Jan Verheijen

A 22-single nucleotide polymorphism Alzheimer's disease risk score correlates with family history, onset age, and cerebrospinal fluid Aβ42

The ability to identify individuals at increased genetic risk for Alzheimers disease (AD) may streamline biomarker and drug trials and aid clinical and personal decision making.

Understanding Alzheimer Disease at the Interface between Genetics and Transcriptomics

Over 25 genes are known to affect the risk of developing Alzheimer disease (AD), the most common neurodegenerative dementia. However, mechanistic insights and improved disease management remains limited, due to difficulties in determining the functional consequences of genetic associations. Transcriptomics is increasingly being used to corroborate or enhance interpretation of genetic discoveries. These approaches, which include second and third generation sequencing, single-cell sequencing, and bioinformatics, reveal allele-specific events connecting AD risk genes to expression profiles, and provide converging evidence of pathophysiological pathways underlying AD. Simultaneously, they highlight brain region- and cell-type-specific expression patterns, and alternative splicing events that affect the straightforward relation between a genetic variant and AD, re-emphasizing the need for an integrated approach of genetics and transcriptomics in understanding AD.

Common and rare TBK1 variants in early-onset Alzheimer disease in a European cohort

TANK-binding kinase 1 (TBK1) loss-of-function (LoF) mutations are known to cause frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), often combined with memory deficits early in the disease course. We performed targeted resequencing of TBK1 in 1253 early onset Alzheimers disease (EOAD) patients from 8 European countries to investigate whether pathogenic TBK1 mutations are enriched among patients with clinical diagnosis of EOAD. Variant frequencies were compared against 2117 origin-matched controls. We identified only 1 LoF mutation (p.Thr79del) in a patient clinically diagnosed with Alzheimers disease and a positive family history of ALS. We did not observe enrichment of rare variants in EOAD patients compared to controls, nor of rare variants affecting NFκB induction. Of 3 common coding variants, rs7486100 showed evidence of association (OR 1.46 [95% CI 1.13-1.9]; p-value 0.01). Homozygous carriers of the risk allele showed reduced expression of TBK1 (p-value 0.03). Our findings are not indicative of a significant role for TBK1 mutations in EOAD. The association between common variants in TBK1, disease risk and reduced TBK1 expression warrants follow-up in FTD/ALS cohorts.

DELETERIOUS ABCA7 MUTATIONS CONTRIBUTE TO EARLY-ONSET ALZHEIMER’S DISEASE AND ARE SUBJECT TO TRANSCRIPT RESCUE MECHANISMS

Background:Genes that are expressed in a cell-specific fashion in the human brain were identified from transcriptome-wide (RNAseq) expression measures of purified cell populations (Zhang Y. et al, Neuron, 2016). Leveraging these findings, we estimated the relative proportions of cell-types in a temporal cortex (TCX), tissue-based, transcriptome dataset (RNAseq: Allen M. et al, Sci Data, 2016) of 268 subjects with a pathological diagnosis of Alzheimer’s disease (AD; N1⁄480), progressive supranuclear palsy (PSP; N1⁄482), pathologic aging (PA; N1⁄430) or normal controls (CON; N1⁄476), to identify disease relevant changes and cell-specific vulnerabilities. Methods:We generated expression residuals, adjusting for appropriate covariates, for cell–specific genes (Zhang. Y et al, Neuron 2016) expressed in our dataset (neurons1⁄4415; astrocytes1⁄4234; oligodendroglia1⁄4117; microglia1⁄4352, endothelia1⁄498 genes). We used principal components analysis to generate a surrogate variable (signed eigenvector 1: EV1) representing cell-specific transcripts for each cell type. Each cell-specific EV1 was used as a quantitative variable to test for association with diagnosis, age, sex or APOEε4 genotype (linear regression, R software). Pairwise correlations were tested between all cell-specific EV1 levels (Pearson correlation, R). Analyses were done on the complete cohort, adjusting for diagnosis, and for each individual diagnostic group. We also performed a genome-wide association study (GWAS; linear regression, PLINK) for each cellspecific EV1 on the complete cohort. Results: Significant positive correlations (r2>0.5; p<2.2E-16) were identified between endothelial EV1 and astrocyte or microglia EV1 levels. Neuronal EV1 was negatively correlated with EV1 levels for all other cell types. These correlations were similar across the diagnostic groups. EV1 for astrocytes, microglia, and endothelia were higher, and for neurons lower, in AD subjects compared to other groups, with similar trends observed also for female sex and APOEε4. GWAS did not identify genome-wide significant variants (p<1E08), although suggestive associations include variants at the TMEM106B locus with astrocytes (p1⁄49.0E-07), and an intergenic locus (Chr2) flanked by NXPH2 and LRP1B(p1⁄42.1E-08) with microglia. Conclusions:We have identified brain cell type variability across different diagnosis groups and genetic associations that may influence these. These findings imply specific vulnerabilities for different cell types. We are performing similar analyses in cerebellum, and additional human and mouse brain transcriptome datasets.

TRANSCRIPTOME ANALYSIS IN BLOOD AND BRAIN IDENTIFIES GENE EXPRESSION REGULATION AND CORRESPONDING QUANTITATIVE TRAIT LOCI IN ALZHEIMER’S DISEASE

Background: TDP-43 (transactive response DNA-binding protein 43kDa) proteinopathy is closely associated with Alzheimer’s disease (AD), and affects clinical outcome in AD. TMEM106B rs1990622is a risk allele for TDP-43 proteinopathy, and its implications in clinical presentations of AD remains to be elucidated. Methods: Our subjects are from Religious Orders Study and the Rush Memory and Aging Project (ROS-MAP), two communitybased longitudinal cohort studies of older adults. Our analyses included 841 subjects with genotyping, cognitive, and pathology data (beta-amyloid, paired helical filament tau, and TDP-43 stage). Cognitive decline was defined as the slope of change in composite cognitive z-score in a general linear mixed model, controlling for age at enrollment, sex, and education. The imputed dosage of TMEM106B rs1990622 was tested for its association with cognitive decline after adjusting for AD pathology. Then, TDP-43 was included in the model, and a subsequent mediation analysis (quasi-Bayesian Monte Carlo method with 10,000 simulations) was done to evaluate whether the TMEM106Bvariant’s effect was mediated by TDP-43 proteinopathy. Of note, all analyses were adjusted for study cohort (ROS vs MAP), genotyping platform, and first three principal components from the genotype covariance matrix. Results:TMEM106B rs1990622was associated with more rapid cognitive decline when controlled for the AD pathology (EE1⁄4-0.0098, 95% confidence interval (CI) -0.018 to -0.0016, p1⁄40.020). When TDP-43 stage was also controlled, the association of rs1990622 with cognitive decline loses statistical significance (p1⁄40.078). A mediation analysis shows that about 15% of the association between rs1990622 and more rapid cognitive decline is mediated by more advanced TDP-43 stages (average causal mediation effect p<0.0001). Conclusions: TMEM106B rs1990622, a known TDP-43 proteinopathy risk variant, is associated with more rapid cognitive decline in people with similar degree of AD pathology, and this association is mediated by more advanced TDP-43 stages. Nonetheless, the association of rs1990622 with more rapid cognitive decline in AD is only partially explained by the link between rs1990622 and more advanced TDP-43 stages.

Targeted re-sequencing of sorl1 in early-onset Alzheimer’s dementia: The european early onset dementia consortium

Background:To identify rare mutations by targeted sequencing in eight genes initially detected in genome-wide association studies (GWASs) of late onset Alzheimer’s disease (LOAD). Methods: We conducted targeted sequencing of ABCA7, BIN1, CD2AP, CLU, CR1, EPHA1, MS4A4A/MS4A6A and PICALMin three independent LOAD cohorts: 176 patients from 124 Caribbean Hispanics families, 120 patients and 33 unaffected individuals from the 129 NIA-LOAD Family Study; and 263 unrelated Canadian individuals of European ancestry (210 sporadic patients and 53 controls). The variants were called using the BWA-GATK pipeline. Rare coding mutations found in at least two datasets were genotyped in independent controls similar in age and sex distributions and ancestry to the cases in all datasets to estimate population-based frequencies. Results:We detected a statistically significant 3.71-fold enrichment of the non-synonymous mutations in both cohorts of Caucasian LOAD cases compared with controls (p1⁄40.001) but the mutation rate of non-coding mutations was same in cases and controls. In total, we detected 88 rare damaging mutations, 12 of which were found in at least two datasets: four mutations in ABCA7, two each in CD2AP and PICALM, and one each in BIN1, EPHA1, CLU and MS4A6A. Three of these mutations were observed in all datasets: rs138047593 (BIN1 p.K358R), rs202178565 (EPHA1 p.P460L), and rs138650483 (MS4A6A p.V218M).. The variant in EPHA1 segregated completely in an extended Caribbean Hispanic family and was observed in only one of 300 controls of similar ancestry. Additionally, p.K358R in BIN1segregated in two of the six families where the mutations were discovered. Conclusions: Targeted sequencing of well-confirmed GWAS loci revealed an excess burden of deleterious coding mutations in LOAD with the greatest burden observed in ABCA7 and BIN1. The rarity of these mutations does not fully explain all the associations observed in GWAS, but do represent independent contributions to LOAD pathogenesis. Identifying coding sequence variants in LOAD will facilitate the creation of tractable models for investigation of disease related mechanisms and potential therapies.