Golgi apparatus, endoplasmic reticulum and mitochondrial function implicated in Alzheimer's disease through polygenic risk and RNA sequencing.

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.

Tissue specific LRRK2 interactomes reveal a distinct striatal functional unit.

Mutations in LRRK2 are the most common genetic cause of Parkinson's disease. Despite substantial research efforts, the physiological and pathological role of this multidomain protein remains poorly defined. In this study, we used a systematic approach to construct the general protein-protein interactome around LRRK2, which was then evaluated taking into consideration the differential expression patterns and the co-expression behaviours of the LRRK2 interactors in 15 different healthy tissue types. The LRRK2 interactors exhibited distinct expression features in the brain as compared to the peripheral tissues analysed. Moreover, a high degree of similarity was found for the LRRK2 interactors in putamen, caudate and nucleus accumbens, thus defining a potential LRRK2 functional cluster within the striatum. The general LRRK2 interactome paired with the expression profiles of its members constitutes a powerful tool to generate tissue-specific LRRK2 interactomes. We exemplified the generation of the tissue-specific LRRK2 interactomes and explored the functions highlighted by the "core LRRK2 interactors" in the striatum in comparison with the cerebellum. Finally, we illustrated how the LRRK2 general interactome reported in this manuscript paired with the expression profiles can be used to trace the relationship between LRRK2 and specific interactors of interest, here focusing on the LRRK2 interactors belonging to the Rab protein family.

Plasma biomarkers and genetics in the diagnosis and prediction of Alzheimer's disease.

Plasma biomarkers for Alzheimer's disease-related pathologies have undergone rapid developments during the past few years, and there are now well-validated blood tests for amyloid and tau pathology, as well as neurodegeneration and astrocytic activation. To define Alzheimer's disease with biomarkers rather than clinical assessment, we assessed prediction of research-diagnosed disease status using these biomarkers and tested genetic variants associated with the biomarkers that may reflect more accurately the risk of biochemically defined Alzheimer's disease instead of the risk of dementia. In a cohort of Alzheimer's disease cases [n = 1439, mean age 68 years (standard deviation = 8.2)] and screened controls [n = 508, mean age 82 years (standard deviation = 6.8)], we measured plasma concentrations of the 40 and 42 amino acid-long amyloid-ß (Aß) fragments (Aß40 and Aß42, respectively), tau phosphorylated at amino acid 181 (P-tau181), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) using state-of-the-art Single molecule array (Simoa) technology. We tested the relationships between the biomarkers and Alzheimer's disease genetic risk, age at onset and disease duration. We also conducted a genome-wide association study for association of disease risk genes with these biomarkers. The prediction accuracy of Alzheimer's disease clinical diagnosis by the combination of all biomarkers, APOE and polygenic risk score reached area under receiver operating characteristic curve (AUC) = 0.81, with the most significant contributors being ε4, Aß40 or Aß42, GFAP and NfL. All biomarkers were significantly associated with age in cases and controls (P < 4.3 × 10-5). Concentrations of the Aß-related biomarkers in plasma were significantly lower in cases compared with controls, whereas other biomarker levels were significantly higher in cases. In the case-control genome-wide analyses, APOE-ε4 was associated with all biomarkers (P = 0.011-4.78 × 10-8), except NfL. No novel genome-wide significant single nucleotide polymorphisms were found in the case-control design; however, in a case-only analysis, we found two independent genome-wide significant associations between the Aß42/Aß40 ratio and WWOX and COPG2 genes. Disease prediction modelling by the combination of all biomarkers indicates that the variance attributed to P-tau181 is mostly captured by APOE-ε4, whereas Aß40, Aß42, GFAP and NfL biomarkers explain additional variation over and above APOE. We identified novel plausible genome wide-significant genes associated with Aß42/Aß40 ratio in a sample which is 50 times smaller than current genome-wide association studies in Alzheimer's disease.

Characterising heart rhythm abnormalities associated with Xp22.31 deletion.

BACKGROUND: Genetic deletions at Xp22.31 are associated with the skin condition X linked ichthyosis (XLI), and with a substantially increased risk of atrial fibrillation/flutter (AF), in males. AF is associated with elevated thrombosis, heart failure, stroke and dementia risk. METHODS: Through: (a) examining deletion carriers with a diagnosis of AF in UK Biobank, (b) undertaking an online survey regarding abnormal heart rhythms (AHRs) in men/boys with XLI and female carriers of XLI-associated deletions and (c) screening for association between common genetic variants within Xp22.31 and idiopathic AF-related conditions in UK Biobank, we have investigated how AHRs manifest in deletion carriers, and have identified associated risk factors/comorbidities and candidate gene(s). Finally, we examined attitudes towards heart screening in deletion carriers. RESULTS: We show that AHRs may affect up to 35% of deletion carriers (compared with <20% of age-matched non-carriers), show no consistent pattern of onset but may be precipitated by stress, and typically resolve quickly and respond well to intervention. Gastrointestinal (GI) conditions and asthma/anaemia were the most strongly associated comorbidities in male and female deletion carriers with AHR, respectively. Genetic analysis indicated significant enrichment of common AF risk variants around STS (7 065 298-7 272 682 bp in GRCh37/hg19 genome build) in males, and of common GI disorder and asthma/anaemia risk variants around PNPLA4 (7 866 804-7 895 780 bp) in males and females, respectively. Deletion carriers were overwhelmingly in favour of cardiac screening implementation. CONCLUSION: Our data suggest AHRs are frequently associated with Xp22.31 deletion, and highlight subgroups of deletion carriers that may be prioritised for screening. Examining cardiac function further in deletion carriers, and in model systems lacking steroid sulfatase, may clarify AF pathophysiology.

Dementias Platform UK: Bringing genetics into life.

INTRODUCTION: The Dementias Platform UK (DPUK) Data Portal is a data repository bringing together a wide range of cohorts. Neurodegenerative dementias are a group of diseases with highly heterogeneous pathology and an overlapping genetic component that is poorly understood. The DPUK collection of independent cohorts can facilitate research in neurodegeneration by combining their genetic and phenotypic data. METHODS: For genetic data processing, pipelines were generated to perform quality control analysis, genetic imputation, and polygenic risk score (PRS) derivation with six genome-wide association studies of neurodegenerative diseases. Pipelines were applied to five cohorts. DISCUSSION: The data processing pipelines, research-ready imputed genetic data, and PRS scores are now available on the DPUK platform and can be accessed upon request though the DPUK application process. Harmonizing genome-wide data for multiple datasets increases scientific opportunity and allows the wider research community to access and process data at scale and pace.

Germline variation in RASAL2 may predict survival in patients with RAS-activated colorectal cancer.

BACKGROUND: Therapeutic agents that specifically target patients with RAS mutant colorectal cancer (CRC) are needed. We sought potential drug targets by relating genome-wide association study and survival data in patients with advanced CRC profiled for mitogen-activated protein kinase (MAPK) pathway mutations. METHODS: In total, 694 patients from the clinical trials COIN and COIN-B had MAPK-activated CRCs (assigned as KRAS, NRAS, or BRAF mutant). Genome-wide single nucleotide polymorphism (SNP), gene, and gene-set analyses were performed to identify determinants of survival. For rs12028023 in RAS protein activator-like 2 (RASAL2), we studied its effect by MAPK pathway activation status (by comparing to 760 patients without MAPK-activated CRCs), MAPK gene mutation status, surface area of the primary tumor (as a marker of proliferation), and expression on RASAL2. RESULTS: In MAGMA genome-wide analyses, RASAL2 was the most significant gene associated with survival (p = 2.0 × 10-5 ). Patients carrying the minor (A) allele in the lead SNP, rs12028023 in intron 1 of RASAL2, had a median increase in survival of 167 days as compared with patients carrying the major allele. rs12028023 was predictive for survival by MAPK-activation status (pZ-test  = 2.1 × 10-3 ). Furthermore, rs12028023 improved survival in patients with RAS mutant (hazard ratio [HR] = 0.62, 95% confidence intervals [CI] = 0.5-0.8, p = 3.4 × 10-5 ) but not BRAF mutant (p = 0.87) CRCs. The rs12028023 A-allele was associated with reduced surface area of the primary tumor (Beta = -0.037, standard error [SE] = 0.017, p = 3.2 × 10-2 ) and reduced RASAL2 expression in cultured fibroblasts (p = 1.6 × 10-11 ). CONCLUSION: Our data demonstrate a prognostic role for RASAL2 in patients with MAPK-activated CRCs, with potential as a therapeutic target.

Assessing the relationship between monoallelic PRKN mutations and Parkinson's risk.

Biallelic Parkin (PRKN) mutations cause autosomal recessive Parkinson's disease (PD); however, the role of monoallelic PRKN mutations as a risk factor for PD remains unclear. We investigated the role of single heterozygous PRKN mutations in three large independent case-control cohorts totalling 10 858 PD cases and 8328 controls. Overall, after exclusion of biallelic carriers, single PRKN mutations were more common in PD than controls conferring a >1.5-fold increase in the risk of PD [P-value (P) = 0.035], with meta-analysis (19 574 PD cases and 468 488 controls) confirming increased risk [Odds ratio (OR) = 1.65, P = 3.69E-07]. Carriers were shown to have significantly younger ages at the onset compared with non-carriers (NeuroX: 56.4 vs. 61.4 years; exome: 38.5 vs. 43.1 years). Stratifying by mutation type, we provide preliminary evidence for a more pathogenic risk profile for single PRKN copy number variant (CNV) carriers compared with single nucleotide variant carriers. Studies that did not assess biallelic PRKN mutations or consist of predominantly early-onset cases may be biasing these estimates, and removal of these resulted in a loss of association (OR = 1.23, P = 0.614; n = 4). Importantly, when we looked for additional CNVs in 30% of PD cases with apparent monoallellic PRKN mutations, we found that 44% had biallelic mutations, suggesting that previous estimates may be influenced by cryptic biallelic mutation status. While this study supports the association of single PRKN mutations with PD, it highlights confounding effects; therefore, caution is needed when interpreting current risk estimates. Together, we demonstrate that comprehensive assessment of biallelic mutation status is essential when elucidating PD risk associated with monoallelic PRKN mutations.

Pitfalls of predicting age-related traits by polygenic risk scores.

Polygenic risk scores (PRS) are a method increasingly used to capture the combined effect of genome-wide significant variants and those which individually do not show genome-wide significant association but are likely to contribute to the risk of developing diseases. However, their practical use incurs complications and inconsistencies that so far limit their clinical applicability. The aims of the present review are to discuss the PRS for age-related diseases and to highlight pitfalls and limitations of PRS prediction accuracy due to ageing and mortality effects. We argue that the PRS is widely used but the individual's PRS values differ substantially depending on the number of genetic variants included, the discovery GWAS and the method employed to generate them. Moreover, for neurodegenerative disorders, although an individual's genetics do not change with age, the actual score depends on the age of the sample used in the discovery GWAS and is likely to reflect the individual's disease risk at this particular age. Improvement of PRS prediction accuracy for neurodegenerative disorders will come from two sides, both the precision of clinical diagnoses, and a careful attention to the age distribution in the underlying samples and validation of the prediction in longitudinal studies.

Alzheimer's disease-associated complement gene variants influence plasma complement protein levels.

BACKGROUND: Alzheimer's disease (AD) has been associated with immune dysregulation in biomarker and genome-wide association studies (GWAS). GWAS hits include the genes encoding complement regulators clusterin (CLU) and complement receptor 1 (CR1), recognised as key players in AD pathology, and complement proteins have been proposed as biomarkers. MAIN BODY: To address whether changes in plasma complement protein levels in AD relate to AD-associated complement gene variants we first measured relevant plasma complement proteins (clusterin, C1q, C1s, CR1, factor H) in a large cohort comprising early onset AD (EOAD; n = 912), late onset AD (LOAD; n = 492) and control (n = 504) donors. Clusterin and C1q were significantly increased (p < 0.001) and sCR1 and factor H reduced (p < 0.01) in AD plasma versus controls. ROC analyses were performed to assess utility of the measured complement biomarkers, alone or in combination with amyloid beta, in predicting AD. C1q was the most predictive single complement biomarker (AUC 0.655 LOAD, 0.601 EOAD); combining C1q with other complement or neurodegeneration makers through stepAIC-informed models improved predictive values slightly. Effects of GWS SNPs (rs6656401, rs6691117 in CR1; rs11136000, rs9331888 in CLU; rs3919533 in C1S) on protein concentrations were assessed by comparing protein levels in carriers of the minor vs major allele. To identify new associations between SNPs and changes in plasma protein levels, we performed a GWAS combining genotyping data in the cohort with complement protein levels as endophenotype. SNPs in CR1 (rs6656401), C1S (rs3919533) and CFH (rs6664877) reached significance and influenced plasma levels of the corresponding protein, whereas SNPs in CLU did not influence clusterin levels. CONCLUSION: Complement dysregulation is evident in AD and may contribute to pathology. AD-associated SNPs in CR1, C1S and CFH impact plasma levels of the encoded proteins, suggesting a mechanism for impact on disease risk.

Genetic common variants associated with cerebellar volume and their overlap with mental disorders: a study on 33,265 individuals from the UK-Biobank.

Interest in the cerebellum is expanding given evidence of its contributions to cognition and emotion, and dysfunction in various psychopathologies. However, research into its genetic architecture and shared influences with liability for mental disorders is lacking. We conducted a genome-wide association study (GWAS) of total cerebellar volume and underlying cerebellar lobe volumes in 33,265 UK-Biobank participants. Total cerebellar volume was heritable (h2SNP = 50.6%), showing moderate genetic homogeneity across lobes (h2SNP from 35.4% to 57.1%; mean genetic correlation between lobes rg ≈ 0.44). We identified 33 GWAS signals associated with total cerebellar volume, of which 6 are known to alter protein-coding gene structure, while a further five mapped to genomic regions known to alter cerebellar tissue gene expression. Use of summary data-based Mendelian randomisation further prioritised genes whose change in expression appears to mediate the SNP-trait association. In total, we highlight 21 unique genes of greatest interest for follow-up analyses. Using LD-regression, we report significant genetic correlations between total cerebellar volume and brainstem, pallidum and thalamus volumes. While the same approach did not result in significant correlations with psychiatric phenotypes, we report enrichment of schizophrenia, bipolar disorder and autism spectrum disorder associated signals within total cerebellar GWAS results via conditional and conjunctional-FDR analysis. Via these methods and GWAS catalogue, we identify which of our cerebellar genomic regions also associate with psychiatric traits. Our results provide important insights into the common allele architecture of cerebellar volume and its overlap with other brain volumes and psychiatric phenotypes.

Comparison of long-term effects of metformin on longevity between people with type 2 diabetes and matched non-diabetic controls.

BACKGROUND: Metformin, a medication for type 2 diabetes, has been linked to many non-diabetes health benefits including increasing healthy lifespan. Previous work has only examined the benefits of metformin over periods of less than ten years, which may not be long enough to capture the true effect of this medication on longevity. METHODS: We searched medical records for Wales, UK, using the Secure Anonymised Information Linkage dataset for type 2 diabetes patients treated with metformin (N = 129,140) and sulphonylurea (N = 68,563). Non-diabetic controls were matched on sex, age, smoking, and history of cancer and cardiovascular disease. Survival analysis was performed to examine survival time after first treatment, using a range of simulated study periods. FINDINGS: Using the full twenty-year period, we found that type 2 diabetes patients treated with metformin had shorter survival time than matched controls, as did sulphonylurea patients. Metformin patients had better survival than sulphonylurea patients, controlling for age. Within the first three years, metformin therapy showed a benefit over matched controls, but this reversed after five years of treatment. INTERPRETATION: While metformin does appear to confer benefits to longevity in the short term, these initial benefits are outweighed by the effects of type 2 diabetes when patients are observed over a period of up to twenty years. Longer study periods are therefore recommended for studying longevity and healthy lifespan. EVIDENCE BEFORE THIS STUDY: Work examining the non-diabetes outcomes of metformin therapy has suggested that there metformin has a beneficial effect on longevity and healthy lifespan. Both clinical trials and observational studies broadly support this hypothesis, but tend to be limited in the length of time over which they can study patients or participants. ADDED VALUE OF THIS STUDY: By using medical records we are able to study individuals with Type 2 diabetes over a period of two decades. We are also able to account for the effects of cancer, cardiovascular disease, hypertension, deprivation, and smoking on longevity and survival time following treatment. IMPLICATIONS OF ALL THE AVAILABLE EVIDENCE: We confirm that there is an initial benefit to longevity of metformin therapy, but this benefit does not outweigh the negative effect on longevity of diabetes. Therefore, we suggest that longer study periods are required for inference to be made about longevity in future research.

Genetic variation in ST6GAL1 is a determinant of capecitabine and oxaliplatin induced hand-foot syndrome.

Cancer patients treated with capecitabine and oxaliplatin (XELOX) often develop hand-foot syndrome (HFS) or palmar-plantar erythrodysesthesia. Genetic variation in ST6GAL1 is a risk factor for type-2 diabetes (T2D), a disease also associated with HFS. We analysed genome-wide association data for 10 toxicities in advanced colorectal cancer (CRC) patients from the COIN and COIN-B trials. One thousand and fifty-five patients were treated with XELOX ± cetuximab and 745 with folinic acid, fluorouracil and oxaliplatin ± cetuximab. We also analysed rs6783836 in ST6GAL1 with HFS in CRC patients from QUASAR2. Using UK Biobank data, we sought to confirm an association between ST6GAL1 and T2D (17 384 cases, 317 887 controls) and analysed rs6783836 against markers of diabetes, inflammation and psoriasis. We found that 68% of patients from COIN and COIN-B with grade 2-3 HFS responded to treatment as compared to 58% with grade 0-1 HFS (odds ratio [OR] = 1.1, 95% confidence interval [CI] = 1.02-1.2, P = 2.0 × 10-4 ). HFS was also associated with improved overall survival (hazard ratio = 0.92, 95% CI = 0.84-0.99, P = 4.6 × 10-2 ). rs6783836 at ST6GAL1 was associated with HFS in patients treated with XELOX (OR = 3.1, 95% CI = 2.1-4.6, P = 4.3 × 10-8 ) and was borderline significant in patients receiving capecitabine from QUASAR2, but with an opposite allele effect (OR = 0.66, 95% CI = 0.42-1.03, P = .05). ST6GAL1 was associated with T2D (lead SNP rs3887925, OR = 0.94, 95% CI = 0.92-0.96, P = 1.2 × 10-8 ) and the rs6783836-T allele was associated with lowered HbA1c levels (P = 5.9 × 10-3 ) and lymphocyte count (P = 2.7 × 10-3 ), and psoriasis (P = 7.5 × 10-3 ) beyond thresholds for multiple testing. In conclusion, HFS is a biomarker of treatment outcome and rs6783836 in ST6GAL1 is a potential biomarker for HFS with links to T2D and inflammation.

A transcriptome-wide association study implicates specific pre- and post-synaptic abnormalities in schizophrenia.

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.

Machine learning for genetic prediction of psychiatric disorders: a systematic review.

Machine learning methods have been employed to make predictions in psychiatry from genotypes, with the potential to bring improved prediction of outcomes in psychiatric genetics; however, their current performance is unclear. We aim to systematically review machine learning methods for predicting psychiatric disorders from genetics alone and evaluate their discrimination, bias and implementation. Medline, PsycInfo, Web of Science and Scopus were searched for terms relating to genetics, psychiatric disorders and machine learning, including neural networks, random forests, support vector machines and boosting, on 10 September 2019. Following PRISMA guidelines, articles were screened for inclusion independently by two authors, extracted, and assessed for risk of bias. Overall, 63 full texts were assessed from a pool of 652 abstracts. Data were extracted for 77 models of schizophrenia, bipolar, autism or anorexia across 13 studies. Performance of machine learning methods was highly varied (0.48-0.95 AUC) and differed between schizophrenia (0.54-0.95 AUC), bipolar (0.48-0.65 AUC), autism (0.52-0.81 AUC) and anorexia (0.62-0.69 AUC). This is likely due to the high risk of bias identified in the study designs and analysis for reported results. Choices for predictor selection, hyperparameter search and validation methodology, and viewing of the test set during training were common causes of high risk of bias in analysis. Key steps in model development and validation were frequently not performed or unreported. Comparison of discrimination across studies was constrained by heterogeneity of predictors, outcome and measurement, in addition to sample overlap within and across studies. Given widespread high risk of bias and the small number of studies identified, it is important to ensure established analysis methods are adopted. We emphasise best practices in methodology and reporting for improving future studies.

A genetic link between risk for Alzheimer's disease and severe COVID-19 outcomes via the OAS1 gene.

Recently, we reported oligoadenylate synthetase 1 (OAS1) contributed to the risk of Alzheimer's disease, by its enrichment in transcriptional networks expressed by microglia. However, the function of OAS1 within microglia was not known. Using genotyping from 1313 individuals with sporadic Alzheimer's disease and 1234 control individuals, we confirm the OAS1 variant, rs1131454, is associated with increased risk for Alzheimer's disease. The same OAS1 locus has been recently associated with severe coronavirus disease 2019 (COVID-19) outcomes, linking risk for both diseases. The single nucleotide polymorphisms rs1131454(A) and rs4766676(T) are associated with Alzheimer's disease, and rs10735079(A) and rs6489867(T) are associated with severe COVID-19, where the risk alleles are linked with decreased OAS1 expression. Analysing single-cell RNA-sequencing data of myeloid cells from Alzheimer's disease and COVID-19 patients, we identify co-expression networks containing interferon (IFN)-responsive genes, including OAS1, which are significantly upregulated with age and both diseases. In human induced pluripotent stem cell-derived microglia with lowered OAS1 expression, we show exaggerated production of TNF-α with IFN-γ stimulation, indicating OAS1 is required to limit the pro-inflammatory response of myeloid cells. Collectively, our data support a link between genetic risk for Alzheimer's disease and susceptibility to critical illness with COVID-19 centred on OAS1, a finding with potential implications for future treatments of Alzheimer's disease and COVID-19, and development of biomarkers to track disease progression.

Challenges of Adjusting Single-Nucleotide Polymorphism Effect Sizes for Linkage Disequilibrium.

BACKGROUND: Genome-wide association studies (GWAS) were successful in identifying SNPs showing association with disease, but their individual effect sizes are small and require large sample sizes to achieve statistical significance. Methods of post-GWAS analysis, including gene-based, gene-set and polygenic risk scores, combine the SNP effect sizes in an attempt to boost the power of the analyses. To avoid giving undue weight to SNPs in linkage disequilibrium (LD), the LD needs to be taken into account in these analyses. OBJECTIVES: We review methods that attempt to adjust the effect sizes (ß-coefficients) of summary statistics, instead of simple LD pruning. METHODS: We subject LD adjustment approaches to a mathematical analysis, recognising Tikhonov regularisation as a framework for comparison. RESULTS: Observing the similarity of the processes involved with the more straightforward Tikhonov-regularised ordinary least squares estimate for multivariate regression coefficients, we note that current methods based on a Bayesian model for the effect sizes effectively provide an implicit choice of the regularisation parameter, which is convenient, but at the price of reduced transparency and, especially in smaller LD blocks, a risk of incomplete LD correction. CONCLUSIONS: There is no simple answer to the question which method is best, but where interpretability of the LD adjustment is essential, as in research aiming at identifying the genomic aetiology of disorders, our study suggests that a more direct choice of mild regularisation in the correction of effect sizes may be preferable.

Genome-wide association studies of toxicity to oxaliplatin and fluoropyrimidine chemotherapy with or without cetuximab in 1800 patients with advanced colorectal cancer.

Chemotherapies administered at normal therapeutic dosages can cause significant side-effects and may result in early treatment discontinuation. Inter-individual variation in toxicity highlights the need for biomarkers to personalise treatment. We sought to identify such biomarkers by conducting 40 genome-wide association studies, together with gene and gene set analyses, for any toxicity and 10 individual toxicities in 1800 patients with advanced colorectal cancer treated with oxaliplatin and fluoropyrimidine chemotherapy ± cetuximab from the MRC COIN and COIN-B trials (385 patients received FOLFOX, 360 FOLFOX + cetuximab, 707 XELOX and 348 XELOX + cetuximab). Single nucleotide polymorphisms (SNPs), genes and gene sets that reached genome-wide or suggestive significance were validated in independent patient groups. We found that MROH5 was significantly associated with neutropenia in MAGMA gene analyses in patients treated with XELOX (P = 6.6 × 10-7 ) and was independently validated in those receiving XELOX + cetuximab; pooled P = 3.7 × 10-7 . rs13260246 at 8q21.13 was significantly associated with vomiting in patients treated with XELOX (odds ratio = 5.0, 95% confidence interval = 3.0-8.3, P = 9.8 × 10-10 ) but was not independently replicated. SNPs at 139 loci had suggestive associations for toxicities and lead SNPs at five of these were independently validated (rs6030266 with diarrhoea, rs1546161 with hand-foot syndrome, rs9601722 with neutropenia, rs13413764 with lethargy and rs4600090 with nausea; all with pooled P's < 5.0 × 10-6 ). In conclusion, the association of MROH5 with neutropenia and five other putative biomarkers warrant further investigation for their potential clinical utility. Despite our comprehensive genome-wide analyses of large, well-characterised, clinical trials, we found a lack of common variants with modest effect sizes associated with toxicities.

Genes, pathways and risk prediction in Alzheimer's disease.

The failure of recent clinical trials in Alzheimer's disease has highlighted the need for the development of a more complete understanding of the pathogenesis of the disorder and also a belief that therapies may only work if given very early in the disease process before overt symptoms occur. The rare, early onset forms of the disease are all caused by mutations which make amyloid deposition a more likely event. Here we discuss the recent data showing that, in contrast, much of the risk of late onset disease is encoded by loci involved in lipid metabolism and/or encoded by microglia. We discuss these finding and suggest that amyloid induced membrane damage may be a key factor in disease and also review the evidence that genome wide genetic analysis can substantially help in the prediction of those individuals at high risk of disease in the general population.

Effects of genomic copy number variants penetrant for schizophrenia on cortical thickness and surface area in healthy individuals: analysis of the UK Biobank.

BACKGROUND: Schizophrenia is a highly heritable disorder with undetermined neurobiological causes. Understanding the impact on brain anatomy of carrying genetic risk for the disorder will contribute to uncovering its neurobiological underpinnings. AIMS: To examine the effect of rare copy number variants (CNVs) associated with schizophrenia on brain cortical anatomy in a sample of unaffected participants from the UK Biobank. METHOD: We used regression analyses to compare cortical thickness and surface area (total and across gyri) between 120 unaffected carriers of rare CNVs associated with schizophrenia and 16 670 participants without any pathogenic CNV. A measure of cortical thickness and surface area covariance across gyri was also compared between groups. RESULTS: Carrier status was associated with reduced surface area (ß = -0.020 mm2, P < 0.001) and less robustly with increased cortical thickness (ß = 0.015 mm, P = 0.035), and with increased covariance in thickness (carriers z = 0.31 v. non-carriers z = 0.22, P < 0.0005). Associations were mainly present in frontal and parietal areas and driven by a limited number of rare risk alleles included in our analyses (mainly 15q11.2 deletion for surface area and 16p13.11 duplication for thickness covariance). CONCLUSIONS: Results for surface area conformed with previous clinical findings, supporting surface area reductions as an indicator of genetic liability for schizophrenia. Results for cortical thickness, though, argued against its validity as a potential risk marker. Increased structural thickness covariance across gyri also appears related to risk for schizophrenia. The heterogeneity found across the effects of rare risk alleles suggests potential different neurobiological gateways into schizophrenia's phenotype.

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.