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.

Downregulation of Dickkopf-3, a Wnt antagonist elevated in Alzheimer's disease, restores synapse integrity and memory in a disease mouse model

Increasing evidence supports a role for deficient Wnt signaling in Alzheimer's disease (AD). Studies reveal that the secreted Wnt antagonist Dickkopf-3 (DKK3) colocalizes to amyloid plaques in AD patients. Here, we investigate the contribution of DKK3 to synapse integrity in healthy and AD brains. Our findings show that DKK3 expression is upregulated in the brains of AD subjects and that DKK3 protein levels increase at early stages in the disease. In hAPP-J20 and hAPPNL-G-F/NL-G-F mouse AD models, extracellular DKK3 levels are increased and DKK3 accumulates at dystrophic neuronal processes around plaques. Functionally, DKK3 triggers the loss of excitatory synapses through blockade of the Wnt/GSK3β signaling with a concomitant increase in inhibitory synapses via activation of the Wnt/JNK pathway. In contrast, DKK3 knockdown restores synapse number and memory in hAPP-J20 mice. Collectively, our findings identify DKK3 as a novel driver of synaptic defects and memory impairment in AD.

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.

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.

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-β (Aβ) fragments (Aβ40 and Aβ42, 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, Aβ40 or Aβ42, GFAP and NfL. All biomarkers were significantly associated with age in cases and controls (P < 4.3 × 10-5). Concentrations of the Aβ-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 Aβ42/Aβ40 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 Aβ40, Aβ42, GFAP and NfL biomarkers explain additional variation over and above APOE. We identified novel plausible genome wide-significant genes associated with Aβ42/Aβ40 ratio in a sample which is 50 times smaller than current genome-wide association studies in Alzheimer's disease.

What does heritability of Alzheimer's disease represent?

INTRODUCTION

Both late-onset Alzheimer's disease (AD) and ageing have a strong genetic component. In each case, many associated variants have been discovered, but how much missing heritability remains to be discovered is debated. Variability in the estimation of SNP-based heritability could explain the differences in reported heritability.

METHODS

We compute heritability in five large independent cohorts (N = 7,396, 1,566, 803, 12,528 and 3,963) to determine whether a consensus for the AD heritability estimate can be reached. These cohorts vary by sample size, age of cases and controls and phenotype definition. We compute heritability a) for all SNPs, b) excluding APOE region, c) excluding both APOE and genome-wide association study hit regions, and d) SNPs overlapping a microglia gene-set.

RESULTS

SNP-based heritability of late onset Alzheimer's disease is between 38 and 66% when age and genetic disease architecture are correctly accounted for. The heritability estimates decrease by 12% [SD = 8%] on average when the APOE region is excluded and an additional 1% [SD = 3%] when genome-wide significant regions were removed. A microglia gene-set explains 69-84% of our estimates of SNP-based heritability using only 3% of total SNPs in all cohorts.

CONCLUSION

The heritability of neurodegenerative disorders cannot be represented as a single number, because it is dependent on the ages of cases and controls. Genome-wide association studies pick up a large proportion of total AD heritability when age and genetic architecture are correctly accounted for. Around 13% of SNP-based heritability can be explained by known genetic loci and the remaining heritability likely resides around microglial related genes.

Whole genome analysis in APOE4 homozygotes identifies the DAB1-RELN pathway in Alzheimer's disease pathogenesis

The APOE-ε4 allele is known to predispose to amyloid deposition and consequently is strongly associated with Alzheimer's disease (AD) risk. There is debate as to whether the APOE gene accounts for all genetic variation of the APOE locus. Another question which remains is whether APOE-ε4 carriers have other genetic factors influencing the progression of amyloid positive individuals to AD. We conducted a genome-wide association study in a sample of 5,390 APOE-ε4 homozygous (ε4ε4) individuals (288 cases and 5102 controls) aged 65 or over in the UK Biobank. We found no significant associations of SNPs in the APOE locus with AD in the sample of ε4ε4 individuals. However, we identified a novel genome-wide significant locus associated to AD, mapping to DAB1 (rs112437613, OR = 2.28, CI = 1.73-3.01, p = 5.4 × 10^-9). This identification of DAB1 led us to investigate other components of the DAB1-RELN pathway for association. Analysis of the DAB1-RELN pathway indicated that the pathway itself was associated with AD, therefore suggesting an epistatic interaction between the APOE locus and the DAB1-RELN pathway.

Life course, genetic, and neuropathological associations with brain age in the 1946 British Birth Cohort: a population-based study

BACKGROUND

A neuroimaging-based biomarker termed the brain age is thought to reflect variability in the brain's ageing process and predict longevity. Using Insight 46, a unique narrow-age birth cohort, we aimed to examine potential drivers and correlates of brain age.

METHODS

Participants, born in a single week in 1946 in mainland Britain, have had 24 prospective waves of data collection to date, including MRI and amyloid PET imaging at approximately 70 years old. Using MRI data from a previously defined selection of this cohort, we derived brain-predicted age from an established machine-learning model (trained on 2001 healthy adults aged 18-90 years); subtracting this from chronological age (at time of assessment) gave the brain-predicted age difference (brain-PAD). We tested associations with data from early life, midlife, and late life, as well as rates of MRI-derived brain atrophy.

FINDINGS

Between May 28, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. We included 456 participants (225 female), with a mean chronological age of 70·7 years (SD 0·7; range 69·2 to 71·9). The mean brain-predicted age was 67·9 years (8·2, 46·3 to 94·3). Female sex was associated with a 5·4-year (95% CI 4·1 to 6·8) younger brain-PAD than male sex. An increase in brain-PAD was associated with increased cardiovascular risk at age 36 years (β=2·3 [95% CI 1·5 to 3·0]) and 69 years (β=2·6 [1·9 to 3·3]); increased cerebrovascular disease burden (1·9 [1·3 to 2·6]); lower cognitive performance (-1·3 [-2·4 to -0·2]); and increased serum neurofilament light concentration (1·2 [0·6 to 1·9]). Higher brain-PAD was associated with future hippocampal atrophy over the subsequent 2 years (0·003 mL/year [0·000 to 0·006] per 5-year increment in brain-PAD). Early-life factors did not relate to brain-PAD. Combining 12 metrics in a hierarchical partitioning model explained 33% of the variance in brain-PAD.

INTERPRETATION

Brain-PAD was associated with cardiovascular risk, and imaging and biochemical markers of neurodegeneration. These findings support brain-PAD as an integrative summary metric of brain health, reflecting multiple contributions to pathological brain ageing, and which might have prognostic utility.

FUNDING

Alzheimer's Research UK, Medical Research Council Dementia Platforms UK, Selfridges Group Foundation, Wolfson Foundation, Wellcome Trust, Brain Research UK, Alzheimer's Association.

Post-partum psychosis and its association with bipolar disorder in the UK: a case-control study using polygenic risk scores

BACKGROUND

For more than 150 years, controversy over the status of post-partum psychosis has hindered research and caused considerable confusion for clinicians and women, with potentially negative consequences. We aimed to explore the hypothesis that genetic vulnerability differs between women with first-onset post-partum psychosis and those with bipolar disorder more generally.

METHODS

In this case-control study on first-onset post-partum psychosis and bipolar disorder in the UK, we included 203 women with first-onset post-partum psychosis (defined as a manic, mixed, or psychotic depression episode within 6 weeks of delivery without a psychiatric history) and 1225 parous women with a history of bipolar disorder. Information on women with bipolar disorder was obtained from the Bipolar Disorder Research Network database, and participants were recruited through screening community mental health teams across the UK and via the media and patient support organisations. All were assessed using a semistructured face-to-face psychiatric interview and psychiatric case note review. 2809 women from the general population were recruited via the national UK Blood Services and the 1958 Birth Cohort (UK National Child Development Study) as controls and matched to cases according to genetic ancestry. All self-reported their ethnicity as White and were recruited from across the UK. Polygenic risk scores (PRSs) were generated from discovery genome-wide association studies of schizophrenia, bipolar disorder, and major depression. Logistic regression was used to model the effect of each PRS on diagnosis, and the RRs and ORs presented were adjusted for ten principal components of genetic variation to account for population stratification.

FINDINGS

203 women with first-onset post-partum psychosis (median age at interview: 46 years [IQR 37-55]) and 1225 women with bipolar disorder (49 years [41-58]) were recruited between September, 1991, and May, 2013, as well as 2809 controls. Women with first-onset post-partum psychosis had similar bipolar disorder and schizophrenia PRSs to women with bipolar disorder, which were significantly higher than those of controls. When compared with controls, women with first-onset post-partum psychosis had an adjusted relative risk ratio (RR) for bipolar disorder PRSs of 1·71 (95% CI 1·56-1·86, p<0·0001) and for schizophrenia PRSs of 1·82 (1·66-1·97, p<0·0001). The effect sizes were similar when comparing women with bipolar disorder to controls (adjusted RR 1·77 [1·69-1·84], p<0·0001 for bipolar disorder PRSs; 2·00 (1·92-2·08), p<0·0001 for schizophrenia PRSs). Although women with bipolar disorder also had higher major depression PRSs than did controls (1·24 [1·17-1·31], p<0·0001), women with first-onset post-partum psychosis did not differ from controls in their polygenic liability to major depression (0·97 (0·82-1·11), p=0·63).

INTERPRETATION

Our study supports the recognition of first-onset post-partum psychosis as a separate nosological entity within the bipolar disorder spectrum both in research and clinical settings.

FUNDING

Wellcome Trust and Medical Research Council.

Identifying individuals with high risk of Alzheimer's disease using polygenic risk scores

Polygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals' scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals' scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

Defining functional variants associated with Alzheimer's disease in the induced immune response

Defining the mechanisms involved in the aetiology of Alzheimer’s disease from genome-wide association studies alone is challenging since Alzheimer’s disease is polygenic and most genetic variants are non-coding. Non-coding Alzheimer’s disease risk variants can influence gene expression by affecting miRNA binding and those located within enhancers and within CTCF sites may influence gene expression through alterations in chromatin states. In addition, their function can be cell-type specific. They can function specifically in microglial enhancers thus affecting gene expression in the brain. Hence, transcriptome-wide association studies have been applied to test the genetic association between disease risk and cell-/tissue-specific gene expression. Many Alzheimer’s disease-associated loci are involved in the pathways of the innate immune system. Both microglia, the primary immune cells of the brain, and monocytes which can infiltrate the brain and differentiate into activated macrophages, have roles in neuroinflammation and β‐amyloid clearance through phagocytosis. In monocytes the function of regulatory variants can be context-specific after immune stimulation. To dissect the variants associated with Alzheimer’s disease in the context of monocytes, we utilized data from naïve monocytes and following immune stimulation in vitro, in combination with genome-wide association studies of Alzheimer’s disease in transcriptome-wide association studies. Of the nine genes with statistically independent transcriptome-wide association signals, seven are located in known Alzheimer’s disease risk loci: BIN1, PTK2B, SPI1, MS4A4A, MS4A6E, APOE and PVR. The transcriptome-wide association signal for MS4A6E, PTK2B and PVR and the direction of effect replicated in an independent genome-wide association studies. Our analysis identified two novel candidate genes for Alzheimer’s disease risk, LACTB2 and PLIN2/ADRP. LACTB2 replicated in a transcriptome-wide association study using independent expression weights. LACTB2 and PLIN2/ADRP are involved in mitochondrial function and lipid metabolism, respectively. Comparison of transcriptome-wide association study results from monocytes, whole blood and brain showed that the signal for PTK2B is specific to blood and MS4A6E is specific to LPS stimulated monocytes.

Cognitive Decline in Alzheimer's Disease Is Not Associated with APOE

BACKGROUND

The rate of cognitive decline in Alzheimer's disease (AD) has been found to vary widely between individuals, with numerous factors driving this heterogeneity.

OBJECTIVE

This study aimed to compute a measure of cognitive decline in patients with AD based on clinical information and to utilize this measure to explore the genetic architecture of cognitive decline in AD.

METHODS

An in-house cohort of 616 individuals, hereby termed the Cardiff Genetic Resource for AD, as well as a subset of 577 individuals from the publicly available ADNI dataset, that have been assessed at multiple timepoints, were used in this study. Measures of cognitive decline were computed using various mixed effect linear models of Mini-Mental State Examination (MMSE). After an optimal model was selected, a metric of cognitive decline for each individual was estimated as the random slope derived from this model. This metric was subsequently used for testing the association of cognitive decline with apolipoprotein E (APOE) genotype.

RESULTS

No association was found between the number of APOEɛ2 or ɛ4 alleles and the rate of cognitive decline in either of the datasets examined.

CONCLUSION

Further exploration is required to uncover possible genetic variants that affect the rate of decline in patients with AD.

Age-dependent effect of APOE and polygenic component on Alzheimer's disease

Alzheimer's disease (AD) is a devastating neurodegenerative condition with significant genetic heritability. Several genes have been implicated in the onset of AD with the apolipoprotein E (APOE) gene being the strongest single genetic risk loci. Evidence suggests that the effect of APOE alters with age during disease progression. Here, we aim to investigate the impact of APOE and other variants outside the APOE region on AD risk in younger and older participants. Using data from both the Alzheimer's Disease Neuroimaging Initiative and the UK Biobank, we computed the polygenic risk score of each individual informed by the latest genetic study from the International Genomics of Alzheimer's Project. Our analysis showed that the effect of APOE on the disease risk is greater in younger participants and reduces as participants' age increases. Our findings indicate the increased impact of polygenic risk score as participants' age increases. Therefore, AD in older individuals can potentially be triggered by the cumulative effect of genes which are outside the APOE region.

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Polygenic risk score analysis was used in ADNI and the UK Biobank data sets.

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APOE's effect on Alzheimer's disease risk was greater in the younger group (age<80 years).

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Genes outside APOE region could trigger Alzheimer's disease in older ages (age≥80 years).

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No considerable reduction of APOE ε4 alleles in ages less than and more than 80 years old.

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Age-specific genetic scores could aid in clinical trials and personalized medicine.

Comparison of Genetic Liability for Sleep Traits Among Individuals With Bipolar Disorder I or II and Control Participants

IMPORTANCE

Insomnia, hypersomnia, and an evening chronotype are common in individuals with bipolar disorder (BD), but whether this reflects shared genetic liability is unclear. Stratifying by BD subtypes could elucidate this association and inform sleep and BD research.

OBJECTIVE

To assess whether polygenic risk scores (PRSs) for sleep traits are associated with BD subtypes I and II.

DESIGN, SETTING, AND PARTICIPANTS

This case-control study was conducted in the United Kingdom and Sweden with participants with BD and control participants. Multinomial regression was used to assess whether PRSs for insomnia, daytime sleepiness, sleep duration, and chronotype are associated with BD subtypes compared with control participants. Affected individuals were recruited from the Bipolar Disorder Research Network. Control participants were recruited from the 1958 British Birth Cohort and the UK Blood Service. Analyses were repeated in an independent Swedish sample from August 2018 to July 2019. All participants were of European ancestry.

EXPOSURES

Standardized PRSs derived using alleles from genome-wide association studies of insomnia, sleep duration, daytime sleepiness, and chronotype. These were adjusted for the first 10 population principal components, genotyping platforms, and sex.

MAIN OUTCOMES AND MEASURES

Association of PRSs with BD subtypes, determined by semistructured psychiatric interview and case notes.

RESULTS

The main analysis included 4672 participants with BD (3132 female participants [67.0%]; 3404 with BD-I [72.9%]) and 5714 control participants (2812 female participants [49.2%]). Insomnia PRS was associated with increased risk of BD-II (relative risk [RR], 1.14 [95% CI, 1.07-1.21]; P = 8.26 × 10-5) but not BD-I (RR, 0.98 [95% CI, 0.94-1.03]; P = .409) relative to control participants. Sleep-duration PRS was associated with BD-I (RR, 1.10 [95% CI, 1.06-1.15]; P = 1.13 × 10-5) but not BD-II (RR, 0.99 [95% CI, 0.93-1.06]; P = .818). Associations between (1) insomnia PRS and BD-II and (2) sleep-duration PRS and BD-I were replicated in the Swedish sample of 4366 individuals with BD (2697 female participants [61.8%]; 2627 with BD-I [60.2%]) and 6091 control participants (3767 female participants [61.8%]). Chronotype and daytime-sleepiness PRS were not associated with BD subtypes.

CONCLUSIONS AND RELEVANCE

Per this analysis, BD subtypes differ in genetic liability to insomnia and hypersomnia, providing further evidence that the distinction between BD-I and BD-II has genetic validity. This distinction will be crucial in selecting participants for future research on the role of sleep disturbance in BD.

Gene-based analysis in HRC imputed genome wide association data identifies three novel genes for Alzheimer's disease

Late onset Alzheimer's disease is the most common form of dementia for which about 30 susceptibility loci have been reported. The aim of the current study is to identify novel genes associated with Alzheimer's disease using the largest up-to-date reference single nucleotide polymorphism (SNP) panel, the most accurate imputation software and a novel gene-based analysis approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 million genotypes from 17,008 Alzheimer's cases and 37,154 controls. In addition to earlier reported genes, we detected three novel gene-wide significant loci PPARGC1A (p = 2.2 × 10-6), RORA (p = 7.4 × 10-7) and ZNF423 (p = 2.1 × 10-6). PPARGC1A and RORA are involved in circadian rhythm; circadian disturbances are one of the earliest symptoms of Alzheimer's disease. PPARGC1A is additionally linked to energy metabolism and the generation of amyloid beta plaques. RORA is involved in a variety of functions apart from circadian rhythm, such as cholesterol metabolism and inflammation. The ZNF423 gene resides in an Alzheimer's disease-specific protein network and is likely involved with centrosomes and DNA damage repair.

Genetic risk for alzheimer disease is distinct from genetic risk for amyloid deposition

Objective

Alzheimer disease (AD) is the most common form of dementia and is responsible for a huge and growing health care burden in the developed and developing world. The polygenic risk score (PRS) approach has shown 75 to 84% prediction accuracy of identifying individuals with AD risk.

Methods

In this study, we tested the prediction accuracy of AD, mild cognitive impairment (MCI), and amyloid deposition risks with PRS, including and excluding APOE genotypes in a large publicly available dataset with extensive phenotypic data, the Alzheimer's Disease Neuroimaging Initiative cohort. Among MCI individuals with amyloid‐positive status, we examined PRS prediction accuracy in those who converted to AD. In addition, we divided polygenic risk score by biological pathways and tested them independently for distinguishing between AD, MCI, and amyloid deposition.

Results

We found that AD and MCI are predicted by both APOE genotype and PRS (area under the curve [AUC] = 0.82% and 68%, respectively). Amyloid deposition is predicted by APOE only (AUC = 79%). Further progression to AD of individuals with MCI and amyloid‐positive status is predicted by PRS over and above APOE (AUC = 67%). In pathway‐specific PRS analyses, the protein–lipid complex has the strongest association with AD and amyloid deposition even when genes in the APOE region were removed (p = 0.0055 and p = 0.0079, respectively).

Interpretation

The results showed different pattern of APOE contribution in PRS risk predictions of AD/MCI and amyloid deposition. Our study suggests that APOE mostly contributes to amyloid accumulation and the PRS affects risk of further conversion to AD. ANN NEUROL 2019;86:427–435

Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

Polygenic risk and hazard scores for Alzheimer's disease prediction

Objective

Genome-wide association studies (GWAS) have identified over 30 susceptibility loci associated with Alzheimer's disease (AD). Using AD GWAS data from the International Genomics of Alzheimer's Project (IGAP), Polygenic Risk Score (PRS) was successfully applied to predict life time risk of AD development. A recently introduced Polygenic Hazard Score (PHS) is able to quantify individuals with age-specific genetic risk for AD. The aim of this study was to quantify the age-specific genetic risk for AD with PRS and compare the results generated by PRS with those from PHS.

Methods

Quantification of individual differences in age-specific genetic risk for AD identified by the PRS, was performed with Cox Regression on 9903 (2626 cases and 7277 controls) individuals from the Genetic and Environmental Risk in Alzheimer's Disease consortium (GERAD). Polygenic Hazard Scores were generated for the same individuals. The age-specific genetic risk for AD identified by the PRS was compared with that generated by the PHS. This was repeated using varying SNPs P-value thresholds for disease association.

Results

Polygenic Risk Score significantly predicted the risk associated with age at AD onset when SNPs were preselected for association to AD at P ≤ 0.001. The strongest effect (B = 0.28, SE = 0.04, P = 2.5 × 10-12) was observed for PRS based upon genome-wide significant SNPs (P ≤ 5 × 10-8). The strength of association was weaker with less stringent SNP selection thresholds.

Interpretation

Both PRS and PHS can be used to predict an age-specific risk for developing AD. The PHS approach uses SNP effect sizes derived with the Cox Proportional Hazard Regression model. When SNPs were selected based upon AD GWAS case/control P ≤ 10-3, we found no advantage of using SNP effects sizes calculated with the Cox Proportional Hazard Regression model in our study. When SNPs are selected for association with AD risk at P > 10-3, the age-specific risk prediction results are not significant for either PRS or PHS. However PHS could be more advantageous than PRS of age specific AD risk predictions when SNPs are prioritized for association with AD age at onset (i.e., powerful Cox Regression GWAS study).

A data-driven investigation of relationships between bipolar psychotic symptoms and schizophrenia genome-wide significant genetic loci

The etiologies of bipolar disorder (BD) and schizophrenia include a large number of common risk alleles, many of which are shared across the disorders. BD is clinically heterogeneous and it has been postulated that the pattern of symptoms is in part determined by the particular risk alleles carried, and in particular, that risk alleles also confer liability to schizophrenia influence psychotic symptoms in those with BD. To investigate links between psychotic symptoms in BD and schizophrenia risk alleles we employed a data-driven approach in a genotyped and deeply phenotyped sample of subjects with BD. We used sparse canonical correlation analysis (sCCA) (Witten, Tibshirani, & Hastie, ) to analyze 30 psychotic symptoms, assessed with the OPerational CRITeria checklist, and 82 independent genome-wide significant single nucleotide polymorphisms (SNPs) identified by the Schizophrenia Working group of the Psychiatric Genomics Consortium for which we had data in our BD sample (3,903 subjects). As a secondary analysis, we applied sCCA to larger groups of SNPs, and also to groups of symptoms defined according to a published factor analyses of schizophrenia. sCCA analysis based on individual psychotic symptoms revealed a significant association (p = .033), with the largest weights attributed to a variant on chromosome 3 (rs11411529), chr3:180594593, build 37) and delusions of influence, bizarre behavior and grandiose delusions. sCCA analysis using the same set of SNPs supported association with the same SNP and the group of symptoms defined "factor 3" (p = .012). A significant association was also observed to the "factor 3" phenotype group when we included a greater number of SNPs that were less stringently associated with schizophrenia; although other SNPs contributed to the significant multivariate association result, the greatest weight remained assigned to rs11411529. Our results suggest that the canonical correlation is a useful tool to explore phenotype-genotype relationships. To the best of our knowledge, this is the first study to apply this approach to complex, polygenic psychiatric traits. The sparse canonical correlation approach offers the potential to include a larger number of fine-grained systematic descriptors, and to include genetic markers associated with other disorders that are genetically correlated with BD.

Association Between Schizophrenia-Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder

Importance

Bipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes and mechanisms.

Objective

To investigate the association between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRSs), and psychotic presentations of BD.

Design, Setting, and Participants

This case-control study in the United Kingdom used multinomial logistic regression to estimate differential PRS associations across categories of cases and controls. Participants included in the final analyses were 4436 cases of BD from the Bipolar Disorder Research Network. These cases were compared with the genotypic data for 4976 cases of schizophrenia and 9012 controls from the Type 1 Diabetes Genetics Consortium study and the Generation Scotland study. Data were collected between January 1, 2000, and December 31, 2013. Data analysis was conducted from March 1, 2016, to February 28, 2017.

Exposures

Standardized PRSs, calculated using alleles with an association threshold of P < .05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, were adjusted for the first 10 population principal components and genotyping platforms.

Main Outcomes and Measures

Multinomial logit models estimated PRS associations with BD stratified by Research Diagnostic Criteria subtypes of BD, by lifetime occurrence of psychosis, and by lifetime mood-incongruent psychotic features. Ordinal logistic regression examined PRS associations across levels of mood incongruence. Ratings were derived from the Schedules for Clinical Assessment in Neuropsychiatry interview and the Bipolar Affective Disorder Dimension Scale.

Results

Of the 4436 cases of BD, 2966 (67%) were female patients, and the mean (SD) age at interview was 46 [12] years. Across clinical phenotypes, there was an exposure-response gradient, with the strongest PRS association for schizophrenia (risk ratio [RR] = 1.94; 95% CI, 1.86-2.01), followed by schizoaffective BD (RR = 1.37; 95% CI, 1.22-1.54), bipolar I disorder subtype (RR = 1.30; 95% CI, 1.24-1.36), and bipolar II disorder subtype (RR = 1.04; 95% CI, 0.97-1.11). Within BD cases, there was an effect gradient, indexed by the nature of psychosis. Prominent mood-incongruent psychotic features had the strongest association (RR = 1.46; 95% CI, 1.36-1.57), followed by mood-congruent psychosis (RR = 1.24; 95% CI, 1.17-1.33) and BD with no history of psychosis (RR = 1.09; 95% CI, 1.04-1.15).

Conclusions and Relevance

For the first time to date, a study shows a polygenic-risk gradient across schizophrenia and BD, indexed by the occurrence and level of mood-incongruent psychotic symptoms.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia

This corrects the article DOI: 10.1038/mp.2016.97.

Mutation intolerant genes and targets of FMRP are enriched for nonsynonymous alleles in schizophrenia

Risk of schizophrenia is conferred by alleles occurring across the full spectrum of frequencies from common SNPs of weak effect through to ultra rare alleles, some of which may be moderately to highly penetrant. Previous studies have suggested that some of the risk of schizophrenia is attributable to uncommon alleles represented on Illumina exome arrays. Here, we present the largest study of exomic variation in schizophrenia to date, using samples from the United Kingdom and Sweden (10,011 schizophrenia cases and 13,791 controls). Single variants, genes, and gene sets were analyzed for association with schizophrenia. No single variant or gene reached genome-wide significance. Among candidate gene sets, we found significant enrichment for rare alleles (minor allele frequency [MAF] < 0.001) in genes intolerant of loss-of-function (LoF) variation and in genes whose messenger RNAs bind to fragile X mental retardation protein (FMRP). We further delineate the genetic architecture of schizophrenia by excluding a role for uncommon exomic variants (0.01 ≤ MAF ≥ 0.001) that confer a relatively large effect (odds ratio [OR] > 4). We also show risk alleles within this frequency range exist, but confer smaller effects and should be identified by larger studies.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia

This corrects the article DOI: 10.1038/mp.2016.97.

Exome arrays capture polygenic rare variant contributions to schizophrenia

Schizophrenia is a highly heritable disorder. Genome-wide association studies based largely on common alleles have identified over 100 schizophrenia risk loci, but it is also evident from studies of copy number variants (CNVs) and from exome-sequencing studies that rare alleles are also involved. Full characterization of the contribution of rare alleles to the disorder awaits the deployment of sequencing technology in very large sample sizes, meanwhile, as an interim measure, exome arrays allow rare non-synonymous variants to be sampled at a fraction of the cost. In an analysis of exome array data from 13 688 individuals (5585 cases and 8103 controls) from the UK, we found that rare (minor allele frequency < 0.1%) variant association signal was enriched among genes that map to autosomal loci that are genome-wide significant (GWS) in common variant studies of schizophrenia genome-wide association study (P_GWAS = 0.01) as well as gene sets known to be enriched for rare variants in sequencing studies (P_RARE = 0.026). We also identified the gene-wise equivalent of GWS support for WDR88 (WD repeat-containing protein 88), a gene of unknown function (P = 6.5 × 10⁻⁷). Rare alleles represented on exome chip arrays contribute to the genetic architecture of schizophrenia, but as is the case for GWAS, very large studies are required to reveal additional susceptibility alleles for the disorder.

Genome-wide burden of deleterious coding variants increased in schizophrenia

Schizophrenia is a common complex disorder with polygenic inheritance. Here we show that by using an approach that compares the individual loads of rare variants in 1,042 schizophrenia cases and 961 controls, schizophrenia cases carry an increased burden of deleterious mutations. At a genome-wide level, our results implicate non-synonymous, splice site as well as stop-altering single-nucleotide variations occurring at minor allele frequency of ≥ 0.01% in the population. In an independent replication sample of 5,585 schizophrenia cases and 8,103 controls of European ancestry we confirm an enrichment in cases of the alleles identified in our study. In addition, the genes implicated by the increased burden of rare coding variants highlight the involvement of neurodevelopment in the aetiology of schizophrenia.