POLARIS: polygenic LD-adjusted risk score approach for set-based analysis of GWAS data

Polygenic risk scores (PRSs) are a method to summarise the additive trait variance captured by a set of SNPs, and can increase the power of set-based analyses by leveraging public GWAS datasets. PRS aims to assess the genetic liability to some phenotype on the basis of polygenic risk for the same or di�erent phenotype estimated from independent data. We propose the application of PRSs as a set-based method with an additional component of adjustment for linkage disequilibrium (LD), with potential extension of the PRS approach to analyse biologically meaningful SNP sets. We call this method POLARIS: POlygenic Ld-Adjusted RIsk Score. POLARIS identi�es the LD-structure of SNPs using spectral decomposition of the SNP correlation matrix and replaces the individuals' SNP allele counts with LD-adjusted dosages. Using a raw genotype dataset together with SNP e�ect sizes from a second independent dataset, POLARIS can be used for set-based analysis. MAGMA is an alternative set-based approach employing principal component analysis to account for LD between markers in a raw genotype dataset. We used simulations, both with simple constructed and real LD-structure, to compare the power of these methods. POLARIS shows more power than MAGMA applied to the raw genotype dataset only, but less or comparable power to combined analysis of both datasets. POLARIS has the advantages that it produces a risk score per person per set using all available SNPs, and aims to increase power by leveraging the e�ect sizes from the discovery set in a self-contained test of association in the test dataset

Common Variants in Alzheimer’s Disease and Risk Stratification by Polygenic Risk Scores

Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n=409,435 and validation size n=58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease.The present work has been performed as part of the doctoral program of I. de Rojas at the Universitat de Barcelona (Barcelona, Spain) supported by national grant from the Instituto de Salud Carlos III FI20/00215. The Genome Research @ Fundació ACE project (GR@ACE) is supported by Grifols SA, Fundación bancaria “La Caixa”, Fundació ACE, and CIBERNED. A.R. and M.B. receive support from the European Union/EFPIA Innovative Medicines Initiative Joint undertaking ADAPTED and MOPEAD projects (grant numbers 115975 and 115985, respectively). M.B. and A.R. are also supported by national grants PI13/02434, PI16/01861, PI17/01474, PI19/01240 and PI19/01301. Acción Estratégica en Salud is integrated into the Spanish National R + D + I Plan and funded by ISCIII (Instituto de Salud Carlos III)—Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER—“Una manera de hacer Europa”). The Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting VUmc fonds. The clinical database structure was developed with funding from Stichting Dioraphte. Genotyping of the Dutch case-control samples was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project number 733051061). 100-Plus study. This work was supported by Stichting Alzheimer Nederland (WE09.2014-03), Stichting Diorapthe, horstingstuit foundation, Memorabel (ZonMW project number 733050814, 733050512) and Stichting VUmc Fonds. Genotyping of the 100-Plus Study was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project numb 733051061). Longitudinal Aging Study Amsterdam (LASA) is largely supported by a grant from the Netherlands Ministry of Health, Welfare and Sports, Directorate of LongTerm Care. This work was supported by a grant (European Alzheimer DNA BioBank, EADB) from the EU Joint Program—Neurodegenerative Disease Research (JPND) and also funded by Inserm, Institut Pasteur de Lille, the Lille Métropole Communauté Urbaine, the French government’s LABEX DISTALZ program (development of innovative strategies for a transdisciplinary approach to AD). Genotyping of the German case-control samples was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND (German Federal Ministry of Education and Research, BMBF: 01ED1619A). The i–Select chips was funded by the French National Foundation on AD and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant n° 503480), Alzheimer’s Research UK (Grant n° 503176), the Wellcome Trust (Grant n° 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant n° 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIA/NHLBI grants AG049505, AG058589, HL105756 and AGES contract N01–AG–12100, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer’s Association grant ADGC–10–19672

Gene-Based Analysis in HRC Imputed Genome Wide Association Data Identifies Three Novel Genes For Alzheimer’s Disease

A novel POLARIS gene-based analysis approach was employed to compute gene-based polygenic risk score (PRS) for all individuals in the latest HRC imputed GERAD (N cases=3,332 and N controls=9,832) data using the International Genomics of Alzheimer’s Project summary statistics (N cases=13,676 and N controls=27,322, excluding GERAD subjects) to identify the SNPs and weight their risk alleles for the PRS score. SNPs were assigned to known, protein coding genes using GENCODE (v19). SNPs are assigned using both 1) no window around the gene and 2) a window of 35kb upstream and 10kb downstream to include transcriptional regulatory elements. The overall association of a gene is determined using a logistic regression model, adjusting for population covariates. Three novel gene-wide significant genes were determined from the POLARIS gene-based analysis using a gene window; PPARGC1A, RORA and ZNF423 . The ZNF423 gene resides in an Alzheimer’s disease (AD)-specific protein network which also includes other AD-related genes. The PPARGC1A gene has been linked to energy metabolism and the generation of amyloid beta plaques and the RORA has strong links with genes which are differentially expressed in the hippocampus. We also demonstrate no enrichment for genes in either loss of function intolerant or conserved noncoding sequence regions

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)

Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.Peer reviewe

Genome-wide association for major depression through age at onset stratification

BACKGROUND: Major depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset. METHODS: Discovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer’s disease, and coronary artery disease. RESULTS: We identified one replicated genome-wide significant locus associated with adult-onset (>27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11–1.21, p = 5.2 × 10-11). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD. CONCLUSIONS: We demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder

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

A novel POLARIS gene-based analysis approach was employed to compute gene-based polygenic risk score (PRS) for all individuals in the latest HRC imputed GERAD (N cases=3332 and N controls=9,832) data using the International Genomics of Alzheimer's Project summary statistics (N cases=13676 and N controls= 27322, excluding GERAD subjects) to identify the SNPs and weight their risk alleles for the PRS score. SNPs were assigned to known, protein coding genes using GENCODE (v19). SNPs are assigned using both 1) no window around the gene and 2) a window of 35kb upstream and 10kb downstream to include transcriptional regulatory elements. The overall association of a gene is determined using a logistic regression model, adjusting for population covariates. Three novel gene wide significant genes were determined for the POLARIS gene-based analysis using a gene window; PPARGC1A, RORA and ZNF423. The ZNF432 gene resides in an Alzheimer's disease (AD) specific protein network which also includes other AD-related genes. The PPARGC1A gene has been linked to energy metabolism and the generation of amyloid beta plaques and the RORA has strong links with genes which are differentially expressed in the hippocampus. We also demonstrate no enrichment for genes in either loss of function intolerant or conserved noncoding sequence regions

Genetic variation at the <em>CELF1</em> (CUGBP, elav-like family member 1 gene) locus is genome-wide associated with Alzheimer&#39;s disease and obesity.

Deviations from normal body weight are observed prior to and after the onset of Alzheimer&#39;s disease (AD). Midlife obesity confers increased AD risk in later life, whereas late-life obesity is associated with decreased AD risk. The role of underweight and weight loss for AD risk is controversial. Based on the hypothesis of shared genetic variants for both obesity and AD, we analyzed the variants identified for AD or obesity from genome-wide association meta-analyses of the GERAD (AD, cases = 6,688, controls = 13,685) and GIANT (body mass index [BMI] as measure of obesity, n = 123,865) consortia. Our cross-disorder analysis of genome-wide significant 39 obesity SNPs and 23 AD SNPs in these two large data sets revealed that: (1) The AD SNP rs10838725 (p(AD) = 1.1 x 10(-08)) at the locus CELF1 is also genome-wide significant for obesity (pBMI = 7.35 x 10(-09)). (2) Four additional AD risk SNPs were nominally associated with obesity (rs17125944 at FERMT2, p(BMI) = 4.03 x 10(-05), p(BMI corr) = 2.50 x 10(-03); rs3851179 at PICALM; p(BMI) = 0.002, rs2075650 at TOMM40/APOE, p(BMI) = 0.024, rs3865444 at CD33, p(BMI) = 0.024). (3) SNPs at two of the obesity risk loci (rs4836133 downstream of ZNF608; p(AD) = 0.002 and at rs713586 downstream of RBJ/DNAJC27; p(AD) = 0.018) were nominally associated with AD risk. Additionally, among the SNPs used for confirmation in both studies the AD risk allele of rs1858973, with an AD association just below genome-wide significance (p(AD) = 7.20 x 10(-07)), was also associated with obesity (SNP at IQCK/GPRC5B; p(BMI) = 5.21 x 10(-06); p(corr) = 3.24 x 10(-04)). Our first GWAS based cross-disorder analysis for AD and obesity suggests that rs10838725 at the locus CELF1 might be relevant for both disorders

GWAS of cerebrospinal fluid tau levels identifies risk variants for Alzheimer's disease

Cerebrospinal fluid (CSF) tau, tau phosphorylated at threonine 181 (ptau), and Aβ42 are established biomarkers for Alzheimer’s disease (AD) and have been used as quantitative traits for genetic analyses. We performed the largest genome-wide association study for cerebrospinal fluid (CSF) tau/ptau levels published to date (n = 1,269), identifying three genome-wide significant loci for CSF tau and ptau: rs9877502 (p = 4.89 × 10−9 for tau) located at 3q28 between GEMC1 and OSTN, rs514716 (p = 1.07 × 10−8 and p = 3.22 × 10−9 for tau and ptau, respectively), located at 9p24.2 within GLIS3 and rs6922617 (p = 3.58 × 10−8 for CSF ptau) at 6p21.1 within the TREM gene cluster, a region recently reported to harbor rare variants that increase AD risk. In independent data sets, rs9877502 showed a strong association with risk for AD, tangle pathology, and global cognitive decline (p = 2.67 × 10−4, 0.039, 4.86 × 10−5, respectively) illustrating how this endophenotype-based approach can be used to identify new AD risk loci