OR 1.06; 95% CI 1.02-1.09), showing a genetic risk gradient across the conditions and the comorbidity.

CONCLUSIONS

This study suggests that depression and anxiety have partially independent genetic liabilities and the genetic vulnerabilities to depression and anxiety make distinct contributions to comorbid depression and anxiety.

Ensembled best subset selection using summary statistics for polygenic risk prediction

Polygenic risk scores (PRS) enhance population risk stratification and advance personalized medicine, yet existing methods face a tradeoff between predictive power and computational efficiency. We introduce ALL-Sum, a fast and scalable PRS method that combines an efficient summary statistic-based L 0 L 2 penalized regression algorithm with an ensembling step that aggregates estimates from different tuning parameters for improved prediction performance. In extensive large-scale simulations across a wide range of polygenicity and genome-wide association studies (GWAS) sample sizes, ALL-Sum consistently outperforms popular alternative methods in terms of prediction accuracy, runtime, and memory usage. We analyze 27 published GWAS summary statistics for 11 complex traits from 9 reputable data sources, including the Global Lipids Genetics Consortium, Breast Cancer Association Consortium, and FinnGen, evaluated using individual-level UKBB data. ALL-Sum achieves the highest accuracy for most traits, particularly for GWAS with large sample sizes. We provide ALL-Sum as a user-friendly command-line software with pre-computed reference data for streamlined user-end analysis.

Characterising depression trajectories in young people at high familial risk of depression

BACKGROUND

Parental depression is a common and potent risk factor for depression in offspring. However, the developmental course of depression from childhood to early-adulthood has not been characterized in this high-risk group.

METHODS

Using longitudinal data from 337 young people who had a parent with a history of recurrent major depressive disorder (MDD), we characterized trajectories of broadly defined depressive disorder using latent class growth analysis. We used clinical descriptions to further characterise trajectory classes.

RESULTS

Two trajectory classes were identified: childhood-emerging (25 %) and adulthood-emerging (75 %). The childhood-emerging class showed high rates of depressive disorder from age 12.5, which persisted through the study period. The adulthood-emerging class showed low rates of depressive disorder until age 26. Individual factors (IQ and ADHD symptoms) and parent depression severity (comorbidity, persistence and impairment) differentiated the classes but there were no differences in family history score or polygenic scores associated with psychiatric disorder. Clinical descriptions indicated functional impairment in both classes, but more severe symptomatology and impairment in the childhood-emerging class.

LIMITATIONS

Attrition particularly affected participation in young adulthood. Factors associated with attrition were low family income, single parent household status and low parental education.

CONCLUSIONS

The developmental course of depressive disorder in children of depressed parents is variable. When followed up to adult life, most individuals exhibited some functional impairment. An earlier age-of-onset was associated with a more persistent and impairing course of depression. Access to effective prevention strategies is particularly warranted for at-risk young people showing early-onsetting and persistent depressive symptoms.

The prediction of Alzheimer's disease through multi-trait genetic modeling

To better capture the polygenic architecture of Alzheimer's disease (AD), we developed a joint genetic score, MetaGRS. We incorporated genetic variants for AD and 24 other traits from two independent cohorts, NACC (n = 3,174, training set) and UPitt (n = 2,053, validation set). One standard deviation increase in the MetaGRS is associated with about 57% increase in the AD risk [hazard ratio (HR) = 1.577, p = 7.17 E-56], showing little difference from the HR for AD GRS alone (HR = 1.579, p = 1.20E-56), suggesting similar utility of both models. We also conducted APOE-stratified analyses to assess the role of the e4 allele on risk prediction. Similar to that of the combined model, our stratified results did not show a considerable improvement of the MetaGRS. Our study showed that the prediction power of the MetaGRS significantly outperformed that of the reference model without any genetic information, but was effectively equivalent to the prediction power of the AD GRS.

GWAS reveals genetic basis of a predisposition to severe COVID-19 through in silico modeling of the FYCO1 protein

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is heavily reliant on its natural ability to "hack" the host's genetic and biological pathways. The genetic susceptibility of the host is a key factor underlying the severity of the disease. Polygenic risk scores are essential for risk assessment, risk stratification, and the prevention of adverse outcomes. In this study, we aimed to assess and analyze the genetic predisposition to severe COVID-19 in a large representative sample of the Russian population as well as to build a reliable but simple polygenic risk score model with a lower margin of error. Another important goal was to learn more about the pathogenesis of severe COVID-19. We examined the tertiary structure of the FYCO1 protein, the only gene with mutations in its coding region and discovered changes in the coiled-coil domain. Our findings suggest that FYCO1 may accelerate viral intracellular replication and excessive exocytosis and may contribute to an increased risk of severe COVID-19. We found significant associations between COVID-19 and LZTFL1, FYCO1, XCR1, CCR9, TMLHE-AS1, and SCYL2 at 3p21.31. Our findings further demonstrate the polymorphic nature of the severe COVID-19 phenotype.

Cross-phenotype relationship between opioid use disorder and suicide attempts: new evidence from polygenic association and Mendelian randomization analyses

Clinical epidemiological studies have found high co-occurrence between suicide attempts (SA) and opioid use disorder (OUD). However, the patterns of correlation and causation between them are still not clear due to psychiatric confounding. To investigate their cross-phenotype relationship, we utilized raw phenotypes and genotypes from >150,000 UK Biobank samples, and genome-wide association summary statistics from >600,000 individuals with European ancestry. Pairwise association and a potential bidirectional relationship between OUD and SA were evaluated with and without controlling for major psychiatric disease status (e.g., schizophrenia, major depressive disorder, and alcohol use disorder). Multiple statistical and genetics tools were used to perform epidemiological association, genetic correlation, polygenic risk score prediction, and Mendelian randomizations (MR) analyses. Strong associations between OUD and SA were observed at both the phenotypic level (overall samples [OR = 2.94, P = 1.59 ×10-14]; non-psychiatric subgroup [OR = 2.15, P = 1.07 ×10-3]) and the genetic level (genetic correlation rg = 0.38 and 0.5 with or without conditioning on psychiatric traits, respectively). Consistently, increasing polygenic susceptibility to SA is associated with increasing risk of OUD (OR = 1.08, false discovery rate [FDR] =1.71 ×10-3), and similarly, increasing polygenic susceptibility to OUD is associated with increasing risk of SA (OR = 1.09, FDR = 1.73 ×10-6). However, these polygenic associations were much attenuated after controlling for comorbid psychiatric diseases. A combination of MR analyses suggested a possible causal association from genetic liability for SA to OUD risk (2-sample univariable MR: OR = 1.14, P = 0.001; multivariable MR: OR = 1.08, P = 0.001). This study provided new genetic evidence to explain the observed OUD-SA comorbidity. Future prevention strategies for each phenotype needs to take into consideration of screening for the other one.

Developmental manifestations of polygenic risk for bipolar disorder from infancy to middle childhood

Knowledge on how genetic risk for bipolar disorder manifests in developmental, emotional or behavioral traits during childhood is lacking. This issue is important to address to inform early detection and intervention efforts. We investigated whether polygenic risk for bipolar disorder is associated with developmental outcomes during early to middle childhood in the general population, and if associations differ between boys and girls. Our sample consisted of 28 001 children from the Norwegian Mother, Father and Child Cohort study, a prospective pregnancy cohort with available genotype and developmental data. Mothers reported on a range of developmental outcomes in their children at 6 and 18 months, 3, 5 and 8 years. Polygenic risk scores reflecting common variant liability to bipolar disorder were calculated. Linear regression models were used in a multi-group framework to investigate associations between polygenic risk score and developmental outcomes, using sex as a grouping variable. We found robust evidence for an association between polygenic risk scores for bipolar disorder and conduct difficulties (β = 0.041, CI = 0.020-0.062) and oppositional defiant difficulties (β = 0.032, CI = 0.014-0.051) at 8 years. Associations with most other outcomes were estimated within the region of practical equivalence to zero (equivalence range D = -0.1 to 0.1), with the exceptions of negative association for activity levels (β = -0.028, CI = -0.047- -0.010) at age 5 and benevolence (β = -0.025, CI = -0.043 to -0.008) at age 8, and positive association for motor difficulties (β = 0.025, CI = 0.008-0.043) at age 3, inattention (β = 0.021, CI = 0.003-0.041) and hyperactivity (β = 0.025, CI = 0.006-0.044) at age 8. Our results suggest that genetic risk for bipolar disorder manifests as disruptive behaviors like oppositional defiant and conduct difficulties in childhood in the general population.

Genetic nurture versus genetic transmission of risk for ADHD traits in the Norwegian Mother, Father and Child Cohort Study

Identifying mechanisms underlying the intergenerational transmission of risk for attention-deficit/hyperactivity disorder (ADHD) traits can inform interventions and provide insights into the role of parents in shaping their children's outcomes. We investigated whether genetic transmission and genetic nurture (environmentally mediated effects) underlie associations between polygenic scores indexing parental risk and protective factors and their offspring's ADHD traits. This birth cohort study included 19,506 genotyped mother-father-offspring trios from the Norwegian Mother, Father and Child Cohort Study. Polygenic scores were calculated for parental factors previously associated with ADHD, including psychopathology, substance use, neuroticism, educational attainment, and cognitive performance. Mothers reported on their 8-year-old children's ADHD traits (n = 9,454 children) using the Parent/Teacher Rating Scale for Disruptive Behaviour Disorders. We found that associations between ADHD maternal and paternal polygenic scores and child ADHD traits decreased significantly when adjusting for the child polygenic score (pΔβ = 9.95 × 10-17 for maternal and pΔβ = 1.48 × 10-14 for paternal estimates), suggesting genetic transmission of ADHD risk. Similar patterns suggesting genetic transmission of risk were observed for smoking, educational attainment, and cognition. The maternal polygenic score for neuroticism remained associated with children's ADHD ratings even after adjusting for the child polygenic score, indicating genetic nurture. There was no robust evidence of genetic nurture for other parental factors. Our findings indicate that the intergenerational transmission of risk for ADHD traits is largely explained by the transmission of genetic variants from parents to offspring rather than by genetic nurture. Observational associations between parental factors and childhood ADHD outcomes should not be interpreted as evidence for predominantly environmentally mediated effects.

Developmental milestones in early childhood and genetic liability to neurodevelopmental disorders

BACKGROUND

Timing of developmental milestones, such as age at first walking, is associated with later diagnoses of neurodevelopmental disorders. However, its relationship to genetic risk for neurodevelopmental disorders in the general population is unknown. Here, we investigate associations between attainment of early-life language and motor development milestones and genetic liability to autism, attention deficit hyperactivity disorder (ADHD), and schizophrenia.

METHODS

We use data from a genotyped sub-set (N = 25699) of children in the Norwegian Mother, Father and Child Cohort Study (MoBa). We calculate polygenic scores (PGS) for autism, ADHD, and schizophrenia and predict maternal reports of children's age at first walking, first words, and first sentences, motor delays (18 months), and language delays and a generalised measure of concerns about development (3 years). We use linear and probit regression models in a multi-group framework to test for sex differences.

RESULTS

We found that ADHD PGS were associated with earlier walking age (β = -0.033, padj < 0.001) in both males and females. Additionally, autism PGS were associated with later walking (β = 0.039, padj = 0.006) in females only. No robust associations were observed for schizophrenia PGS or between any neurodevelopmental PGS and measures of language developmental milestone attainment.

CONCLUSIONS

Genetic liabilities for neurodevelopmental disorders show some specific associations with the age at which children first walk unsupported. Associations are small but robust and, in the case of autism PGS, differentiated by sex. These findings suggest that early-life motor developmental milestone attainment is associated with genetic liability to ADHD and autism in the general population.

Do Poor Diet and Lifestyle Behaviors Modify the Genetic Susceptibility to Impulsivity in the General Population?

The present study investigated whether an unhealthy diet and other lifestyle behaviors may modify the genetic susceptibility to impulsivity. A total of 33,047 participants (mean age = 42.1 years, 59.8% females) from the Dutch Lifelines cohort were included. Each diet index and other lifestyle behaviors were tested for their interactions on the effect on the attention-deficit/hyperactivity disorder (ADHD) polygenic risk score (PRS) on impulsivity using a linear regression model with adjustment for covariates. The ADHD PRS was significantly associated with impulsivity (B = 0.03 (95% CI: 0.02, 0.04); p = 2.61 × 10−9). A poorer diet, a higher intake of energy, and a higher intake of fat were all associated with higher impulsivity, and a high intake of energy amplified the effect of ADHD PRS on impulsivity (e.g., for the interaction term of ADHD PRS and highest tertile on intake of energy, B = 0.038 (95% CI: 0.014, 0.062); p = 0.002. The other lifestyle factors, namely short and long sleep duration, current and past smoking, higher alcohol intake, and more time spent on moderate-to-vigorous physical activity were associated with higher impulsivity, but no interaction effect was observed. In conclusion, we found that a high intake of energy exacerbated the genetic susceptibility to impulsivity. Our study helps to improve our understanding of the role of diet and genetic factors on impulsivity.

Independent role of Alzheimer's disease genetics and C-reactive protein on cognitive ability in aging

Apolipoprotein E (APOE) ε4, the strongest genetic risk factor for late onset Alzheimer's disease (LOAD), has been associated with cognitive decline independent from AD pathology, but the role for other LOAD risk genes in normal cognitive aging is less studied. We examined the effect of APOE ε4 and several different polygenic risk scores (PRS) for LOAD on cognitive level and decline in aging, using longitudinal data from the UK Biobank. While PRS-LOAD including all variants (except APOE) predicted cognitive level, APOE ε4 and PRS-LOAD based on 17 non-APOE gene variants with strong association to AD (p < 5e-8) predicted age-related decline in verbal numeric reasoning. The effect on decline were partly driven by 4 variants involved in the immune system. Those variants also predicted serum levels of the inflammatory marker C-reactive protein (CRP), but CRP did not mediate the effect on decline. Those findings suggest genetic variations in immune functions play a role in aspects of cognitive aging that may be independent of LOAD pathology as well as systemic inflammation measured by CRP.

Genetic predisposition to major depressive disorder differentially impacts alcohol consumption and high-risk drinking situations in men and women with alcohol use disorder

Lifetime history of major depressive disorder (MDD) has a sex-specific association with pretreatment alcohol consumption in patients with alcohol dependence. Here, we investigated the association of genetic load for MDD estimated using a polygenic risk score (PRS) with pretreatment alcohol consumption assessed with Timeline Follow Back in a sample of 287 men and 156 women meeting DSM-IV-TR criteria for alcohol dependence. Preferred drinking situations were assessed using the Inventory of Drug Taking Situations (IDTS). Linear models were used to test for association of normalized alcohol consumption measures with the MDD-PRS, adjusting for ancestry, age, sex, and number of days sober at baseline. We fit models both with and without adjustment for MDD history and alcohol-use-related PRSs as covariates. Higher MDD-PRS was associated with lower 90-day total alcohol consumption in men (β = -0.16, p = 0.0012) but not in women (β = 0.11, p = 0.18). The association of MDD-PRS with IDTS measures was also sex-specific: higher MDD-PRS was associated with higher propensity to drink in temptation-related situations in women, while the opposite (negative association)was found in men. MDD-PRS was not associated with lifetime MDD history in our sample, and adjustment for lifetime MDD and alcohol-related PRSs did not impact the results. Our results suggest that genetic load for MDD impacts pretreatment alcohol consumption in a sex-specific manner, which is similar to, but independent from, the effect of history of MDD. The clinical implications of these findings and contributing biological and psychological factors should be investigated in future studies.

Stress-related exposures amplify the effects of genetic susceptibility on depression and anxiety

It is unclear whether and to what extent stress-related exposures moderate the effects of polygenic risk scores (PRSs) on depression and anxiety. We aimed to examine such moderation effects for a variety of stress-related exposures on depression and anxiety. We included 41,810 participants with both genome-wide genetic data and measurements of depression and anxiety in the Lifelines Cohort Study. Current depression and anxiety were measured by the MINI International Neuropsychiatric Interview. Stress-related exposures included long-term difficulties, stressful life events, reduced social support, childhood trauma, and loneliness, which were measured by self-report questionnaires. PRSs were calculated based on recent large genome-wide association studies for depression and anxiety. We used linear mixed models adjusting for family relationships to estimate the interactions between PRSs and stress-related exposures. Nine of the ten investigated interactions between the five stress-related exposures and the two PRSs for depression and anxiety were significant (Ps < 0.001). Reduced social support, and higher exposure to long-term difficulties, stressful life events, and loneliness amplified the genetic effects on both depression and anxiety. As for childhood trauma exposure, its interaction with the PRS was significant for depression (P = 1.78 × 10^-05) but not for anxiety (P = 0.32). Higher levels of stress-related exposures significantly amplify the effects of genetic susceptibility on depression and anxiety. With a large sample size and a comprehensive set of stress-related exposures, our study provides powerful evidence on the presence of polygenic risk-by-environment interactions in relation to depression and anxiety.

Polygenic Liability to Alzheimer's Disease Is Associated with a Wide Range of Chronic Diseases: A Cohort Study of 312,305 Participants

BACKGROUND

Alzheimer's disease (AD) patients rank among the highest levels of comorbidities compared to persons with other diseases. However, it is unclear whether the conditions are caused by shared pathophysiology due to the genetic pleiotropy for AD risk genes.

OBJECTIVE

To figure out the genetic pleiotropy for AD risk genes in a wide range of diseases.

METHODS

We estimated the polygenic risk score (PRS) for AD and tested the association between PRS and 16 ICD10 main chapters, 136 ICD10 level-1 chapters, and 377 diseases with cases more than 1,000 in 312,305 individuals without AD diagnosis from the UK Biobank.

RESULTS

After correction for multiple testing, AD PRS was associated with two main ICD10 chapters: Chapter IV (endocrine, nutritional and metabolic diseases) and Chapter VII (eye and adnexa disorders). When narrowing the definition of the phenotypes, positive associations were observed between AD PRS and other types of dementia (OR = 1.39, 95% CI [1.34, 1.45], p = 1.96E-59) and other degenerative diseases of the nervous system (OR = 1.18, 95% CI [1.13, 1.24], p = 7.74E-10). In contrast, we detected negative associations between AD PRS and diabetes mellitus, obesity, chronic bronchitis, other retinal disorders, pancreas diseases, and cholecystitis without cholelithiasis (ORs range from 0.94 to 0.97, FDR < 0.05).

CONCLUSION

Our study confirms several associations reported previously and finds some novel results, which extends the knowledge of genetic pleiotropy for AD in a range of diseases. Further mechanistic studies are necessary to illustrate the molecular mechanisms behind these associations.

Investigating Direct and Indirect Genetic Effects in Attention-Deficit/Hyperactivity Disorder Using Parent-Offspring Trios

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is highly heritable, but little is known about the relative effects of transmitted (i.e., direct) and nontransmitted (i.e., indirect) common variant risks. Using parent-offspring trios, we tested whether polygenic liability for neurodevelopmental and psychiatric disorders and lower cognitive ability is overtransmitted to ADHD probands. We also tested for indirect or genetic nurture effects by examining whether nontransmitted ADHD polygenic liability is elevated. Finally, we examined whether complete trios are representative of the clinical ADHD population.

METHODS

Polygenic risk scores (PRSs) for ADHD, anxiety, autism, bipolar disorder, depression, obsessive-compulsive disorder, schizophrenia, Tourette syndrome, and cognitive ability were calculated in UK control subjects (n = 5081), UK probands with ADHD (n = 857), their biological parents (n = 328 trios), and also a replication sample of 844 ADHD trios.

RESULTS

ADHD PRSs were overtransmitted and cognitive ability and obsessive-compulsive disorder PRSs were undertransmitted. These results were independently replicated. Overtransmission of polygenic liability was not observed for other disorders. Nontransmitted alleles were not enriched for ADHD liability compared with control subjects. Probands from incomplete trios had more hyperactive-impulsive and conduct disorder symptoms, lower IQ, and lower socioeconomic status than complete trios. PRS did not vary by trio status.

CONCLUSIONS

The results support direct transmission of polygenic liability for ADHD and cognitive ability from parents to offspring, but not for other neurodevelopmental/psychiatric disorders. They also suggest that nontransmitted neurodevelopmental/psychiatric parental alleles do not contribute indirectly to ADHD via genetic nurture. Furthermore, ascertainment of complete ADHD trios may be nonrandom, in terms of demographic and clinical factors.

A genetically informed prediction model for suicidal and aggressive behaviour in teens

Suicidal and aggressive behaviours cause significant personal and societal burden. As risk factors associated with these behaviours frequently overlap, combined approaches in predicting the behaviours may be useful in identifying those at risk for either. The current study aimed to create a model that predicted if individuals will exhibit suicidal behaviour, aggressive behaviour, both, or neither in late adolescence. A sample of 5,974 twins from the Child and Adolescent Twin Study in Sweden (CATSS) was broken down into a training (80%), tune (10%) and test (10%) set. The Netherlands Twin Register (NTR; N = 2702) was used for external validation. Our longitudinal data featured genetic, environmental, and psychosocial predictors derived from parental and self-report data. A stacked ensemble model was created which contained a gradient boosted machine, random forest, elastic net, and neural network. Model performance was transferable between CATSS and NTR (macro area under the receiver operating characteristic curve (AUC) [95% CI] AUCCATSS(test set) = 0.709 (0.671-0.747); AUCNTR = 0.685 (0.656-0.715), suggesting model generalisability across Northern Europe. The notable exception is suicidal behaviours in the NTR, which was no better than chance. The 25 highest scoring variable importance scores for the gradient boosted machines and random forest models included self-reported psychiatric symptoms in mid-adolescence, sex, and polygenic scores for psychiatric traits. The model's performance is comparable to current prediction models that use clinical interviews and is not yet suitable for clinical use. Moreover, genetic variables may have a role to play in predictive models of adolescent psychopathology.

Research Review: A guide to computing and implementing polygenic scores in developmental research

The increasing availability of genotype data in longitudinal population- and family-based samples provides opportunities for using polygenic scores (PGS) to study developmental questions in child and adolescent psychology and psychiatry. Here, we aim to provide a comprehensive overview of how PGS can be generated and implemented in developmental psycho(patho)logy, with a focus on longitudinal designs. As such, the paper is organized into three parts: First, we provide a formal definition of polygenic scores and related concepts, focusing on assumptions and limitations. Second, we give a general overview of the methods used to compute polygenic scores, ranging from the classic approach to more advanced methods. We include recommendations and reference resources available to researchers aiming to conduct PGS analyses. Finally, we focus on the practical applications of PGS in the analysis of longitudinal data. We describe how PGS have been used to research developmental outcomes, and how they can be applied to longitudinal data to address developmental questions.

Associations between brain imaging and polygenic scores of mental health and educational attainment in children aged 9-11

Psychiatric disorders are highly heritable and polygenic, and many have their peak onset in late childhood and adolescence, a period of tremendous changes. Although the neurodevelopmental antecedents of mental illness are widely acknowledged, research in youth population cohorts is still scarce, preventing our progress towards the early characterization of these disorders. We included 7,124 children (9-11 years old) from the Adolescent Brain and Cognitive Development Study to map the associations of structural and diffusion brain imaging with common genetic variants and polygenic scores for psychiatric disorders and educational attainment. We used principal component analysis to derive imaging components, and calculated their heritability. We then assessed the relationship of imaging components with genetic and clinical psychiatric risk with univariate models and Canonical correlation analysis (CCA). Most imaging components had moderate heritability. Univariate models showed limited evidence and small associations of polygenic scores with brain structure at this age. CCA revealed two significant modes of covariation. The first mode linked higher polygenic scores for educational attainment with less externalizing problems and larger surface area. The second mode related higher polygenic scores for schizophrenia, bipolar disorder, and autism spectrum disorder to higher global cortical thickness, smaller white matter volumes of the fornix and cingulum, larger medial occipital surface area and smaller surface area of lateral and medial temporal regions. While cross-validation suggested limited generalizability, our results highlight the potential of multivariate models to better understand the transdiagnostic and distributed relationships between mental health and brain structure in late childhood.

Early manifestations of genetic liability for ADHD, autism and schizophrenia at ages 18 and 24 months

Background

ADHD and autism are neurodevelopmental conditions, for which non-specific precursors or early signs include difficulties with language and motor skills, and differences in temperament in the first and second year of life. These early features have also been linked to later diagnosis of schizophrenia which is widely considered to have neurodevelopmental origins. Given that ADHD, autism and schizophrenia are all highly heritable, we tested the hypothesis that in the general population, measures of toddler language development, motor development and temperament are associated with genetic liability to ADHD, autism and/or schizophrenia.

Methods

Data were analysed from the Avon Longitudinal Study of Parents and Children (ALSPAC) which included motor development scores at age 18 months and language development and temperament scores at age 24 months (N=7498). Genetic liability was indexed by polygenic risk scores (PGS) for ADHD, autism and schizophrenia.

Results

ADHD PGS were associated with specific temperament scales (higher activity β=0.07, 95% CI=0.04, 0.09 and lower withdrawal β=-0.05, 95% CI=-0.07, -0.02) as well as better gross motor scores (β=0.04, 95% CI=0.01, 0.06). Schizophrenia PGS were associated with one specific temperament scale (negative mood β=0.04, 95% CI=0.02, 0.07). We did not find strong evidence of association of autism PGS with any of the toddler measures; there was also not strong evidence of association with motor or language delays for any of the PGS.

Conclusions

This study suggests that some specific aspects of early temperament and gross motor differences in the general population could represent part of the early manifestation of genetic liability to neurodevelopmental conditions.

Association of autism diagnosis and polygenic scores with eating disorder severity

Among individuals with eating disorders (ED), those with co-occurring autism are often considered to have more severe presentations and poorer prognosis. However, previous findings have been contradictory and limited by small sample size and/or cross-sectional assessment of autistic traits. We examine the hypothesis that autism diagnosis and autism polygenic score (PGS) are associated with increased ED severity in a large ED cohort using a broad range of ED severity indicators. Our cohort included 3189 individuals (64 males) born 1977-2000 with current or previous anorexia nervosa who participated in the Anorexia Nervosa Genetics Initiative-Sweden (ANGI-SE) and for whom genotypes and linkage to national registers were available. We identified 134 (4.2%) individuals with registered autism diagnoses. Individuals with confirmed autism diagnosis had significantly more severe ED across three sets of severity indicators. Some of the largest effects were found for the proportion of individuals who attempted suicide and who received tube feeding (higher in autism), and for the time spent in inpatient care (longer in autism). Results for autism PGS were not statistically significant. Adapting ED treatment to the needs of individuals with co-occurring autism is an important research direction to improve treatment outcome in this group.

Early manifestations of genetic risk for neurodevelopmental disorders

BACKGROUND

Attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (autism) and schizophrenia are highly heritable neurodevelopmental disorders, affecting the lives of many individuals. It is important to increase our understanding of how the polygenic risk for neurodevelopmental disorders manifests during childhood in boys and girls.

METHODS

Polygenic risk scores (PRS) for ADHD, autism and schizophrenia were calculated in a subsample of 15 205 children from the Norwegian Mother, Father and Child Cohort Study (MoBa). Mother-reported traits of repetitive behavior, social communication, language and motor difficulties, hyperactivity and inattention were measured in children at 6 and 18 months, 3, 5 and 8 years. Linear regression models in a multigroup framework were used to investigate associations between the three PRS and dimensional trait measures in MoBa, using sex as a grouping variable.

RESULTS

Before the age of 2, the ADHD PRS was robustly associated with hyperactivity and inattention, with increasing strength up to 8 years, and with language difficulties at age 5 and 8. The autism PRS was robustly associated with language difficulties at 18 months, motor difficulties at 36 months, and hyperactivity and inattention at 8 years. We did not identify robust associations for the schizophrenia PRS. In general, the PRS associations were similar in boys and girls. The association between ADHD PRS and hyperactivity at 18 months was, however, stronger in boys.

CONCLUSIONS

Polygenic risk for autism and ADHD in the general population manifests early in childhood and broadly across behavioral measures of neurodevelopmental traits.

The role of ADHD genetic risk in mid-to-late life somatic health conditions

Growing evidence suggests that ADHD, an early onset neurodevelopmental disorder, is associated with poor somatic health in adulthood. However, the mechanisms underlying these associations are poorly understood. Here, we tested whether ADHD polygenic risk scores (PRS) are associated with mid-to-late life somatic health in a general population sample. Furthermore, we explored whether potential associations were moderated and mediated by life-course risk factors. We derived ADHD-PRS in 10,645 Swedish twins born between 1911 and 1958. Sixteen cardiometabolic, autoimmune/inflammatory, and neurological health conditions were evaluated using self-report (age range at measure 42-88 years) and clinical diagnoses defined by International Classification of Diseases codes in national registers. We estimated associations of ADHD-PRS with somatic outcomes using generalized estimating equations, and tested moderation and mediation of these associations by four life-course risk factors (education level, body mass index [BMI], tobacco use, alcohol misuse). Results showed that higher ADHD-PRS were associated with increased risk of seven somatic outcomes (heart failure, cerebro- and peripheral vascular disease, obesity, type 1 diabetes, rheumatoid arthritis, and migraine) with odds ratios ranging 1.07 to 1.20. We observed significant mediation effects by education, BMI, tobacco use, and alcohol misuse, primarily for associations of ADHD-PRS with cardiometabolic outcomes. No moderation effects survived multiple testing correction. Our findings suggests that higher ADHD genetic liability confers a modest risk increase for several somatic health problems in mid-to-late life, particularly in the cardiometabolic domain. These associations were observable in the general population, even in the absence of medical treatment for ADHD, and appear to be in part mediated by life-course risk factors.

Novel disease associations with schizophrenia genetic risk revealed in ~400,000 UK Biobank participants

Schizophrenia is a serious mental disorder with considerable somatic and psychiatric morbidity. It is unclear whether comorbid health conditions predominantly arise due to shared genetic risk or consequent to having schizophrenia. To explore the contribution of genetic risk for schizophrenia, we analysed the effect of schizophrenia polygenic risk scores (PRS) on a broad range of health problems in 406 929 individuals with no schizophrenia diagnosis from the UK Biobank. Diagnoses were derived from linked health data including primary care, hospital inpatient records, and registers with information on cancer and deaths. Schizophrenia PRS were generated and tested for associations with general health conditions, 16 ICD10 main chapters, and 603 diseases using linear and logistic regressions. Higher schizophrenia PRS was significantly associated with poorer overall health ratings, more hospital inpatient diagnoses, and more unique illnesses. It was also significantly positively associated with 4 ICD10 chapters: mental disorders; respiratory diseases; digestive diseases; and pregnancy, childbirth and the puerperium, but negatively associated with musculoskeletal disorders. Thirty-one specific phenotypes were significantly associated with schizophrenia PRS, and the 19 novel findings include several musculoskeletal diseases, respiratory diseases, digestive diseases, varicose veins, pituitary hyperfunction, and other peripheral nerve disorders. These findings extend knowledge of the pleiotropic effect of genetic risk for schizophrenia and offer insight into how some conditions often comorbid with schizophrenia arise. Additional studies incorporating the genetic basis of hormone regulation and involvement of immune mechanisms in the pathophysiology of schizophrenia may further elucidate the biological mechanisms underlying schizophrenia and its comorbid conditions.

Polygenic Risk for Schizophrenia Has Sex-Specific Effects on Brain Activity during Memory Processing in Healthy Individuals

Genetic risk for schizophrenia has a negative impact on memory and other cognitive abilities in unaffected individuals, and it was recently shown that this effect is specific to males. Using functional MRI, we investigated the effect of a polygenic risk score (PRS) for schizophrenia on brain activation during working memory and episodic memory in 351 unaffected participants (167 males and 184 females, 25–95 years), and specifically tested if any effect of PRS on brain activation is sex-specific. Schizophrenia PRS was significantly associated with decreased brain activation in the left dorsolateral prefrontal cortex (DLPFC) during working-memory manipulation and in the bilateral superior parietal lobule (SPL) during episodic-memory encoding and retrieval. A significant interaction effect between sex and PRS was seen in the bilateral SPL during episodic-memory encoding and retrieval, and sex-stratified analyses showed that the effect of PRS on SPL activation was male-specific. These results confirm previous findings of DLPFC inefficiency in schizophrenia, and highlight the SPL as another important genetic intermediate phenotype of the disease. The observed sex differences suggest that the previously shown male-specific effect of schizophrenia PRS on cognition translates into an additional corresponding effect on brain functioning.

Sleep disturbances in ADHD: investigating the contribution of polygenic liability for ADHD and sleep-related phenotypes

Sleep disturbances are common in attention deficit hyperactivity disorder (ADHD) and associated with poor outcomes. We tested whether, in children with ADHD, (1) polygenic liability for sleep phenotypes is over- or under-transmitted from parents, (2) this liability is linked to comorbid sleep disturbances, and (3) ADHD genetic risk is associated with comorbid sleep disturbances. We derived polygenic scores (PGS) for insomnia, chronotype, sleep duration, and ADHD, in 758 children (5-18 years old) diagnosed with ADHD and their parents. We conducted polygenic transmission disequilibrium tests for each sleep PGS in complete parent-offspring ADHD trios (N = 328) and an independent replication sample of ADHD trios (N = 844). Next, we tested whether insomnia, sleep duration, and ADHD PGS were associated with co-occurring sleep phenotypes (hypersomnia, insomnia, restless sleep, poor sleep quality, and nightmares) in children with ADHD. Children's insomnia and chronotype PGS did not differ from mid-parent average PGS but long sleep duration PGS were significantly over-transmitted to children with ADHD. This was supported by a combined analysis using the replication sample. Insomnia, sleep duration, and ADHD PGS were not associated with comorbid sleep disturbances. There is weak evidence that children with ADHD over-inherit polygenic liability for longer sleep duration and do not differentially inherit polygenic liability for insomnia or chronotype. There was insufficient evidence that childhood sleep disturbances were driven by polygenic liability for ADHD or sleep traits, suggesting that sleep disturbances in ADHD may be aetiologically different to general population sleep phenotypes and do not index greater ADHD genetic risk burden.