Benchmarking network-based gene prioritization methods for cerebral small vessel disease.

Network-based gene prioritization algorithms are designed to prioritize disease-associated genes based on known ones using biological networks of protein interactions, gene-disease associations (GDAs) and other relationships between biological entities. Various algorithms have been developed based on different mechanisms, but it is not obvious which algorithm is optimal for a specific disease. To address this issue, we benchmarked multiple algorithms for their application in cerebral small vessel disease (cSVD). We curated protein-gene interactions (PGIs) and GDAs from databases and assembled PGI networks and disease-gene heterogeneous networks. A screening of algorithms resulted in seven representative algorithms to be benchmarked. Performance of algorithms was assessed using both leave-one-out cross-validation (LOOCV) and external validation with MEGASTROKE genome-wide association study (GWAS). We found that random walk with restart on the heterogeneous network (RWRH) showed best LOOCV performance, with median LOOCV rediscovery rank of 185.5 (out of 19 463 genes). The GenePanda algorithm had most GWAS-confirmable genes in top 200 predictions, while RWRH had best ranks for small vessel stroke-associated genes confirmed in GWAS. In conclusion, RWRH has overall better performance for application in cSVD despite its susceptibility to bias caused by degree centrality. Choice of algorithms should be determined before applying to specific disease. Current pure network-based gene prioritization algorithms are unlikely to find novel disease-associated genes that are not associated with known ones. The tools for implementing and benchmarking algorithms have been made available and can be generalized for other diseases.

Whole-exome sequencing reveals a role of HTRA1 and EGFL8 in brain white matter hyperintensities.

White matter hyperintensities (WMH) are among the most common radiological abnormalities in the ageing population and an established risk factor for stroke and dementia. While common variant association studies have revealed multiple genetic loci with an influence on their volume, the contribution of rare variants to the WMH burden in the general population remains largely unexplored. We conducted a comprehensive analysis of this burden in the UK Biobank using publicly available whole-exome sequencing data (n up to 17 830) and found a splice-site variant in GBE1, encoding 1,4-alpha-glucan branching enzyme 1, to be associated with lower white matter burden on an exome-wide level [c.691+2T>C, ß = -0.74, standard error (SE) = 0.13, P = 9.7 × 10-9]. Applying whole-exome gene-based burden tests, we found damaging missense and loss-of-function variants in HTRA1 (frequency of 1 in 275 in the UK Biobank population) to associate with an increased WMH volume (P = 5.5 × 10-6, false discovery rate = 0.04). HTRA1 encodes a secreted serine protease implicated in familial forms of small vessel disease. Domain-specific burden tests revealed that the association with WMH volume was restricted to rare variants in the protease domain (amino acids 204-364; ß = 0.79, SE = 0.14, P = 9.4 × 10-8). The frequency of such variants in the UK Biobank population was 1 in 450. The WMH volume was brought forward by ∼11 years in carriers of a rare protease domain variant. A comparison with the effect size of established risk factors for WMH burden revealed that the presence of a rare variant in the HTRA1 protease domain corresponded to a larger effect than meeting the criteria for hypertension (ß = 0.26, SE = 0.02, P = 2.9 × 10-59) or being in the upper 99.8% percentile of the distribution of a polygenic risk score based on common genetic variants (ß = 0.44, SE = 0.14, P = 0.002). In biochemical experiments, most (6/9) of the identified protease domain variants resulted in markedly reduced protease activity. We further found EGFL8, which showed suggestive evidence for association with WMH volume (P = 1.5 × 10-4, false discovery rate = 0.22) in gene burden tests, to be a direct substrate of HTRA1 and to be preferentially expressed in cerebral arterioles and arteries. In a phenome-wide association study mapping ICD-10 diagnoses to 741 standardized Phecodes, rare variants in the HTRA1 protease domain were associated with multiple neurological and non-neurological conditions including migraine with aura (odds ratio = 12.24, 95%CI: 2.54-35.25; P = 8.3 × 10-5]. Collectively, these findings highlight an important role of rare genetic variation and the HTRA1 protease in determining WMH burden in the general population.

Genome-wide association study of multisite chronic pain in UK Biobank.

Chronic pain is highly prevalent worldwide and represents a significant socioeconomic and public health burden. Several aspects of chronic pain, for example back pain and a severity-related phenotype 'chronic pain grade', have been shown previously to be complex heritable traits with a polygenic component. Additional pain-related phenotypes capturing aspects of an individual's overall sensitivity to experiencing and reporting chronic pain have also been suggested as a focus for investigation. We made use of a measure of the number of sites of chronic pain in individuals within the UK general population. This measure, termed Multisite Chronic Pain (MCP), is a complex trait and its genetic architecture has not previously been investigated. To address this, we carried out a large-scale genome-wide association study (GWAS) of MCP in ~380,000 UK Biobank participants. Our findings were consistent with MCP having a significant polygenic component, with a Single Nucleotide Polymorphism (SNP) heritability of 10.2%. In total 76 independent lead SNPs at 39 risk loci were associated with MCP. Additional gene-level association analyses identified neurogenesis, synaptic plasticity, nervous system development, cell-cycle progression and apoptosis genes as enriched for genetic association with MCP. Genetic correlations were observed between MCP and a range of psychiatric, autoimmune and anthropometric traits, including major depressive disorder (MDD), asthma and Body Mass Index (BMI). Furthermore, in Mendelian randomisation (MR) analyses a causal effect of MCP on MDD was observed. Additionally, a polygenic risk score (PRS) for MCP was found to significantly predict chronic widespread pain (pain all over the body), indicating the existence of genetic variants contributing to both of these pain phenotypes. Overall, our findings support the proposition that chronic pain involves a strong nervous system component with implications for our understanding of the physiology of chronic pain. These discoveries may also inform the future development of novel treatment approaches.

Correction: The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function.

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

The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function.

Genome-wide association studies (GWAS) of psychiatric phenotypes have tended to focus on categorical diagnoses, but to understand the biology of mental illness it may be more useful to study traits which cut across traditional boundaries. Here, we report the results of a GWAS of mood instability as a trait in a large population cohort (UK Biobank, n = 363,705). We also assess the clinical and biological relevance of the findings, including whether genetic associations show enrichment for nervous system pathways. Forty six unique loci associated with mood instability were identified with a SNP heritability estimate of 9%. Linkage Disequilibrium Score Regression (LDSR) analyses identified genetic correlations with Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizophrenia, anxiety, and Post Traumatic Stress Disorder (PTSD). Gene-level and gene set analyses identified 244 significant genes and 6 enriched gene sets. Tissue expression analysis of the SNP-level data found enrichment in multiple brain regions, and eQTL analyses highlighted an inversion on chromosome 17 plus two brain-specific eQTLs. In addition, we used a Phenotype Linkage Network (PLN) analysis and community analysis to assess for enrichment of nervous system gene sets using mouse orthologue databases. The PLN analysis found enrichment in nervous system PLNs for a community containing serotonin and melatonin receptors. In summary, this work has identified novel loci, tissues and gene sets contributing to mood instability. These findings may be relevant for the identification of novel trans-diagnostic drug targets and could help to inform future stratified medicine innovations in mental health.

Carotid Intima-Media Thickness: Novel Loci, Sex-Specific Effects, and Genetic Correlations With Obesity and Glucometabolic Traits in UK Biobank.

OBJECTIVE: Atherosclerosis is the underlying cause of most cardiovascular disease, but mechanisms underlying atherosclerosis are incompletely understood. Ultrasound measurement of the carotid intima-media thickness (cIMT) can be used to measure vascular remodeling, which is indicative of atherosclerosis. Genome-wide association studies have identified many genetic loci associated with cIMT, but heterogeneity of measurements collected by many small cohorts have been a major limitation in these efforts. Here, we conducted genome-wide association analyses in UKB (UK Biobank; N=22 179), the largest single study with consistent cIMT measurements. Approach and Results: We used BOLT-LMM software to run linear regression of cIMT in UKB, adjusted for age, sex, and genotyping chip. In white British participants, we identified 5 novel loci associated with cIMT and replicated most previously reported loci. In the first sex-specific analyses of cIMT, we identified a locus on chromosome 5, associated with cIMT in women only and highlight VCAN as a good candidate gene at this locus. Genetic correlations with body mass index and glucometabolic traits were also observed. Two loci influenced risk of ischemic heart disease. CONCLUSIONS: These findings replicate previously reported associations, highlight novel biology, and provide new directions for investigating the sex differences observed in cardiovascular disease presentation and progression.

The dual phosphodiesterase 3 and 4 inhibitor RPL554 stimulates CFTR and ciliary beating in primary cultures of bronchial epithelia.

Cystic fibrosis (CF), a genetic disease caused by mutations in the CFTR gene, is a life-limiting disease characterized by chronic bacterial airway infection and severe inflammation. Some CFTR mutants have reduced responsiveness to cAMP/PKA signaling; hence, pharmacological agents that elevate intracellular cAMP are potentially useful for the treatment of CF. By inhibiting cAMP breakdown, phosphodiesterase (PDE) inhibitors stimulate CFTR in vitro and in vivo. Here, we demonstrate that PDE inhibition by RPL554, a drug that has been shown to cause bronchodilation in asthma and chronic obstructive pulmonary disease (COPD) patients, stimulates CFTR-dependent ion secretion across bronchial epithelial cells isolated from patients carrying the R117H/F508del CF genotype. RPL554-induced CFTR activity was further increased by the potentiator VX-770, suggesting an additional benefit by the drug combination. RPL554 also increased cilia beat frequency in primary human bronchial epithelial cells. The results indicate RPL554 may increase mucociliary clearance through stimulation of CFTR and increasing ciliary beat frequency and thus could provide a novel therapeutic option for CF.

Investigating light sensitivity in bipolar disorder (HELIOS-BD).

Many people with bipolar disorder have disrupted circadian rhythms. This means that the timing of sleep and wake activities becomes out-of-sync with the standard 24-hour cycle. Circadian rhythms are strongly influenced by light levels and previous research suggests that people with bipolar disorder might have a heightened sensitivity to light, causing more circadian rhythm disruption, increasing the potential for triggering a mood switch into mania or depression. Lithium has been in clinical use for over 70 years and is acknowledged to be the most effective long-term treatment for bipolar disorder. Lithium has many reported actions in the body but the precise mechanism of action in bipolar disorder remains an active area of research. Central to this project is recent evidence that lithium may work by stabilising circadian rhythms of mood, cognition and rest/activity. Our primary hypothesis is that people with bipolar disorder have some pathophysiological change at the level of the retina which makes them hypersensitive to the visual and non-visual effects of light, and therefore more susceptible to circadian rhythm dysfunction. We additionally hypothesise that the mood-stabilising medication lithium is effective in bipolar disorder because it reduces this hypersensitivity, making individuals less vulnerable to light-induced circadian disruption. We will recruit 180 participants into the HELIOS-BD study. Over an 18-month period, we will assess visual and non-visual responses to light, as well as retinal microstructure, in people with bipolar disorder compared to healthy controls. Further, we will assess whether individuals with bipolar disorder who are being treated with lithium have less pronounced light responses and attenuated retinal changes compared to individuals with bipolar disorder not being treated with lithium. This study represents a comprehensive investigation of visual and non-visual light responses in a large bipolar disorder population, with great translational potential for patient stratification and treatment innovation.

Mucolytic treatment of chronic rhinosinusitis in a murine model of primary ciliary dyskinesia.

Background: Genetic defects in motile cilia cause primary ciliary dyskinesia (PCD), a rare disease with no specific therapeutics. Individuals with PCD often have impaired fertility and laterality defects and universally suffer from upper and lower airway diseases. Chronic rhinosinusitis is a universal feature of PCD, and mucus accumulation and subsequent infections of the sinonasal cavity cause significant morbidity in individuals with PCD. Despite this, there are no approved treatments that specifically target mucus. Objective: The goals of this study were to determine whether computed tomography (CT) imaging could be used to quantify mucus accumulation and whether the use of a mucolytic agent to reduce disulfide cross-links present in mucins would improve the effectiveness of nasal lavage at removing mucus in a murine model of PCD. Methods: Adult mice with a deletion of the axonemal dynein Dnaic1 were imaged using CT scanning to characterize mucus accumulation. The animals were then treated by nasal lavage with saline, with/without the disulfide-reducing agent tris(2-carboxyethyl)phosphine. Post-treatment CT scans were used to quantify improvement in the sinonasal cavity. Results: Mucus accumulation in the nasal cavity was readily quantified by CT. Compared to sham-treated control animals, nasal lavage with/without a mucolytic agent resulted in a significant reduction of accumulated mucus (p < 0.01). Treatment with the mucolytic agent showed a greater reduction of accumulated mucus than treatment with saline alone. Conclusion: The results suggest that inclusion of a mucolytic agent may increase the effectiveness of nasal lavage at reducing mucus burden in PCD.

Frequency and Phenotype Associations of Rare Variants in 5 Monogenic Cerebral Small Vessel Disease Genes in 200,000 UK Biobank Participants.

Background and Objectives: Based on previous case reports and disease-based cohorts, a minority of patients with cerebral small vessel disease (cSVD) have a monogenic cause, with many also manifesting extracerebral phenotypes. We investigated the frequency, penetrance, and phenotype associations of putative pathogenic variants in cSVD genes in the UK Biobank (UKB), a large population-based study. Methods: We used a systematic review of previous literature and ClinVar to identify putative pathogenic rare variants in CTSA, TREX1, HTRA1, and COL4A1/2. We mapped phenotypes previously attributed to these variants (phenotypes-of-interest) to disease coding systems used in the UKB's linked health data from UK hospital admissions, death records, and primary care. Among 199,313 exome-sequenced UKB participants, we assessed the following: the proportion of participants carrying ≥1 variant(s); phenotype-of-interest penetrance; and the association between variant carrier status and phenotypes-of-interest using a binary (any phenotype present/absent) and phenotype burden (linear score of the number of phenotypes a participant possessed) approach. Results: Among UKB participants, 0.5% had ≥1 variant(s) in studied genes. Using hospital admission and death records, 4%-20% of variant carriers per gene had an associated phenotype. This increased to 7%-55% when including primary care records. Only COL4A1 variant carrier status was significantly associated with having ≥1 phenotype-of-interest and a higher phenotype score (OR = 1.29, p = 0.006). Discussion: While putative pathogenic rare variants in monogenic cSVD genes occur in 1:200 people in the UKB population, only approximately half of variant carriers have a relevant disease phenotype recorded in their linked health data. We could not replicate most previously reported gene-phenotype associations, suggesting lower penetrance rates, overestimated pathogenicity, and/or limited statistical power.

Systematic Review of Cerebral Phenotypes Associated With Monogenic Cerebral Small-Vessel Disease.

Background Cerebral small-vessel disease (cSVD) is an important cause of stroke and vascular dementia. Most cases are multifactorial, but an emerging minority have a monogenic cause. While NOTCH3 is the best-known gene, several others have been reported. We aimed to summarize the cerebral phenotypes associated with these more recent cSVD genes. Methods and Results We performed a systematic review (PROSPERO [International Prospective Register of Systematic Reviews]: CRD42020196720), searching Medline/Embase (conception to July 2020) for any language publications describing COL4A1/2, TREX1, HTRA1, ADA2, or CTSA pathogenic variant carriers. We extracted data about individuals' characteristics and clinical and vascular radiological cerebral phenotypes. We summarized phenotype frequencies per gene, comparing patterns across genes. We screened 6485 publications including 402, and extracted data on 390 individuals with COL4A1, 123 with TREX1, 44 with HTRA1 homozygous, 41 with COL4A2, 346 with ADA2, 82 with HTRA1 heterozygous, and 14 with CTSA. Mean age ranged from 15 (ADA2) to 59 years (HTRA1 heterozygotes). Clinical phenotype frequencies varied widely: stroke, 9% (TREX1) to 52% (HTRA1 heterozygotes); cognitive features, 0% (ADA2) to 64% (HTRA1 homozygotes); and psychiatric features, 0% (COL4A2; ADA2) to 57% (CTSA). Among individuals with neuroimaging, vascular radiological phenotypes appeared common, ranging from 62% (ADA2) to 100% (HTRA1 homozygotes; CTSA). White matter lesions were the most common pathology, except in ADA2 and COL4A2 cases, where ischemic and hemorrhagic lesions dominated, respectively. Conclusions There appear to be differences in cerebral manifestations across cSVD genes. Vascular radiological changes were more common than clinical neurological phenotypes, and present in the majority of individuals with reported neuroimaging. However, these results may be affected by age and biases inherent to case reports. In the future, better characterization of associated phenotypes, as well as insights from population-based studies, should improve our understanding of monogenic cSVD to inform genetic testing, guide clinical management, and help unravel underlying disease mechanisms.

Physician-Confirmed and Administrative Definitions of Stroke in UK Biobank Reflect the Same Underlying Genetic Trait.

BACKGROUND: Stroke in UK Biobank (UKB) is ascertained via linkages to coded administrative datasets and self-report. We studied the accuracy of these codes using genetic validation. METHODS: We compiled stroke-specific and broad cerebrovascular disease (CVD) code lists (Read V2/V3, ICD-9/-10) for medical settings (hospital, death record, primary care) and self-report. Among 408,210 UKB participants, we identified all with a relevant code, creating 12 stroke definitions based on the code type and source. We performed genome-wide association studies (GWASs) for each definition, comparing summary results against the largest published stroke GWAS (MEGASTROKE), assessing genetic correlations, and replicating 32 stroke-associated loci. RESULTS: The stroke case numbers identified varied widely from 3,976 (primary care stroke-specific codes) to 19,449 (all codes, all sources). All 12 UKB stroke definitions were significantly correlated with the MEGASTROKE summary GWAS results (rg.81-1) and each other (rg.4-1). However, Bonferroni-corrected confidence intervals were wide, suggesting limited precision of some results. Six previously reported stroke-associated loci were replicated using ≥1 UKB stroke definition. CONCLUSIONS: Stroke case numbers in UKB depend on the code source and type used, with a 5-fold difference in the maximum case-sample size. All stroke definitions are significantly genetically correlated with the largest stroke GWAS to date.

The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals.

Understanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.

Use of Procalcitonin for Identification of Cobacterial Pneumonia in Pediatric Patients.

OBJECTIVE: To evaluate the utility of procalcitonin (PCT) in identifying cobacterial pneumonia in pediatric patients with known viral respiratory infection. METHODS: A retrospective cohort study was conducted in a stand-alone children's hospital during 2 time periods (period 1: October 1, 2014, to March 31, 2015; period 2: October 1, 2015, to March 31, 2016). Patients admitted with any upper respiratory tract infection were included. Exclusion criteria included any condition compromising lung function, age <30 days or >18 years, or lack of PCT (period 2). PCT values of <0.5 ng/mL were considered normal, whereas values of >1.5 ng/mL were used to identify cobacterial pneumonia. Receiver-operator characteristic curves were used with multiple logistic regression to evaluate patient variables. RESULTS: Of the 374 pediatric patients evaluated, 64% were classified as having viral pneumonia and 23% as having cobacterial pneumonia across both study time periods. Non-significant predictors of cobacterial pneumonia included temperature (p = 0.0795, p = 0.1466), WBC count (p = 0.8774, p = 0.6675), and C-reactive protein (p = 0.7115, p = 0.3835). Median initial PCT for patients with viral pneumonia was 0.14 ng/mL compared with 1.41 ng/mL in patients with cobacterial pneumonia; median second PCTs were 0.26 ng/mL (viral pneumonia) and 4.55 ng/mL (cobacterial pneumonia). Patients with an elevated PCT had 17.5 times (95% CI, 5.2, 59.1) greater odds of having a cobacterial pneumonia. CONCLUSIONS: PCT was found to be strongly associated with cobacterial pneumonia with an underlying viral etiology. Temperature, WBC, and C-reactive protein failed to be significant predictors in differentiating between viral and cobacterial pneumonia.

Association of SBP and BMI with cognitive and structural brain phenotypes in UK Biobank.

OBJECTIVE: To test for associations between SBP and BMI, with domain-specific cognitive abilities and examine which brain structural phenotypes mediate those associations. METHODS: Using cross-sectional UK Biobank data (final N = 28 412), we examined SBP/BMI vs. cognitive test scores of pairs-matching, matrix completion, trail making test A/B, digit symbol substitution, verbal-numerical reasoning, tower rearranging and simple reaction time. We adjusted for potential confounders of age, sex, deprivation, medication, apolipoprotein e4 genotype, smoking, population stratification and genotypic array. We tested for mediation via multiple structural brain imaging phenotypes and corrected for multiple testing with false discovery rate. RESULTS: We found positive associations for higher BMI with worse reaction time, reasoning, tower rearranging and matrix completion tasks by 0.024-0.067 SDs per BMI SD (all P < 0.001). Higher SBP was associated with worse reasoning (0.034 SDs) and matrix completion scores (-0.024 SDs; both P < 0.001). Both BMI and SBP were associated with multiple brain structural metrics including total grey/white matter volumes, frontal lobe volumes, white matter tract integrity and white matter hyperintensity volumes: specific metrics mediated around one-third of the associations with cognition. CONCLUSION: Our findings add to the body of evidence that addressing cardiovascular risk factors may also preserve cognitive function, via specific aspects of brain structure.

Exploring the Role of Contactins across Psychological, Psychiatric and Cardiometabolic Traits within UK Biobank.

Individuals with severe mental illness have an increased risk of cardiometabolic diseases compared to the general population. Shared risk factors and medication effects explain part of this excess risk; however, there is growing evidence to suggest that shared biology (including genetic variation) is likely to contribute to comorbidity between mental and physical illness. Contactins are a family of genes involved in development of the nervous system and implicated, though genome-wide association studies, in a wide range of psychological, psychiatric and cardiometabolic conditions. Contactins are plausible candidates for shared pathology between mental and physical health. We used data from UK Biobank to systematically assess how genetic variation in contactin genes was associated with a wide range of psychological, psychiatric and cardiometabolic conditions. We also investigated whether associations for cardiometabolic and psychological traits represented the same or distinct signals and how the genetic variation might influence the measured traits. We identified: A novel genetic association between variation in CNTN1 and current smoking; two independent signals in CNTN4 for BMI; and demonstrated that associations between CNTN5 and neuroticism were distinct from those between CNTN5 and blood pressure/HbA1c. There was no evidence that the contactin genes contributed to shared aetiology between physical and mental illness.

Alzheimer's Disease Susceptibility Gene Apolipoprotein E (APOE) and Blood Biomarkers in UK Biobank (N = 395,769).

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition where the underlying etiology is still unclear. Investigating the potential influence of apolipoprotein E (APOE), a major genetic risk factor, on common blood biomarkers could provide a greater understanding of the mechanisms of AD and dementia risk. OBJECTIVE: Our objective was to conduct the largest (to date) single-protocol investigation of blood biomarkers in the context of APOE genotype, in UK Biobank. METHODS: After quality control and exclusions, data on 395,769 participants of White European ancestry were available for analysis. Linear regressions were used to test potential associations between APOE genotypes and biomarkers. RESULTS: Several biomarkers significantly associated with APOEɛ4 'risk' and ɛ2 'protective' genotypes (versus neutral ɛ3/ɛ3). Most associations supported previous data: for example, ɛ4 genotype was associated with elevated low-density lipoprotein cholesterol (LDL) (standardized beta [b] = 0.150 standard deviations [SDs] per allele, p < 0.001) and ɛ2 with lower LDL (b = -0.456 SDs, p < 0.001). There were however instances of associations found in unexpected directions: e.g., ɛ4 and increased insulin-like growth factor (IGF-1) (b = 0.017, p < 0.001) where lower levels have been previously suggested as an AD risk factor. CONCLUSION: These findings highlight biomarker differences in non-demented people at genetic risk for dementia. The evidence herein supports previous hypotheses of involvement from cardiometabolic and neuroinflammatory pathways.

Novel genome-wide associations for anhedonia, genetic correlation with psychiatric disorders, and polygenic association with brain structure.

Anhedonia is a core symptom of several psychiatric disorders but its biological underpinnings are poorly understood. We performed a genome-wide association study of state anhedonia in 375,275 UK Biobank participants and assessed for genetic correlation between anhedonia and neuropsychiatric conditions (major depressive disorder, schizophrenia, bipolar disorder, obsessive compulsive disorder and Parkinson's Disease). We then used a polygenic risk score approach to test for association between genetic loading for anhedonia and both brain structure and brain function. This included: magnetic resonance imaging (MRI) assessments of total grey matter volume, white matter volume, cerebrospinal fluid volume, and 15 cortical/subcortical regions of interest; diffusion tensor imaging (DTI) measures of white matter tract integrity; and functional MRI activity during an emotion processing task. We identified 11 novel loci associated at genome-wide significance with anhedonia, with a SNP heritability estimate (h2SNP) of 5.6%. Strong positive genetic correlations were found between anhedonia and major depressive disorder, schizophrenia and bipolar disorder; but not with obsessive compulsive disorder or Parkinson's Disease. Polygenic risk for anhedonia was associated with poorer brain white matter integrity, smaller total grey matter volume, and smaller volumes of brain regions linked to reward and pleasure processing, including orbito-frontal cortex. In summary, the identification of novel anhedonia-associated loci substantially expands our current understanding of the biological basis of state anhedonia and genetic correlations with several psychiatric disorders confirm the utility of this phenotype as a transdiagnostic marker of vulnerability to mental illness. We also provide the first evidence that genetic risk for state anhedonia influences brain structure, including in regions associated with reward and pleasure processing.

Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide.

BACKGROUND: Suicide is a major issue for global public health. Suicidality describes a broad spectrum of thoughts and behaviours, some of which are common in the general population. Although suicide results from a complex interaction of multiple social and psychological factors, predisposition to suicidality is at least partly genetic. METHODS: Ordinal genome-wide association study of suicidality in the UK Biobank cohort comparing: 'no suicidality' controls (N = 83,557); 'thoughts that life was not worth living' (N = 21,063); 'ever contemplated self-harm' (N = 13,038); 'act of deliberate self-harm in the past' (N = 2498); and 'previous suicide attempt' (N = 2666). OUTCOMES: We identified three novel genome-wide significant loci for suicidality (on chromosomes nine, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (rg 0·81). INTERPRETATION: These findings provide new information about genetic variants relating to increased risk of suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level. FUND: UKRI Innovation-HDR-UK Fellowship (MR/S003061/1). MRC Mental Health Data Pathfinder Award (MC_PC_17217). MRC Doctoral Training Programme Studentship at the University of Glasgow (MR/K501335/1). MRC Doctoral Training Programme Studentship at the Universities of Glasgow and Edinburgh. UKRI Innovation Fellowship (MR/R024774/1).

Genetic variation in CADM2 as a link between psychological traits and obesity.

CADM2 has been associated with a range of behavioural and metabolic traits, including physical activity, risk-taking, educational attainment, alcohol and cannabis use and obesity. Here, we set out to determine whether CADM2 contributes to mechanisms shared between mental and physical health disorders. We assessed genetic variants in the CADM2 locus for association with phenotypes in the UK Biobank, IMPROVE, PROCARDIS and SCARFSHEEP studies, before performing meta-analyses. A wide range of metabolic phenotypes were meta-analysed. Psychological phenotypes analysed in UK Biobank only were major depressive disorder, generalised anxiety disorder, bipolar disorder, neuroticism, mood instability and risk-taking behaviour. In UK Biobank, four, 88 and 172 genetic variants were significantly (p < 1 × 10-5) associated with neuroticism, mood instability and risk-taking respectively. In meta-analyses of 4 cohorts, we identified 362, 63 and 11 genetic variants significantly (p < 1 × 10-5) associated with BMI, SBP and CRP respectively. Genetic effects on BMI, CRP and risk-taking were all positively correlated, and were consistently inversely correlated with genetic effects on SBP, mood instability and neuroticism. Conditional analyses suggested an overlap in the signals for physical and psychological traits. Many significant variants had genotype-specific effects on CADM2 expression levels in adult brain and adipose tissues. CADM2 variants influence a wide range of both psychological and metabolic traits, suggesting common biological mechanisms across phenotypes via regulation of CADM2 expression levels in adipose tissue. Functional studies of CADM2 are required to fully understand mechanisms connecting mental and physical health conditions.