Assessing the validity of a self-reported clinical diagnosis of schizophrenia.

Background: Diagnoses in psychiatric research can be derived from various sources. This study assesses the validity of a self-reported clinical diagnosis of schizophrenia. Methods: The study included 3,029 clinically ascertained participants with schizophrenia or psychotic disorders diagnosed by self-report and/or research interview and 1,453 UK Biobank participants with self-report and/or medical record diagnosis of schizophrenia or schizoaffective disorder depressed-type (SA-D). We assessed positive predictive values (PPV) of self-reported clinical diagnoses against research interview and medical record diagnoses. We compared polygenic risk scores (PRS) and phenotypes across diagnostic groups, and compared the variance explained by schizophrenia PRS to samples in the Psychiatric Genomics Consortium (PGC). Results: In the clinically ascertained sample, the PPV of self-reported schizophrenia to a research diagnosis of schizophrenia was 0.70, which increased to 0.81 when benchmarked against schizophrenia or SA-D. In UK Biobank, the PPV of self-reported schizophrenia to a medical record diagnosis was 0.74. Compared to self-report participants, those with a research diagnosis were younger and more likely to have a high school qualification (clinically ascertained sample) and those with a medical record diagnosis were less likely to be employed or have a high school qualification (UK Biobank). Schizophrenia PRS did not differ between participants that had a diagnosis from self-report, research diagnosis or medical record diagnosis. Polygenic liability r2, for all diagnosis definitions, fell within the distribution of PGC schizophrenia cohorts. Conclusions: Self-report measures of schizophrenia are justified in research to maximise sample size and representativeness, although within sample validation of diagnoses is recommended.

Investigation of the genetic aetiology of Lewy body diseases with and without dementia.

Up to 80% of Parkinson's disease patients develop dementia, but time to dementia varies widely from motor symptom onset. Dementia with Lewy bodies presents with clinical features similar to Parkinson's disease dementia, but cognitive impairment precedes or coincides with motor onset. It remains controversial whether dementia with Lewy bodies and Parkinson's disease dementia are distinct conditions or represent part of a disease spectrum. The biological mechanisms underlying disease heterogeneity, in particular the development of dementia, remain poorly understood, but will likely be key to understanding disease pathways and ultimately therapy development. Previous genome-wide association studies in Parkinson's disease and dementia with Lewy bodies/Parkinson's disease dementia have identified risk loci differentiating patients from controls. We collated data for 7,804 patients of European ancestry from Tracking Parkinson's (PRoBaND), The Oxford Discovery Cohort, and AMP-PD. We conducted a discrete phenotype genome-wide association studies comparing Lewy body diseases with and without dementia to decode disease heterogeneity by investigating the genetic drivers of dementia in Lewy body diseases. We found that risk alleles rs429358 tagging APOEe4 and rs7668531 near the MMRN1 and SNCA-AS1 genes, increase the odds of developing dementia and that an intronic variant rs17442721 tagging LRRK2 G2019S, on chromosome 12 is protective against dementia. These results should be validated in autopsy confirmed cases in future studies.

Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression.

OBJECTIVE: Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD. METHOD: Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)-based heritability ([Formula: see text]), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system. RESULTS: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The [Formula: see text] of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD. CONCLUSIONS: While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone).

Epigenetic insights into neuropsychiatric and cognitive symptoms in Parkinson's disease: A DNA co-methylation network analysis.

Parkinson's disease is a highly heterogeneous disorder, encompassing a complex spectrum of clinical presentation including motor, sleep, cognitive and neuropsychiatric symptoms. We aimed to investigate genome-wide DNA methylation networks in post-mortem Parkinson's disease brain samples and test for region-specific association with common neuropsychiatric and cognitive symptoms. Of traits tested, we identify a co-methylation module in the substantia nigra with significant correlation to depressive symptoms and with ontological enrichment for terms relevant to neuronal and synaptic processes. Notably, expression of the genes annotated to the methylation loci present within this module are found to be significantly enriched in neuronal subtypes within the substantia nigra. These findings highlight the potential involvement of neuronal-specific changes within the substantia nigra with regard to depressive symptoms in Parkinson's disease.

Family-based analysis of the contribution of rare and common genetic variants to school performance in schizophrenia.

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 common and rare variants to school performance, and by implication cognitive function, in schizophrenia. Parental transmission of common alleles contributing to higher educational attainment (p value = 0.00015; OR = 2.63) and intelligence (p value = 0.00009; OR = 2.80), but not to schizophrenia, were associated with higher proband school performance. No significant effects were seen for non-transmitted parental common alleles. Probands with lower school performance 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. Among probands with lower school performance, those with damaging de novo coding variants in DD genes had a higher rate of comorbid mild intellectual disability (p value = 0.0002; OR = 15.6). Overall, we provide evidence for rare and common genetic contributions to school performance in schizophrenia. The strong effects for damaging de novo coding 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 common alleles for cognitive traits contributed to school performance in schizophrenia via indirect effects on the environment.

DRAGON-Data: a platform and protocol for integrating genomic and phenotypic data across large psychiatric cohorts.

BACKGROUND: Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood. AIMS: Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research. METHOD: As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant. RESULTS: We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation. CONCLUSIONS: DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

Genomic Stratification of Clozapine Prescription Patterns Using Schizophrenia Polygenic Scores.

BACKGROUND: Treatment-resistant schizophrenia affects approximately 30% of individuals with the disorder. Clozapine is the medication of choice in treatment-resistant schizophrenia, but optimizing administration and dose titration is complex. The identification of factors influencing clozapine prescription and response, including genetics, is of interest in a precision psychiatry framework. METHODS: We used linear regression models accounting for demographic, pharmacological, and clinical covariates to determine whether a polygenic risk score (PRS) for schizophrenia would be associated with the highest dose recorded during clozapine treatment. Analyses were performed across 2 independent multiancestry samples of individuals from a UK patient monitoring system, CLOZUK2 (n = 3133) and CLOZUK3 (n = 909), and a European sample from a Norwegian therapeutic drug monitoring service (n = 417). In a secondary analysis merging both UK cohorts, logistic regression models were used to estimate the relationship between schizophrenia PRSs and clozapine doses classified as low, standard, or high. RESULTS: After controlling for relevant covariates, the schizophrenia PRS was correlated with the highest clozapine dose on record for each individual across all samples: CLOZUK2 (ß = 12.22, SE = 3.78, p = .001), CLOZUK3 (ß = 12.73, SE = 5.99, p = .034), and the Norwegian cohort (ß = 46.45, SE = 18.83, p = .014). In a secondary analysis, the schizophrenia PRS was associated with taking clozapine doses >600 mg/day (odds ratio = 1.279, p = .006). CONCLUSIONS: The schizophrenia PRS was associated with the highest clozapine dose prescribed for an individual in records from 3 independent samples, suggesting that the genetic liability for schizophrenia might index factors associated with therapeutic decisions in cohorts of patients with treatment-resistant schizophrenia.

Association between the LRP1B and APOE loci and the development of Parkinson's disease dementia.

Parkinson's disease is one of the most common age-related neurodegenerative disorders. Although predominantly a motor disorder, cognitive impairment and dementia are important features of Parkinson's disease, particularly in the later stages of the disease. However, the rate of cognitive decline varies among Parkinson's disease patients, and the genetic basis for this heterogeneity is incompletely understood. To explore the genetic factors associated with rate of progression to Parkinson's disease dementia, we performed a genome-wide survival meta-analysis of 3923 clinically diagnosed Parkinson's disease cases of European ancestry from four longitudinal cohorts. In total, 6.7% of individuals with Parkinson's disease developed dementia during study follow-up, on average 4.4 ± 2.4 years from disease diagnosis. We have identified the APOE ε4 allele as a major risk factor for the conversion to Parkinson's disease dementia [hazard ratio = 2.41 (1.94-3.00), P = 2.32 × 10-15], as well as a new locus within the ApoE and APP receptor LRP1B gene [hazard ratio = 3.23 (2.17-4.81), P = 7.07 × 10-09]. In a candidate gene analysis, GBA variants were also identified to be associated with higher risk of progression to dementia [hazard ratio = 2.02 (1.21-3.32), P = 0.007]. CSF biomarker analysis also implicated the amyloid pathway in Parkinson's disease dementia, with significantly reduced levels of amyloid ß42 (P = 0.0012) in Parkinson's disease dementia compared to Parkinson's disease without dementia. These results identify a new candidate gene associated with faster conversion to dementia in Parkinson's disease and suggest that amyloid-targeting therapy may have a role in preventing Parkinson's disease dementia.

Universal clinical Parkinson's disease axes identify a major influence of neuroinflammation.

BACKGROUND: There is large individual variation in both clinical presentation and progression between Parkinson's disease patients. Generation of deeply and longitudinally phenotyped patient cohorts has enormous potential to identify disease subtypes for prognosis and therapeutic targeting. METHODS: Replicating across three large Parkinson's cohorts (Oxford Discovery cohort (n = 842)/Tracking UK Parkinson's study (n = 1807) and Parkinson's Progression Markers Initiative (n = 472)) with clinical observational measures collected longitudinally over 5-10 years, we developed a Bayesian multiple phenotypes mixed model incorporating genetic relationships between individuals able to explain many diverse clinical measurements as a smaller number of continuous underlying factors ("phenotypic axes"). RESULTS: When applied to disease severity at diagnosis, the most influential of three phenotypic axes "Axis 1" was characterised by severe non-tremor motor phenotype, anxiety and depression at diagnosis, accompanied by faster progression in cognitive function measures. Axis 1 was associated with increased genetic risk of Alzheimer's disease and reduced CSF Aß1-42 levels. As observed previously for Alzheimer's disease genetic risk, and in contrast to Parkinson's disease genetic risk, the loci influencing Axis 1 were associated with microglia-expressed genes implicating neuroinflammation. When applied to measures of disease progression for each individual, integration of Alzheimer's disease genetic loci haplotypes improved the accuracy of progression modelling, while integrating Parkinson's disease genetics did not. CONCLUSIONS: We identify universal axes of Parkinson's disease phenotypic variation which reveal that Parkinson's patients with high concomitant genetic risk for Alzheimer's disease are more likely to present with severe motor and non-motor features at baseline and progress more rapidly to early dementia.

Examining sex differences in neurodevelopmental and psychiatric genetic risk in anxiety and depression.

Anxiety and depression are common mental health disorders and have a higher prevalence in females. They are modestly heritable, share genetic liability with other psychiatric disorders, and are highly heterogeneous. There is evidence that genetic liability to neurodevelopmental disorders, such as attention deficit hyperactivity disorder (ADHD) is associated with anxiety and depression, particularly in females. We investigated sex differences in family history for neurodevelopmental and psychiatric disorders and neurodevelopmental genetic risk burden (indexed by ADHD polygenic risk scores (PRS) and rare copy number variants; CNVs) in individuals with anxiety and depression, also taking into account age at onset. We used two complementary datasets: 1) participants with a self-reported diagnosis of anxiety or depression (N = 4,178, 65.5% female; mean age = 41.5 years; N = 1,315 with genetic data) from the National Centre for Mental Health (NCMH) cohort and 2) a clinical sample of 13,273 (67.6% female; mean age = 45.2 years) patients with major depressive disorder (MDD) from the Psychiatric Genomics Consortium (PGC). We tested for sex differences in family history of psychiatric problems and presence of rare CNVs (neurodevelopmental and >500kb loci) in NCMH only and for sex differences in ADHD PRS in both datasets. In the NCMH cohort, females were more likely to report family history of neurodevelopmental and psychiatric disorders, but there were no robust sex differences in ADHD PRS or presence of rare CNVs. There was weak evidence of higher ADHD PRS in females compared to males in the PGC MDD sample, particularly in those with an early onset of MDD. These results do not provide strong evidence of sex differences in neurodevelopmental genetic risk burden in adults with anxiety and depression. This indicates that sex may not be a major index of neurodevelopmental genetic heterogeneity, that is captured by ADHD PRS and rare CNV burden, in adults with anxiety and depression.

Associations Between Schizophrenia Polygenic Liability, Symptom Dimensions, and Cognitive Ability in Schizophrenia.

Importance: Schizophrenia is a clinically heterogeneous disorder. It is currently unclear how variability in symptom dimensions and cognitive ability is associated with genetic liability for schizophrenia. Objective: To determine whether phenotypic dimensions within schizophrenia are associated with genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence. Design, Setting, and Participants: In a genetic association study, 3 cross-sectional samples of 1220 individuals with a diagnosis of schizophrenia were recruited from community, inpatient, and voluntary sector mental health services across the UK. Confirmatory factor analysis was used to create phenotypic dimensions from lifetime ratings of the Scale for the Assessment of Positive Symptoms, Scale for the Assessment of Negative Symptoms, and the MATRICS Consensus Cognitive Battery. Analyses of polygenic risk scores (PRSs) were used to assess whether genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence were associated with these phenotypic dimensions. Data collection for the cross-sectional studies occurred between 1993 and 2016. Data analysis for this study occurred between January 2019 and March 2021. Main Outcomes and Measures: Outcome measures included phenotypic dimensions defined from confirmatory factor analysis relating to positive symptoms, negative symptoms of diminished expressivity, negative symptoms of motivation and pleasure, disorganized symptoms, and current cognitive ability. Exposure measures included PRSs for schizophrenia, bipolar disorder, major depression, attention-deficit/hyperactivity disorder, autism spectrum disorder, and intelligence. Results: Of the 1220 study participants, 817 were men (67.0%). Participants' mean (SD) age at interview was 43.10 (12.74) years. Schizophrenia PRS was associated with increased disorganized symptom dimension scores in both a 5-factor model (ß = 0.14; 95% CI, 0.07-0.22; P = 2.80 × 10-4) and a 3-factor model across all samples (ß = 0.10; 95% CI, 0.05-0.15; P = 2.80 × 10-4). Current cognitive ability was associated with genetic liability to schizophrenia (ß = -0.11; 95% CI, -0.19 to -0.04; P = 1.63 × 10-3) and intelligence (ß = 0.23; 95% CI, 0.16-0.30; P = 1.52 × 10-10). After controlling for estimated premorbid IQ, current cognitive performance was associated with schizophrenia PRS (ß = -0.08; 95% CI, -0.14 to -0.02; P = 8.50 × 10-3) but not intelligence PRS. Conclusions and Relevance: The findings of this study suggest that genetic liability for schizophrenia is associated with higher disorganized dimension scores but not other symptom dimensions. Cognitive performance in schizophrenia appears to reflect distinct contributions from genetic liabilities to both intelligence and schizophrenia.

Sex differences in anxiety and depression in children with attention deficit hyperactivity disorder: Investigating genetic liability and comorbidity.

It is unknown why attention deficit hyperactivity disorder (ADHD) is more common in males, whereas anxiety and depression show a female population excess. We tested the hypothesis that anxiety and depression risk alleles manifest as ADHD in males. We also tested whether anxiety and depression in children with ADHD show a different etiology to typical anxiety and depression and whether this differs by sex. The primary clinical ADHD sample consisted of 885 (14% female) children. Psychiatric symptoms were assessed using standardized interviews. Polygenic risk scores (PRS) were derived using large genetic studies. Replication samples included independent clinical ADHD samples (N = 3,794; 25.7% female) and broadly defined population ADHD samples (N = 995; 33.4% female). We did not identify sex differences in anxiety or depression PRS in children with ADHD. In the primary sample, anxiety PRS were associated with social and generalized anxiety in males, with evidence of a sex-by-PRS interaction for social anxiety. These results did not replicate in the broadly defined ADHD sample. Depression PRS were not associated with comorbid depression symptoms. The results suggest that anxiety and depression genetic risks are not more likely to lead to ADHD in males. Also, the evidence for shared etiology between anxiety symptoms in those with ADHD and typical anxiety was weak and needs replication.

Risk Factors, Clinical Features, and Polygenic Risk Scores in Schizophrenia and Schizoaffective Disorder Depressive-Type.

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 disorganized 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.

Rare Copy Number Variants Are Associated With Poorer Cognition in Schizophrenia.

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 (ß = -0.66, 95% confidence interval [CI] = -1.31 to -0.01) and replication samples (ß = -0.91, 95% CI = -1.71 to -0.11) and after meta-analysis (ß = -0.76, 95% CI = -1.26 to -0.25, p = .003). CNVs hitting loss-of-function intolerant genes were associated with lower cognition (ß = -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.

Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets.

Importance: Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective: To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting: This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures: It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. Results: Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance: Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies.

Genome-Wide Association Studies of Cognitive and Motor Progression in Parkinson's Disease.

BACKGROUND: There are currently no treatments that stop or slow the progression of Parkinson's disease (PD). Case-control genome-wide association studies have identified variants associated with disease risk, but not progression. The objective of the current study was to identify genetic variants associated with PD progression. METHODS: We analyzed 3 large longitudinal cohorts: Tracking Parkinson's, Oxford Discovery, and the Parkinson's Progression Markers Initiative. We included clinical data for 3364 patients with 12,144 observations (mean follow-up 4.2 years). We used a new method in PD, following a similar approach in Huntington's disease, in which we combined multiple assessments using a principal components analysis to derive scores for composite, motor, and cognitive progression. These scores were analyzed in linear regression in genome-wide association studies. We also performed a targeted analysis of the 90 PD risk loci from the latest case-control meta-analysis. RESULTS: There was no overlap between variants associated with PD risk, from case-control studies, and PD age at onset versus PD progression. The APOE ε4 tagging variant, rs429358, was significantly associated with composite and cognitive progression in PD. Conditional analysis revealed several independent signals in the APOE locus for cognitive progression. No single variants were associated with motor progression. However, in gene-based analysis, ATP8B2, a phospholipid transporter related to vesicle formation, was nominally associated with motor progression (P = 5.3 × 10-6 ). CONCLUSIONS: We provide early evidence that this new method in PD improves measurement of symptom progression. We show that the APOE ε4 allele drives progressive cognitive impairment in PD. Replication of this method and results in independent cohorts are needed. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genetic analysis of Mendelian mutations in a large UK population-based Parkinson's disease study.

Our objective was to define the prevalence and clinical features of genetic Parkinson's disease in a large UK population-based cohort, the largest multicentre prospective clinico-genetic incident study in the world. We collected demographic data, Movement Disorder Society Unified Parkinson's Disease Rating Scale scores, and Montreal Cognitive Assessment scores. We analysed mutations in PRKN (parkin), PINK1, LRRK2 and SNCA in relation to age at symptom onset, family history and clinical features. Of the 2262 participants recruited to the Tracking Parkinson's study, 424 had young-onset Parkinson's disease (age at onset ≤ 50) and 1799 had late onset Parkinson's disease. A range of methods were used to genotype 2005 patients: 302 young-onset patients were fully genotyped with multiplex ligation-dependent probe amplification and either Sanger and/or exome sequencing; and 1701 late-onset patients were genotyped with the LRRK2 'Kompetitive' allele-specific polymerase chain reaction assay and/or exome sequencing (two patients had missing age at onset). We identified 29 (1.4%) patients carrying pathogenic mutations. Eighteen patients carried the G2019S or R1441C mutations in LRRK2, and one patient carried a heterozygous duplication in SNCA. In PRKN, we identified patients carrying deletions of exons 1, 4 and 5, and P113Xfs, R275W, G430D and R33X. In PINK1, two patients carried deletions in exon 1 and 5, and the W90Xfs point mutation. Eighteen per cent of patients with age at onset ≤30 and 7.4% of patients from large dominant families carried pathogenic Mendelian gene mutations. Of all young-onset patients, 10 (3.3%) carried biallelic mutations in PRKN or PINK1. Across the whole cohort, 18 patients (0.9%) carried pathogenic LRRK2 mutations and one (0.05%) carried an SNCA duplication. There is a significant burden of LRRK2 G2019S in patients with both apparently sporadic and familial disease. In young-onset patients, dominant and recessive mutations were equally common. There were no differences in clinical features between LRRK2 carriers and non-carriers. However, we did find that PRKN and PINK1 mutation carriers have distinctive clinical features compared to young-onset non-carriers, with more postural symptoms at diagnosis and less cognitive impairment, after adjusting for age and disease duration. This supports the idea that there is a distinct clinical profile of PRKN and PINK1-related Parkinson's disease. We estimate that there are approaching 1000 patients with a known genetic aetiology in the UK Parkinson's disease population. A small but significant number of patients carry causal variants in LRRK2, SNCA, PRKN and PINK1 that could potentially be targeted by new therapies, such as LRRK2 inhibitors.

Association of Genetic Risk for Rheumatoid Arthritis With Cognitive and Psychiatric Phenotypes Across Childhood and Adolescence.

Importance: The association of rheumatoid arthritis (RA) with cognitive and psychiatric phenotypes has been recognized. However, it is not known whether these phenotypes are a consequence of disease-related factors, such as pain, or reflect shared etiological factors. Objective: To investigate whether genomic risk for RA is associated with cognitive and psychiatric symptoms in children and adolescents. Design, Setting, and Participants: This cohort study analyzed data from 3296 to 5936 adolescents (depending on outcome) from the Avon Longitudinal Study of Parents and Children. Clinical and questionnaire data were collected periodically from September 6, 1990, with collection ongoing, and analyzed from August 21, 2017, to May 21, 2018. Exposures: Polygenic risk scores (PRSs) for RA. Main Outcomes and Measures: Measures of cognition (including IQ, working memory, verbal learning, processing speed, problem solving, selective attention, and attentional control) and psychopathology (including anxiety, depression, negative symptoms, psychotic experiences, attention-deficit/hyperactivity disorder, and hyperactive and inattentive symptoms) in childhood and adolescence. Results: Polygenic risk scores for RA were generated for 7977 children and adolescents (3885 [48.7%] female). Of these 7977 participants, 9 (0.11%) had a known diagnosis of RA at age 22 years. Increased PRS for RA was associated with lower total IQ (ß, -0.05; 95% CI, -0.07 to -0.02; P < .001), performance IQ (ß, -0.03; 95% CI, -0.06 to -0.005; P = .02), and verbal IQ (ß, -0.05; 95% CI, -0.08 to -0.02; P < .001) at age 8 years (mean [SD] age at measurement, 8.6 [0.3] years) and symptoms of hyperactivity and inattention from ages 4 to 16 years, with the strongest evidence of association at age 13 years (mean [SD] age at assessment, 13.2 [0.2] years). The odds ratio at this age per SD increase in PRS was 1.25 (95% CI, 1.12-1.39) (P < .001). There was little evidence of association between the RA PRS and other measures of cognition and psychopathology. Gene-based analyses indicated that polygenic signal for RA was enriched for immune pathways (q ≤ 0.05). No equivalent associations were seen for polygenic risk associated with inflammatory bowel disease or multiple sclerosis. Conclusions and Relevance: These findings support an association between genetic risk for RA and neural phenotypes, suggesting that cognitive impairment in RA is not simply secondary to disease-related processes or treatment effects. These results may suggest that genetic susceptibility for RA might affect psychological well-being in early life and reinforce the emerging link between mental health and the immune system.

Publisher Correction: Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.