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Background\ud Children with intellectual disability frequently have multiple co-morbid neuropsychiatric conditions and poor physical health. Genomic testing is increasingly recommended as a first-line investigation for these children. We aim to determine the effect of genomics, inheritance, and socioeconomic deprivation on neuropsychiatric risk in children with intellectual disability of genetic origin as compared with the general population.\ud Methods\ud IMAGINE is a prospective cohort study using online mental health and medical assessments in a cohort of 3407 UK participants with intellectual disability and pathogenic genomic variants as identified by the UK's National Health Service (NHS). Our study is on a subset of these participants, including all children aged 4–19 years. We collected diagnostic genomic reports from NHS records and asked primary caregivers to provide an assessment of their child using the Development and Well-Being Assessment (DAWBA), the Strengths and Difficulties Questionnaire (SDQ), the Adaptive Behaviour Assessment System 3 (ABAS-3), and a medical history questionnaire. Each child was assigned a rank based on their postcode using the index of multiple deprivation (IMD). We compared the IMAGINE cohort with the 2017 National Survey of Children's Mental Health in England. The main outcomes of interest were mental health and neurodevelopment according to the DAWBA and SDQ.\ud Findings\ud We recruited 2770 children from the IMAGINE study between Oct 1, 2014 and June 30, 2019, of whom 2397 (86·5%) had a basic assessment of their mental health completed by their families and 1277 (46·1%) completed a medical history questionnaire. The mean age of participants was 9·2 years (SD 3·9); 1339 (55·9%) were boys and 1058 (44·1%) were girls. 355 (27·8%) of 1277 reported a seizure disorder and 814 (63·7%) reported movement or co-ordination problems. 1771 (73·9%) of 2397 participants had a pathogenic copy number variant (CNV) and 626 (26·1%) had a pathogenic single nucleotide variant (SNV). Participants were representative of the socioeconomic spectrum of the UK general population. The relative risk (RR) of co-occurring neuropsychiatric diagnoses, compared with the English national population, was high: autism spectrum disorder RR 29·2 (95% CI 23·9–36·5), ADHD RR 13·5 (95% CI 11·1–16·3). In children with a CNV, those with a familial variant tended to live in more socioeconomically deprived areas than those with a de novo variant. Both inheritance and socioeconomic deprivation contributed to neuropsychiatric risk in those with a CNV.\ud Interpretation\ud Children with genomic variants and intellectual disability are at an increased risk of neuropsychiatric difficulties. CNV variant inheritance and socioeconomic deprivation also contribute to the risk. Early genomic investigations of children with intellectual disability could facilitate the identification of the most vulnerable children. Additionally, harnessing parental expertise using online DAWBA assessments could rapidly identify children with exceptional needs to child mental health services.

Introduction to the LINC research collaborative and how they are defining multimorbidity.

Impaired cognition in schizophrenia is associated with worse functional outcomes. While genetic factors are known to contribute to variation in cognition in schizophrenia, few rare coding variants with strong effects have been identified, and the relative effects from de novo, inherited and non-transmitted alleles are unknown. We used array and exome sequencing data from 656 proband-parent trios to examine the contribution of rare and common variants to school performance, and by implication cognitive function, in schizophrenia. Probands who performed worse at school were enriched for damaging de novo coding variants in genes associated with developmental disorders (DD) (p-value = 0.00026; OR = 11.6). Damaging, ultra-rare coding variants in DD genes that were transmitted or non-transmitted from parents, had no effects on school performance. 13 probands had damaging de novocoding variants in DD genes, of whom 12 had lower school performance. Among probands with lower school performance, those with damaging de novocoding variants in DD genes had a higher rate of comorbid mild intellectual disability (p-value = 0.0002; OR = 15.6). Parental transmission of common genetic liability for educational attainment and intelligence, but not for schizophrenia, was associated with proband school performance, but no significant effects were seen for non-transmitted parental alleles. Overall, we provide evidence for rare and common genetic contributions to school performance in schizophrenia. The strong effects for damaging de novocoding variants in DD genes provide further evidence that cognitive impairment in schizophrenia has a shared aetiology with developmental disorders. Furthermore, we report no evidence in this sample that non-transmitted parental alleles for cognitive traits contributed to school performance in schizophrenia via indirect effects on the environment.

An important step towards the development of treatments for cognitive impairment in ageing and neurodegenerative diseases is to identify genetic and environmental modifiers of cognitive function and understand the mechanism by which they exert an effect. In Huntington’s disease, the most common autosomal dominant dementia, a small number of studies have identified intellectual enrichment, i.e. a cognitively stimulating lifestyle and genetic polymorphisms as potential modifiers of cognitive function. The aim of our study was to further investigate the relationship and interaction between genetic factors and intellectual enrichment on cognitive function and brain atrophy in Huntington’s disease. For this purpose, we analysed data from Track-HD, a multi-centre longitudinal study in Huntington’s disease gene carriers and focused on the role of intellectual enrichment (estimated at baseline) and the genes FAN1, MSH3, BDNF, COMT and MAPT in predicting cognitive decline and brain atrophy. We found that carrying the 3a allele in the MSH3 gene had a positive effect on global cognitive function and brain atrophy in multiple cortical regions, such that 3a allele carriers had a slower rate of cognitive decline and atrophy compared with non-carriers, in agreement with its role in somatic instability. No other genetic predictor had a significant effect on cognitive function and the effect of MSH3 was independent of intellectual enrichment. Intellectual enrichment also had a positive effect on cognitive function; participants with higher intellectual enrichment, i.e. those who were better educated, had higher verbal intelligence and performed an occupation that was intellectually engaging, had better cognitive function overall, in agreement with previous studies in Huntington’s disease and other dementias. We also found that intellectual enrichment interacted with the BDNF gene, such that the positive effect of intellectual enrichment was greater in Met66 allele carriers than non-carriers. A similar relationship was also identified for changes in whole brain and caudate volume; the positive effect of intellectual enrichment was greater for Met66 allele carriers, rather than for non-carriers. In summary, our study provides additional evidence for the beneficial role of intellectual enrichment and carrying the 3a allele in MSH3 in cognitive function in Huntington’s disease and their effect on brain structure.

ImportanceImpaired cognitive function in schizophrenia is associated with poor functional outcomes, but the role of rare coding variants is unclear.ObjectiveTo determine whether ultrarare constrained variants (URCVs) are associated with cognition in patients with schizophrenia.Design, Setting, and ParticipantsLinear regression was used to perform a within-case genetic association study of URCVs and current cognition and premorbid cognitive ability. A multivariable linear regression analysis of the outcomes associated with URCVs, schizophrenia polygenic risk score, polygenic risk score for intelligence and schizophrenia associated copy number variants on cognitive ability was performed. Exome sequencing data from 802 participants with schizophrenia were assessed for current cognition using the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery and for estimated premorbid IQ using the National Adult Reading Test. Individuals were recruited from clinical and voluntary mental health services in the UK. Those with a diagnosis of intellectual disability or a neurological disorder known to affect cognition were excluded. Data collection occurred between 2007 and 2015. Data were analyzed between April 2020 and March 2022.Main Outcomes and MeasuresAssociation between URCVs, current cognition, and current cognition adjusted for premorbid IQ.ResultsOf the 802 participants, 499 (62%) were men and 303 (38%) were women; mean (SD) age at interview was 43.36 (11.87) years. Ultrarare constrained variants (n = 400) were associated with lower current cognition scores (β = −0.18; SE = 0.07; P = .005). In the univariable analysis, premorbid IQ was associated with URCVs (β = −0.12; SE = 0.05; P = .02) and partly attenuated the association with current cognition (β = −0.09; SE = 0.05; P = .08). Multivariable analysis showed that measured genetic factors combined accounted for 6.2% of variance in current cognition, 10.3% of variance in premorbid IQ, and supported outcomes of URCVs associated with current cognition independent of premorbid IQ (β = −0.10; SE = 0.05; P = .03).Conclusions and RelevanceThe findings of this study suggest that URCVs contribute to variance in cognitive function in schizophrenia, with partly independent associations before and after onset of the disorder. Although the estimated effect sizes were small, future studies may show that the effect sizes will be greater with better annotation of pathogenic variants. Genomic data may contribute to identifying those at particularly high risk of cognitive impairment in whom early remedial or preventive measures can be implemented.

Polygenic risk scores (PRS) have been widely adopted as a tool for measuring common variant liability and they have been shown to predict lifetime risk of Alzheimer’s disease (AD) development. However, the relationship between PRS and AD pathogenesis is largely unknown. To this end, we performed a differential gene-expression and associated disrupted biological pathway analyses of AD PRS vs. case/controls in human brain-derived cohort sample (cerebellum/temporal cortex; MayoRNAseq). The results highlighted already implicated mechanisms: immune and stress response, lipids, fatty acids and cholesterol metabolisms, endosome and cellular/neuronal death, being disrupted biological pathways in both case/controls and PRS, as well as previously less well characterised processes such as cellular structures, mitochondrial respiration and secretion. Despite heterogeneity in terms of differentially expressed genes in case/controls vs. PRS, there was a consensus of commonly disrupted biological mechanisms. Glia and microglia-related terms were also significantly disrupted, albeit not being the top disrupted Gene Ontology terms. GWAS implicated genes were significantly and in their majority, up-regulated in response to different PRS among the temporal cortex samples, suggesting potential common regulatory mechanisms. Tissue specificity in terms of disrupted biological pathways in temporal cortex vs. cerebellum was observed in relation to PRS, but limited tissue specificity when the datasets were analysed as case/controls. The largely common biological mechanisms between a case/control classification and in association with PRS suggests that PRS stratification can be used for studies where suitable case/control samples are not available or the selection of individuals with high and low PRS in clinical trials.

Cytokines that signal via STAT1 and STAT3 transcription factors instruct decisions affecting tissue homeostasis, anti-microbial host defense, and inflammation-induced tissue injury. To understand the coordination of these activities, we applied RNA-seq, ChIP-seq, and ATAC-seq to identify the transcriptional output of STAT1 and STAT3 in peritoneal tissues during acute resolving inflammation and inflammation primed to drive fibrosis. Bioinformatics focussed on the transcriptional signature of the immuno-modulatory cytokine IL-6 in both settings and examined how pro-fibrotic IFNγ-secreting CD4+T-cells altered the interpretation of STAT1 and STAT3 cytokine cues. In resolving inflammation, STAT1 and STAT3 cooperated to drive stromal gene expression affecting anti-microbial immunity and tissue homeostasis. The introduction of IFNγ-secreting CD4+T-cells altered this transcriptional program and channeled STAT1 and STAT3 to a previously latent GAS motif inAlu-like elements. STAT1 and STAT3 binding to this conserved sequence revealed evidence of reciprocal cross-regulation and gene signatures relevant to pathophysiology. Thus, we propose that effector T-cells re-tune the transcriptional output of IL-6 by shaping a regulatory interplay between STAT1 and STAT3 in inflammation.

Background Psychotic experiences emerge from abnormalities in perception and belief formation, and occur more commonly in those experiencing childhood trauma. Yet, which precise aspects of belief formation are atypical in psychosis is not well understood. We used a computational modelling approach to characterise belief-updating in young adults in the general population, examine their relationship with psychotic outcomes and trauma, and the extent to which they mediate the trauma-psychosis relationship.MethodsWe used data from 3,360 individuals from the Avon Longitudinal Study of Parents and Children birth cohort who completed assessments for psychotic outcomes, depression, anxiety, and two belief-updating tasks at age 24, and had data available on traumatic events assessed from birth to late adolescence. Unadjusted and adjusted regression and counterfactual mediation methods were used for the analyses.ResultsBasic behavioural measures of belief-updating (‘draws to decision’ and ‘disconfirmatory updating’) were not associated with psychotic experiences. However, computational modelling revealed an association between increased decision noise with both psychotic experiences and trauma exposure, although ConclusionsThese findings challenge the hypothesis that atypical belief-updating mechanisms (as indexed by the computational models and behavioural measures we employed) underlie the development of psychotic phenomena.

Observational studies are often used to understand relationships between exposures and outcomes. When analyzing such data, propensity score (PS) and balance weighting are commonly used techniques that aim to reduce the imbalances between exposure groups by weighting the groups to look alike on the observed confounders. There is now a plethora of available methods to estimate PS and balancing weights as well as rich guidance on how to properly employ these in an analysis. In such studies, unbiased and robust estimation of the causal treatment effect is not guaranteed unless several conditions hold. The literature has shown that accurate inference requires these key criteria: 1) the treatment allocation mechanism is known (e.g., no unobserved confounders), 2) the relationship between the baseline covariates and the outcome is known (if one is to rely on the outcome model itself), 3) adequate balance (comparability) of baseline covariates is achieved post-weighting, 4) a proper set of covariates to control for confounding bias is known, and 5) a large enough sample size is available. In this article, we use simulated data of various sizes to investigate the influence of these five criteria on statistical inference. We have two notable new findings to help improve practice. First, our findings provide important new evidence that the maximum Kolmogorov-Smirnov statistic is the proper statistical measure to assess balance on the baseline covariates, in contrast to the mean standardised mean difference used in many applications, and 0.1 is a suitable threshold to consider as acceptable balance. Second, we also find a clear recommendation that 60 − 80 observations, per confounder per treatment group, are required to obtain a reliable and unbiased estimation of the causal treatment effect.

Historically, Huntington’s disease (HD; OMIM #143100) has played an important role in the enormous advances in human genetics seen over the past four decades. This familial neurodegenerative disorder involves variable onset followed by consistent worsening of characteristic abnormal movements along with cognitive decline and psychiatric disturbances. HD was the first autosomal disease for which the genetic defect was assigned to a position on the human chromosomes using only genetic linkage analysis with common DNA polymorphisms. This discovery set off a multitude of similar studies in other diseases, while the HD gene, later renamed HTT, and its vicinity in chromosome 4p16.3 then acted as a proving ground for development of technologies to clone and sequence genes based upon their genomic location, with the growing momentum of such advances fueling the Human Genome Project. The identification of the HD gene has not yet led to an effective treatment, but continued human genetic analysis of genotype-phenotype relationships in large HD subject populations, first at the HTT locus and subsequently genome-wide, has provided insights into pathogenesis that divide the course of the disease into two sequential, mechanistically distinct components.

BackgroundRecent breakthroughs in psychiatric genetics have implicated biological pathways onto which genetic risk for psychiatric disorders converges. However, these studies do not reveal the developmental time point(s) at which these pathways are relevant.MethodsWe aimed to determine the relationship between psychiatric risk and developmental gene expression relating to discrete biological pathways. We used post-mortem RNA sequencing data (BrainSeq and BrainSpan) from brain tissue at multiple pre- and post-natal timepoints and summary statistics from recent genome-wide association studies of schizophrenia, bipolar disorder and major depressive disorder. We prioritised gene sets for overall enrichment of association with each disorder, and then tested the relationship between the association of each of their constituent genes with their relative expression at each developmental stage.ResultsWe observed relationships between the expression of genes involved involtage-gated cation channel activityduring Early Midfetal, Adolescence and Early Adulthood timepoints and association with schizophrenia and bipolar disorder, such that genes more strongly associated with these disorders had relatively low expression during Early Midfetal development and higher expression during Adolescence and Early Adulthood. The relationship with schizophrenia was strongest for the subset of genes related to calcium channel activity, whilst for bipolar disorder the relationship was distributed between calcium and potassium channel activity genes.ConclusionsOur results indicate periods during development when biological pathways related to the activity of calcium and potassium channels may be most vulnerable to the effects of genetic variants conferring risk to psychiatric disorders. Furthermore, they indicate key time points and potential targets for disorder-specific therapeutic interventions.

An important step towards the development of treatments for cognitive impairment in ageing and neurodegenerative diseases is to identify genetic and environmental modifiers of cognitive function and understand the mechanism by which they exert an effect. In Huntington’s disease, the most common autosomal dominant dementia, a small number of studies have identified intellectual enrichment, i.e. a cognitively stimulating lifestyle, and genetic polymorphisms as potential modifiers of cognitive function. The aim of our study was to further investigate the relationship and interaction between genetic factors and intellectual enrichment on cognitive function and brain atrophy in Huntington’s disease. For this purpose, we analysed data from Track- HD, a multi-centre longitudinal study in Huntington’s disease gene-carriers, and focused on the role of intellectual enrichment (estimated at baseline) and the genes FAN1, MSH3, BDNF, COMT and MAPT in predicting cognitive decline and brain atrophy. We found that carrying the 3a allele in the MSH3 gene had a positive effect on global cognitive function and brain atrophy in multiple cortical regions, such that 3a allele carriers had a slower rate of cognitive decline and atrophy compared to non-carriers, in agreement with its role in somatic expansion instability. No other genetic predictor had a significant effect on cognitive function and the effect of MSH3 was independent of intellectual enrichment. Intellectual enrichment also had a positive effect on cognitive function; participants with higher intellectual enrichment, ie. those who were better educated, had higher verbal IQ and performed an occupation that was intellectually engaging, had better cognitive function overall, in agreement with previous studies in Huntington’s disease and other dementias. We also found that intellectual enrichment interacted with the BDNF gene, such that the positive effect of intellectual enrichment was greater in Met66 allele carriers than non- carriers. A similar relationship was also identified for changes in whole brain and caudate volume; the positive effect of intellectual enrichment was greater for Met66 allele carriers, rather than non- carriers. In summary, our study provides additional evidence for the beneficial role of intellectual enrichment and carrying the 3a allele in MSH3 in cognitive function in Huntington’s disease and their mechanism of action.

BackgroundIt is not clear to what extent associations between schizophrenia, cannabis use and cigarette use are due to a shared genetic etiology. We, therefore, examined whether schizophrenia genetic risk associates with longitudinal patterns of cigarette and cannabis use in adolescence and mediating pathways for any association to inform potential reduction strategies.MethodsAssociations between schizophrenia polygenic scores and longitudinal latent classes of cigarette and cannabis use from ages 14 to 19 years were investigated in up to 3925 individuals in the Avon Longitudinal Study of Parents and Children. Mediation models were estimated to assess the potential mediating effects of a range of cognitive, emotional, and behavioral phenotypes.ResultsThe schizophrenia polygenic score, based on single nucleotide polymorphisms meeting a training-set p threshold of 0.05, was associated with late-onset cannabis use (OR = 1.23; 95% CI = 1.08,1.41), but not with cigarette or early-onset cannabis use classes. This association was not mediated through lower IQ, victimization, emotional difficulties, antisocial behavior, impulsivity, or poorer social relationships during childhood. Sensitivity analyses adjusting for genetic liability to cannabis or cigarette use, using polygenic scores excluding the CHRNA5-A3-B4 gene cluster, or basing scores on a 0.5 training-set p threshold, provided results consistent with our main analyses.ConclusionsOur study provides evidence that genetic risk for schizophrenia is associated with patterns of cannabis use during adolescence. Investigation of pathways other than the cognitive, emotional, and behavioral phenotypes examined here is required to identify modifiable targets to reduce the public health burden of cannabis use in the population.

Huntington’s disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the HTT gene. It is diagnosed following a standardized exam of motor control and often presents with cognitive decline and psychiatric symptoms. Recent studies have detected genetic loci modifying the age at onset of motor symptoms in HD, but genetic factors influencing cognitive and psychiatric presentations are unknown. We tested the hypothesis that psychiatric and cognitive symptoms in HD are influenced by the same common genetic variation as in the general population by constructing polygenic risk scores from large genome-wide association studies of psychiatric and neurodegenerative disorders, and of intelligence, and testing for correlation with the presence of psychiatric and cognitive symptoms in a large sample (n=5160) of HD patients. Polygenic risk score for major depression was associated specifically with increased risk of depression in HD, as was schizophrenia risk score with psychosis and irritability. Cognitive impairment and apathy were associated with reduced polygenic risk score for intelligence. In general, polygenic risk scores for psychiatric disorders, particularly depression and schizophrenia, are associated with increased risk of the corresponding psychiatric symptoms in HD, suggesting a common genetic liability. However, the genetic liability to cognitive impairment and apathy appears to be distinct from other psychiatric symptoms in HD. No associations were observed between HD symptoms and risk scores for other neurodegenerative disorders. These data provide a rationale for treatments effective in depression and schizophrenia to be used to treat depression and psychotic symptoms in HD.

Genome-wide association studies (GWAS) of Huntington’s disease (HD) have identified six DNA maintenance gene loci (among others) as modifiers and implicated a two step-mechanism of pathogenesis: somatic instability of the causative HTT CAG repeat with subsequent triggering of neuronal damage. The largest studies have been limited to HD individuals with a rater-estimated age at motor onset. To capitalize on the wealth of phenotypic data in several large HD natural history studies, we have performed algorithmic prediction using common motor and cognitive measures to predict age at other disease landmarks as additional phenotypes for GWAS. Combined with imputation using the Trans-Omics for Precision Medicine reference panel, predictions using integrated measures provided objective landmark phenotypes with greater power to detect most modifier loci. Importantly, substantial differences in the relative modifier signal across loci, highlighted by comparing common modifiers at MSH3 and FAN1, revealed that individual modifier effects can act preferentially in the motor or cognitive domains. Individual components of the DNA maintenance modifier mechanisms may therefore act differentially on the neuronal circuits underlying the corresponding clinical measures. In addition, we identified new modifier effects at the PMS1 and PMS2 loci and implicated a potential new locus on chromosome 7. These findings indicate that broadened discovery and characterization of HD genetic modifiers based on additional quantitative or qualitative phenotypes offers not only the promise of in-human validated therapeutic targets, but also a route to dissecting the mechanisms and cell types involved in both the somatic instability and toxicity components of HD pathogenesis.

Gamma oscillations (30–90 Hz) have been proposed as a signature of cortical visual information processing, particularly the balance between excitation and inhibition, and as a biomarker of neuropsychiatric diseases. Magnetoencephalography (MEG) provides highly reliable visual-induced gamma oscillation estimates, both at sensor and source level. Recent studies have reported a deficit of visual gamma activity in schizophrenia patients, in medication naive subjects, and high-risk clinical participants, but the genetic contribution to such a deficit has remained unresolved. Here, for the first time, we use a genetic risk score approach to assess the relationship between genetic risk for schizophrenia and visual gamma activity in a population-based sample drawn from a birth cohort. We compared visual gamma activity in a group (N = 104) with a high genetic risk profile score for schizophrenia (SCZ-PRS) to a group with low SCZ-PRS (N = 99). Source-reconstructed V1 activity was extracted using beamformer analysis applied to MEG recordings using individual MRI scans. No group differences were found in the induced gamma peak amplitude or peak frequency. However, a non-parametric statistical contrast of the response spectrum revealed more robust group differences in the amplitude of high-beta/gamma power across the frequency range, suggesting that overall spectral shape carries important biological information beyond the individual frequency peak. Our findings show that changes in gamma band activity correlate with liability to schizophrenia and suggest that the index changes to synaptic function and neuronal firing patterns that are of pathophysiological relevance rather than consequences of the disorder.

There is controversy about the status of schizoaffective disorder depressive-type (SA-D), particularly whether it should be considered a form of schizophrenia or a distinct disorder. We aimed to determine whether individuals with SA-D differ from individuals with schizophrenia in terms of demographic, premorbid and lifetime clinical characteristics, and genetic liability to schizophrenia, depression and bipolar disorder. Participants were from the CardiffCOGS sample and met ICD-10 criteria for schizophrenia (n=713) or SA-D (n=151). Two samples, Cardiff Affected-sib (n=354) and Cardiff F-series (n=524), were used for replication. For all samples, phenotypic data were ascertained through structured interview, review of medical records, and an ICD-10 diagnosis made by trained researchers. Univariable and multivariable logistic regression models were used to compare individuals with schizophrenia and SA-D for demographic and clinical characteristics, and polygenic risk scores (PRS). In the CardiffCOGS, SA-D, compared to schizophrenia, was associated with female sex, childhood abuse, history of alcohol dependence, higher functioning Global Assessment Scale (GAS) score in worst episode of psychosis, lower functioning GAS score in worst episode of depression, and reduced lifetime severity of disorganised symptoms. Individuals with SA-D had higher depression PRS compared to those with schizophrenia. PRS for schizophrenia and bipolar disorder did not significantly differ between SA-D and schizophrenia. Compared to individuals with schizophrenia, individuals with SA-D had higher rates of environmental and genetic risk factors for depression and a similar genetic liability to schizophrenia. These findings are consistent with SA-D being a sub-type of schizophrenia resulting from elevated liability to both schizophrenia and depression.Key words: Polygenic risk score; depression; psychosis; diagnosis; phenotypes

We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer’s disease, using magnetic resonance imaging (MRI) and genotype data from the Avon Longitudinal Study of Parents and Children. Diffusion MRI data were used to perform whole-brain tractography and to generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participant’s genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and a) the graph theoretical metrics of the structural networks and b) the rich-club, feeder and local connectivity of the whole-brain networks.In the visual subnetwork, the mean nodal strength was negatively correlated with the genomewide PRS (r=−0.19, p=1.3×10−5), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r=0.16, p=9.2×10−4), and the mean clustering coefficient was negatively correlated with the tau protein binding PRS (r=−0.16, p=9.2×10−4). In the default mode network, the mean nodal strength was negatively correlated with the genomewide PRS (r=−0.14, p=1.5×10−3). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r=−0.16, p=3.7×10−4; r=−0.15, p=8.8×10−4). Our results indicate small reductions in brain connectivity in young adults at risk of developing Alzheimer’s disease in later life.

Background The length of the HTT CAG repeat explains around 60% of the variance in Huntington’s disease (HD) age at onset. Recently, genome-wide association studies (GWAS) of HD age at onset have identified multiple single nucleotide variants (SNVs) that influence onset, including an intronic SNV, rs79727797, in TCERG1 (p=3.76E-10). Aims Since the SNV does not modify the protein or appear to change gene expression, we tested whether the GWAS signal is due to genetic variation not present in the GWAS. Methods/Techniques We developed a novel method for calling perfect and imperfect short tandem repeats from whole exome sequencing (WES) data, and applied it to 610 WES samples from HD individuals with age at onset or cognitive test data discrepant from those predicted by their HTT CAG length. We identified an exonic (CAGGCC)n short tandem repeat in TCERG1 previously reported to be associated with altered HD age at onset. The reference allele is (CAGGCC)6. We identified 5 length alleles with 3 to 8 hexamer repeats. Results/Outcome Reduced repeat length is significantly associated with later HD age-at-onset (sum of repeat from both TCERG1 repeat alleles: p=6.51E-9). The (CAGGCC)3 allele (frequency 4.1%) is in linkage disequilibrium (r2=0.98) with the minor allele at rs79727797, associated with later onset in the GWAS. Conditioning the association of rs79727797 on TCERG1 (CAGGCC)n length reduces its significance from p=2.4E-6 to p=0.96, while STR length is still significantly associated with HD age at onset after conditioning on rs79727797 (p=3.9E-4). This indicates that the repeat, rather than rs79727797, is responsible for the association at this locus. Conclusion The GWAS signal in TCERG1 is attributable to a short tandem repeat, rather than SNVs. Further biological study of the mechanism by which it alters HD age at onset is warranted.

Background Huntington’s disease (HD) is marked by a progressive movement disorder together with cognitive and psychiatric abnormalities. Psychiatric symptoms are especially difficult for patients and their families, but despite their importance, the molecular understanding of these symptoms is limited. Aims Using polygenic risk scores (PRS), we tested how the risk for certain neuropsychiatric traits were associated with phenotypes seen in HD patients, to better understand genetic mechanisms governing HD symptoms. Methods PRS were calculated for 5,159 HD participants taken from the Enroll and Registry studies, across 11 neuropsychiatric traits. These included risk scores for schizophrenia, obsessive compulsive disorder, suicidality, and intelligence. 45 phenotypes were examined across motor, cognitive and psychiatric domains. Generalised linear models were constructed using the most recent visit data, covarying for HTT CAG size, patient age and approximate disease duration. Results Intelligence PRS were found to be associated with a number of cognitive and functional measures such as total functional capacity (TFC) and the composite Unified Huntington’s Disease Rating Scale (cUHDRS). Obsessive compulsive disorder PRS were associated with dystonia and other motor phenotypes from the total motor score (TMS). Schizophrenia PRS were associated with delusions as reported by the short form problem behaviours assessment (PBA-s), as well as psychosis from the clinical characteristics questionnaire (CCQ). Conclusion Genes underlying neuropsychiatric phenotypes associate with symptoms experienced by HD patients – studying the mechanisms of these manifestations will improve our understanding of Huntington’s disease.

Randomized controlled trials are the gold standard for measuring the causal effects of treatments on clinical outcomes. However, randomized trials are not always feasible, and causal treatment effects must, therefore, often be inferred from observational data. Observational study designs do not allow conclusions about causal relationships to be drawn unless statistical techniques are used to account for the imbalance of confounders across groups while key assumptions hold. Propensity score (PS) and balance weighting are two useful techniques that aim to reduce the imbalances between treatment groups by weighting the groups to look alike on the observed confounders. There are many methods available to estimate PS and balancing weights. However, it is unclear a priori which will achieve the best trade-off between covariate balance and effective sample size. Weighted analyses are further complicated by small studies with limited sample sizes, which is common when studying rare diseases. To address these issues, we present a step-by- step guide to covariate balancing strategies, including how to evaluate overlap, obtain estimates of PS and balancing weights, check for covariate balance, and assess sensitivity to unobserved confounding. We compare the performance of a number of commonly used estimation methods on a synthetic data set based on the Physical Activity and Exercise Outcomes in Huntington Disease (PACE-HD) study, which explored whether enhanced physical activity affects the progression and severity of the disease. We provide general guidelines for the choice of method for estimation of PS and balancing weights, interpretation, and sensitivity analysis of results.

Background CAG length accounts for 50-60% of variation in HD age at motor onset (AMO). The power to detect other modifiers of AMO in HD (for example, genetic) is improved by correcting AMO relative to that expected based on CAG. It is therefore important to estimate expected onset accurately. The Langbehn formula, which assumes that log(AMO) has a linear relationship to CAG, is commonly used to estimate AMO. However, this relationship only holds for CAG of 40-55 repeats. Kaplan et al. propose an alternative estimate of AMO by modelling the time taken for repeats to expand over a pathogenic threshold. Aims To use the Enroll PDS5 data (n=12,030) to compare the fit of AMO predicted by the Langbehn and Kaplan models over CAG repeat lengths ranging from 36-70. Both sxrater (clinician’s estimate of disease onset) and ccmtrage (estimate of motor onset from multiple sources) were used to define AMO. Methods/Techniques The fit of the model to the data was estimated by R2, the proportion of the overall variation in AMO accounted for by the fitted AMO estimates. R2 was calculated for the whole dataset, and for CAG 36-39, 40-55 and 56+ separately. The Kaplan model was fitted by performing a grid search over the model parameters (repeat expansion rate and pathogenic threshold) to maximise R2. This was done on the whole sample, and the three CAG ranges separately. Results/Outcome For sxrater, the Kaplan and Langbehn models gave very similar prediction accuracy when fitted to CAG in the range 40-55 (R2=0.550 for Kaplan, 0.54 for Langbehn). Refitting the Kaplan model using only individuals with CAG from 40-55 improved R2 only slightly (0.561). The Kaplan model outperformed the Langbehn model for CAG of 56+, although prediction accuracy was reduced (R2=0.180). Neither model could predict AMO for individuals with CAG of 36-39. Conclusions were similar using the ccmtrage estimate of AMO. Conclusions The Kaplan model predicts AMO more accurately than the Langbehn model for CAG >55, and could enable individuals with long CAG to be included in genetic modifier studies.

Genes encoding the mRNA targets of Fragile X mental retardation protein (FMRP) are enriched for genetic association with psychiatric disorders. However, many FMRP targets possess functions that are themselves genetically associated with psychiatric disorders, including synaptic transmission and plasticity, making it unclear whether the genetic risk is truly related to binding by FMRP or is alternatively mediated by the sampling of genes better characterised by another trait or functional annotation. Using published common variant, rare coding variant and copy number variant data, we examined the relationship between FMRP binding and genetic association with schizophrenia, major depressive disorder and bipolar disorder. We then explored the partitioning of genetic association between overrepresented functional categories. High-confidence targets of FMRP were enriched for common schizophrenia risk alleles, as well as rare loss-of-function andde novononsynonymous variants in cases. Similarly, through common variation, FMRP targets were associated with major depressive disorder, and we present novel evidence of association with bipolar disorder. These relationships could not be explained by membership of other functional annotations known to be associated with psychiatric disorders, including those related to synaptic structure and function. This study reinforces the evidence that targeting by FMRP captures a subpopulation of genes enriched for genetic association with a range of psychiatric disorders, across traditional diagnostic boundaries.

BackgroundHuntington’s disease is caused by an expanded CAG tract in HTT. The length of the CAG tract accounts for over half the variance in age at onset of disease, and is influenced by other genetic factors, mostly implicating the DNA maintenance machinery. We examined a single nucleotide variant, rs79727797, on chromosome 5 in the TCERG1 gene, previously reported to be associated with Huntington’s disease and a quasi-tandem repeat (QTR) hexamer in exon 4 of TCERG1 with a central pure repeat.MethodsWe developed a novel method for calling perfect and imperfect repeats from exome sequencing data, and tested association between the QTR in TCERG1 and residual age at motor onset (after correcting for the effects of CAG length in the HTT gene) in 610 individuals with Huntington’s disease via regression analysis.ResultsWe found a significant association between age at onset and the sum of the repeat lengths from both alleles of the QTR (p = 2.1×10−9), with each added repeat hexamer reducing age at onset by one year (95% confidence interval [0.7, 1.4]). This association explained that previously observed with rs79727797.ConclusionsThe association with age at onset in the genome-wide association study is due to a QTR hexamer in TCERG1, translated to a glutamine/alanine tract in the protein. We could not distinguish whether this was due to cis-effects of the hexamer repeat on gene expression or of the encoded glutamine/alanine tract in the protein. These results motivate further study of the mechanisms by which TCERG1 modifies onset of HD.

Background Cognitive impairment in schizophrenia is a major contributor to poor outcomes, yet its causes are poorly understood. Some rare copy number variants (CNVs) are associated with schizophrenia risk and affect cognition in healthy populations, but their contribution to cognitive impairment in schizophrenia has not been investigated. We examined the effect of 12 schizophrenia CNVs on cognition in those with schizophrenia. Methods General cognitive ability was measured using the Measurement and Treatment Research to Improve Cognition in Schizophrenia composite z score in 875 patients with schizophrenia and in a replication sample of 519 patients with schizophrenia using Wechsler Adult Intelligence Scale Full Scale IQ. Using linear regression, we tested for association between cognition and schizophrenia CNV status, covarying for age and sex. In addition, we tested whether CNVs hitting genes in schizophrenia-enriched gene sets (loss-of-function intolerant and synaptic gene sets) were associated with cognitive impairment. Results A total of 23 schizophrenia CNV carriers were identified. Schizophrenia CNV carriers had lower general cognitive ability than nonschizophrenia CNV carriers in discovery (β = −0.66, 95% confidence interval [CI] = −1.31 to −0.01) and replication samples (β = −0.91, 95% CI = −1.71 to −0.11) and after meta-analysis (β = −0.76, 95% CI = −1.26 to −0.25, p = .003). CNVs hitting loss-of-function intolerant genes were associated with lower cognition (β = −0.15, 95% CI = −0.29 to −0.001, p = .048). Conclusions In those with schizophrenia, cognitive ability in schizophrenia CNV carriers is 0.5–1.0 standard deviations below non-CNV carriers, which may have implications for clinical assessment and management. We also demonstrate that rare CNVs hitting genes intolerant to loss-of-function variation lead to more severe cognitive impairment, above and beyond the effect of known schizophrenia CNVs.

Schizophrenia is a complex highly heritable disorder. Genome-wide association studies (GWAS) have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. We identify a significant correlation between schizophrenia risk and expression at 89 genes in the dorsolateral prefrontal cortex (P ≤ 9.43 × 10−6), including 20 novel genes. Genes whose expression correlate with schizophrenia were enriched for those involved in abnormal CNS synaptic transmission (PFDR = 0.02) and antigen processing and presentation of peptide antigen via MHC class I (PFDR = 0.02). Within the CNS synaptic transmission set, we identify individual significant candidate genes to which we assign direction of expression changes in schizophrenia. The findings provide strong candidates for experimentally probing the molecular basis of synaptic pathology in schizophrenia.

SummaryThe age at onset of motor symptoms in Huntington’s disease (HD) is driven by HTT CAG repeat length but modified by other genes. We used exome sequencing of 683 HD patients with extremes of onset or phenotype relative to CAG length to identify rare variants associated with clinical effect. We identified damaging coding variants in candidate modifier genes from prior genome-wide association studies associated with altered HD onset or severity. Variants in FAN1 clustered in its DNA-binding and nuclease domains and were associated predominantly with earlier onset HD. Nuclease activities of these variants correlated with residual age at motor onset of HD. Mutating endogenous FAN1 to a nuclease-inactive form in an induced pluripotent stem cell model of HD led to rates of CAG expansion comparable to those observed with complete FAN1 knock out. Together, these data implicate FAN1 nuclease activity in slowing somatic repeat expansion and hence onset of HD.

Risk for late-onset Alzheimer’s disease (LOAD) is driven by multiple loci primarily identified by genome-wide association studies, many of which are common variants with minor allele frequencies (MAF)> 0.01. To identify additional common and rare LOAD risk variants, we performed a GWAS on 25,170 LOAD subjects and 41,052 cognitively normal controls in 44 datasets from the International Genomics of Alzheimer’s Project (IGAP). Existing genotype data was imputed using the dense, high-resolution Haplotype Reference Consortium (HRC) r1.1 reference panel. Stage 1 associations of P−5 were meta-analyzed with the European Alzheimer’s Disease Biobank (EADB) (n=20,301 cases; 21,839 controls) (stage 2 combined IGAP and EADB). An expanded meta-analysis was performed using a GWAS of parental AD/dementia history in the UK Biobank (UKBB) (n=35,214 cases; 180,791 controls) (stage 3 combined IGAP, EADB, and UKBB). Common variant (MAF≥0.01) associations were identified for 29 loci in stage 2, including novel genome-wide significant associations at TSPAN14 (P=2.33×10−12), SHARPIN (P=1.56×10−9), and ATF5/SIGLEC11 (P=1.03×10−8), and newly significant associations without using AD proxy cases in MTSS1L/IL34 (P=1.80×10−8), APH1B (P=2.10×10−13), and CLNK (P=2.24×10−10). Rare variant (MAFAPOE and TREM2, and a novel association of a rare variant (rs143080277; MAF=0.0054; P=2.69×10−9) in NCK2, further strengthened with the inclusion of UKBB data in stage 3 (P=7.17×10−13). Single-nucleus sequence data shows that NCK2 is highly expressed in amyloid-responsive microglial cells, suggesting a role in LOAD pathology.

Huntington’s disease (HD) (OMIM 143100) is caused by an expanded CAG repeat tract in the HTT gene. The inherited CAG length is known to expand further in somatic and germline cells in HD subjects. Age at onset of the disease is inversely correlated with the inherited CAG length, but is further modulated by a series of genetic modifiers which are most likely to act on the CAG repeat in HTT that permit it to further expand. Longer repeats are more prone to expansions, and this expansion is age dependent and tissue-specific. Given that the inherited tract expands through life and most subjects develop disease in mid-life, this implies that in cells that degenerate, the CAG length is likely to be longer than the inherited length. These findings suggest two thresholds— the inherited CAG length which permits further expansion, and the intracellular pathogenic threshold, above which cells become dysfunctional and die. This two-step mechanism has been previously proposed and modelled mathematically to give an intracellular pathogenic threshold at a tract length of 115 CAG (95% confidence intervals 70– 165 CAG). Empirically, the intracellular pathogenic threshold is difficult to determine. Clues from studies of people and models of HD, and from other diseases caused by expanded repeat tracts, place this threshold between 60– 100 CAG, most likely towards the upper part of that range. We assess this evidence and discuss how the intracellular pathogenic threshold in manifest disease might be better determined. Knowing the cellular pathogenic threshold would be informative for both understanding the mechanism in HD and deploying treatments.