Tulsi Patel

Polygenic risk score in postmortem diagnosed sporadic early-onset Alzheimer’s disease

Sporadic early-onset Alzheimers disease (sEOAD) exhibits the symptoms of late-onset Alzheimers disease but lacks the familial aspect of the early-onset familial form. The genetics of Alzheimers disease (AD) identifies APOEε4 to be the greatest risk factor; however, it is a complex disease involving both environmental risk factors and multiple genetic loci. Polygenic risk scores (PRSs) accumulate the total risk of a phenotype in an individual based on variants present in their genome. We determined whether sEOAD cases had a higher PRS compared to controls. A cohort of sEOAD cases was genotyped on the NeuroX array, and PRSs were generated using PRSice. The target data set consisted of 408 sEOAD cases and 436 controls. The base data set was collated by the International Genomics of Alzheimers Project consortium, with association data from 17,008 late-onset Alzheimers disease cases and 37,154 controls, which can be used for identifying sEOAD cases due to having shared phenotype. PRSs were generated using all common single nucleotide polymorphisms between the base and target data set, PRS were also generated using only single nucleotide polymorphisms within a 500 kb region surrounding the APOE gene. Sex and number of APOE ε2 or ε4 alleles were used as variables for logistic regression and combined with PRS. The results show that PRS is higher on average in sEOAD cases than controls, although there is still overlap among the whole cohort. Predictive ability of identifying cases and controls using PRSice was calculated with 72.9% accuracy, greater than the APOE locus alone (65.2%). Predictive ability was further improved with logistic regression, identifying cases and controls with 75.5% accuracy.

Whole-exome sequencing of the BDR cohort: Evidence to support the role of the PILRA gene in Alzheimer's disease

Late‐onset Alzheimers disease (LOAD) accounts for 95% of all Alzheimers cases and is genetically complex in nature. Overlapping clinical and neuropathological features between AD, FTD and Parkinsons disease highlight the potential role of genetic pleiotropy across diseases. Recent genome‐wide association studies (GWASs) have uncovered 20 new loci for AD risk; however, these exhibit small effect sizes. Using NGS, here we perform association analyses using exome‐wide and candidate‐gene‐driven approaches.

Methylation profiling RIN3 and MEF2C identifies epigenetic marks associated with sporadic early onset Alzheimer’s disease

A number of genetic loci associate with early onset Alzheimer’s disease (EOAD); however, the drivers of this disease remains enigmatic. Genome wide association and in vivo modeling have shown that loss-of-function, e.g., ABCA7, reduced levels of SIRT1 and MEFF2C, or increased levels of PTK2β confer risk or link to the pathogenies. It is known that DNA methylation can profoundly affect gene expression and can impact on the composition of the proteome; therefore, the aim of this study is to assess if genes associated with sporadic EOAD (sEOAD) are differentially methylated. Epi-profiles of DNA extracted from blood and cortex were compared using a pyrosequencing platform. We identified significant group-wide hypomethylation in AD blood when compared to controls for 7 CpGs located within the 3’UTR of RIN3 (CpG1 p = 0.019, CpG2 p = 0.018, CpG3 p = 0.012, CpG4 p = 0.009, CpG5 p = 0.002, CpG6 p = 0.018, and CpG7 p = 0.013, respectively; AD/Control n = 22/26; Male/Female n = 27/21). Observed effects were not gender specific. No group wide significant differences were found in the promoter methylation of PTK2β, ABCA7, SIRT1, or MEF2C, genes known to associate with late onset AD. A rare and significant difference in methylation was observed for one CpG located upstream of the MEF2C promoter in one AD individual only (22% reduction in methylation, p = 2.0E-10; Control n = 26, AD n = 25, Male/Female n = 29/22). It is plausible aberrant methylation may mark sEOAD in blood and may manifest in some individuals as rare epi-variants for genes linked to sEOAD.

Genotyping of the Alzheimer’s Disease Genome-Wide Association Study Index Single Nucleotide Polymorphisms in the Brains for Dementia Research Cohort

The Brains for Dementia Research project is a recently established longitudinal cohort which aims to provide brain tissue for research purposes from neuropathologically defined samples. Here we present the findings from our analysis on the 19 established GWAS index SNPs for Alzheimers disease, in order to demonstrate if the BDR sample also displays association to these variants. A highly significant association of the APOEɛ4 allele was identified (p = 3.99×10-12). Association tests for the 19 GWAS SNPs found that although no SNPs survive multiple testing, nominal significant findings were detected and concordance with the Lambert et al. GWAS meta-analysis was observed.

Observations of extensive gene expression differences in the cerebellum and potential relevance to Alzheimer’s disease

ObjectivesIn order to determine how gene expression is altered in disease it is of fundamental importance that the global distribution of gene expression levels across the disease-free brain are understood and how differences between tissue types might inform tissue choice for investigation of altered expression in disease state. The aim of this pilot project was to use RNA-sequencing to investigate gene expression differences between five general areas of post-mortem human brain (frontal, temporal, occipital, parietal and cerebellum), and in particular changes in gene expression in the cerebellum compared to cortex regions for genes relevant to Alzheimer’s disease, as the cerebellum is largely preserved from disease pathology and could be an area of interest for neuroprotective pathways.ResultsGeneral gene expression profiles were found to be similar between cortical regions of the brain, however the cerebellum presented a distinct expression profile. Focused exploration of gene expression for genes associated with Alzheimer’s disease suggest that those involved in the immunity pathway show little expression in the brain. Furthermore some Alzheimer’s disease associated genes display significantly different expression in the cerebellum compared with other brain regions, which might indicate potential neuroprotective measures.

PRELIMINARY ANALYSIS FROM RNA-SEQUENCING DERIVED FROM FIVE BRAIN REGIONS IN BDR SAMPLES

Background:Alzheimer Disease (AD) genomics, including the AD Sequencing Project (ADSP) and the AD Genetics Consortium (ADGC) have focused on non-Hispanic White populations. Puerto Ricans, constituting over 1.5% of the US population and the second largest Hispanic population in the continental US, have an estimated AD prevalence of 65,000. However, there has been limited study of AD genetics in this group. Understanding the genetic causes of AD in multiple ethnic groups will lead to better diagnosis, prevention and treatment. For this abstract we will describe our large cohort of well-phenotyped Hispanics with AD from Puerto Rico, a large number being from multiplex AD families. Methods: Eligible multiplex families have at least two living family members with AD as well as one elderly family member who is cognitively intact (CI). Each individual with AD who was enrolled had a confirmed AD diagnosis by a neurologist and was assess by our research battery consisting of neurological exams and imaging. We will describe our cohort based on current ascertainment numbers stratified by diagnosis, family structure, age at onset (AAO), and APOE status. In addition, we provide preliminary 3MS findings. Results: This cohort consists of 306 individuals (68% female; mean age1⁄4 78 years) from 149 families. We have enrolled 128 individuals with AD, 174 CI individuals, and four individuals with Mild Cognitive Impairment (MCI). Among the 128 individuals with AD, 97% are classified as LOAD; the remaining 3% are EOAD. Forty-one (of 149 families) are multiplex from which 122 individuals were sampled. Within these 122 individuals, 49%meet criteria for LOAD and 51% are CI. Among the multiplex families, the mean number of LOAD cases per family is 2.7; 11 families contained four AD living individuals. The entire cohort was genotyped for APOE; 42% of the sample carries one e4 allele and 6.5% are homozygous. Among the e4/e4 homozygous individuals, 60% were AD cases vs. 40% who were CI. Conclusions:This resource will complement ongoing next-generation sequencing efforts such as the ADSP and ADGC, and will allow identification of novel risk and protective variants specific to Hispanic populations.

Identifying polymorphisms in the Alzheimer's related APP gene using the MinION sequencer

The MinION is a bench top sequencer by Oxford nanopore technologies (ONT) that allows long reads of DNA sequence. Few studies have tested whether polymorphisms can be detected using this device. Several polymorphisms within the APP gene were used to test this capability. Library preparation and sequencing were performed using standard ONT protocols for samples harbouring five different mutations. Alignments to the reference sequence were analysed in MinoTour and basecalls were manually investigated using proportion of reference calls between samples to identify the variants. MinoTour’s algorithm for variant detection was unable to identify the polymorphisms due to high base calling error rate. By calculating the difference in reference basecall proportions along the amplicon, it was possible to identify the polymorphisms above a Bonferroni-corrected threshold (p<1 × 10-4). The MinION has potential for polymorphism detection when comparing samples; however careful interpretation is needed as high base calling error rates can mask the presence of polymorphisms.

Investigating Splicing Variants Uncovered by Next-Generation Sequencing the Alzheimer’s Disease Candidate Genes, CLU, PICALM, CR1, ABCA7, BIN1, the MS4A Locus, CD2AP, EPHA1 and CD33

Late onset Alzheimer’s disease (LOAD), the most common cause of late onset dementia, has a strong genetic component. To date, 21 disease-risk loci have been identified through genome wide association studies (GWAS). However, the causative functional variant(s) within these loci are yet to be discovered. This study aimed to identify potential functional splicing mutations in the nine original GWAS-risk genes: CLU, PICALM, CR1, ABCA7, BIN1, the MS4A locus, CD2AP, EPHA1 and CD33. Target enriched next generation sequencing (NGS) was used to resequence the entire genetic region for each of these GWAS-risk loci in 96 LOAD patients and in silico databases were used to annotate the variants for functionality. Predicted splicing variants were further functionally characterised using splicing prediction software and minigene splicing assays. Following in silico annotation, 21 variants were predicted to influence splicing and, upon further annotation, four of these were examined utilising the in vitro minigene assay. Two variants, rs881768 A>G in ABCA7 and a novel variant 11: 60179827 T>G in MS4A6A were shown, in these cell assays, to affect the splicing of these genes. The method employed in the paper successfully identified potential splicing variants in GWAS-risk genes. Further investigation will be needed to understand the full effect of these variants on LOAD risk. However, these results suggest a possible pipeline in order to identify putative functional variants as a result of NGS in disease-associated loci although improvements are needed within the current prediction programme in order to reduce the number of false positives.

INVESTIGATING SARM1 VARIANTS IN ALZHEIMER’S DISEASE COHORTS

ALZHEIMER’S DISEASE COHORTS Tulsi Patel, Naomi S. Clement, Imelda Barber, Anne Braae, Keeley J. Brookes, Tamar Guetta-Baranes, Sally Chappell, Rita Guerreiro, Jose T. Bras, Andrew Singleton, John Hardy, Kevin Morgan, University of Nottingham, Nottingham, United Kingdom of Great Britain and Northern Ireland; 2 UCL Institute of Neurology, London, United Kingdom; UCL Institute of Neurology, London, United Kingdom; National Institute of Aging, Bethesda, MD, USA; University of Nottingham, Nottingham, United Kingdom. Contact e-mail: mbxtp1@ nottingham.ac.uk