Aims

Alzheimer’s disease (AD) biomarkers show promise in aiding diagnosis and prediction by representing several neurodegenerative processes, such as synaptic dysfunction, neuronal inflammation and injury. Biomarkers could also aid in discovery of AD related genes and inform which biological mechanisms underlie a genetic risk effect. We therefore performed an exome-wide rare variant analysis of six AD biomarkers (β-amyloid, total/phosphorylated tau, NFL, YKL-40, and Neurogranin) to discover genes associated with these indicators and test whether they mediate genetic effects on AD symptoms.

Methods

We performed the exome-wide analysis in two studies: the European Medical Information Framework AD study and the AD Neuroimaging Initiative. Whole exome sequencing and biomarker information data was available for 505 participants. We applied a principal component (PC) analysis to derive combinations of biomarkers, which represent statistically independent biological processes. We then tested whether rare variants in 13,799 protein-coding genes associate with the PCs using a Meta-SKAT test. We also tested whether the PCs are intermediary to gene effects on AD symptoms with a SMUT test.

Results

One PC loaded on NFL and YKL40, both indicators of neuronal injury. Three genes were associated with this PC: IFFO1, PLEKHM1, and DTNB. Mediation tests suggested, that these genes also affect AD symptoms via NFL and YKL40. We also observed an association between a PC loading on Neurogranin and GABBR2 and CASZ1, but no mediation effects.

Conclusions

The results suggest that mutations in IFFO1, PLEKHM1, and DTNB heighten susceptibility to neuronal injury, potentially by altering cytoskeleton structure, resulting in an elevated AD risk.

Aims

Structural variants (SVs) are an important source of genetic diversity and have been linked to many diseases. However, their contribution to molecular traits in the brain and its impact on neurodegenerative diseases remains unknown.

Methods

Here, we integrated whole-genome sequencing of 1,860 subjects from four aging cohorts (ROS/MAP, MSBB, and Mayo Clinic) plus multi-omics data derived from RNAseq, CHIPseq, and Proteomics, to identify SVs and measure their impact through the regulatory cascade and disease.

Results

We identified and genotyped a total of 170,996 SVs, 16% detected only in our dataset. Validation using PacBio long-read sequencing of selected samples showed confirmation rates higher than 85%. Associations of SVs with Progressive Supranuclear Palsy (PSP) identified previously known SVs at MAPT locus and several other novel suggestive associations. We also identified a total of 2,182 SVs altering the expression of 2,518 genes in the dorsolateral prefrontal cortex tissues, many of them, related to neuro diseases like, for example, a known 157kb duplication in KANSL1 (in MAPT locus). Additionally, more than 600 SV-gene pairs were found being affected in more than one molecular phenotype, with significant positive correlation in direction of effect between RNA, H3K9ac peaks, and protein levels.

Conclusions

Overall, we present the most comprehensive map of structural variation in aging cohorts. We further show that many of the SVs have an impact on regulatory variation from RNA to protein and epigenome in the human brain. Our catalog is a valuable resource for understanding the functional impact of SVs in neurodegenerative and neuropsychiatric diseases.

Aims

Exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. To reveal intermediate molecular pathways connecting genetic variance to development of dementia, we aimed to identify protein quantitative trait loci (pQTLs) in cerebrospinal fluid (CSF) in Alzheimer’s disease (AD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD).

Methods

We included 503 subjects for discovery (146 controls, 214 AD, 50 DLB, 93 FTD) and 99 for validation from the Amsterdam Dementia Cohort, from which genetics (Illumina Genome Screening Array) and CSF proteomics (n=665, ligand-proximity immunoarrays) was available. Association signals between risk loci and CSF proteins were tested using linear regression with Bonferroni correction, adjusted for principal components, age and sex and stratified by diagnosis.

Results

Three AD and one DLB risk loci were associated with levels of seven CSF proteins (Figure 1). CR1 locus associated with higher CR2 (P_discovery=5.47e-7, P_replication=1.66e-3), ZCWPW1 with lower PILRB (P_discovery=2.73e-32, P_replication=7.82e-8) and HESX1 with higher RETN CSF levels (P_discovery=6.00e-8, P_replication=0.01); proteins related to the immune system and glucose metabolism. DLB locus GBA associated with higher CSF protein levels of ANG, CD79B, CXCL13 and TNFRSF13B (all P_discovery<1.00x10^-8); proteins associated to angiogenesis and immune response. FTD risk loci did not significantly associate with CSF proteins.

Conclusions

The four pQTLs identified suggest that specific risk loci for AD and DLB may contribute to the pathogenesis of these dementias by exerting effects on the immune system, glucose metabolism and angiogenesis. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying different types of dementia.

Aims

ABCA7 was initially associated with Alzheimer’s disease (AD) in genome-wide association studies. Genetic screening of ABCA7 suggested a role for rare premature termination codon (PTC) mutations. We observed loss of ABCA7 protein in PTC mutation carriers, although with a high variability due to differences in transcript rescue. Additionally, rare missense mutations are present in ABCA7 with an unknown effect on the protein. We aimed to investigate the contribution of rare variants (MAF≤1%), single missense mutations or compound heterozygous mutations in ABCA7 in Belgian AD and control cohorts.

Methods

Targeted resequencing of the ABCA7 coding region or whole exome sequencing in 1365 Belgian AD patients and 976 controls. Allele-specific PCR, haplotype sharing analysis and long-read sequencing to determine cis/trans configuration of compound heterozygous mutations.

Results

We identified missense mutations in 7.3% (99/1365) of the patients and in 4.8% (47/976) of the controls. We observed co-segregation of p.G1820S with AD in a family with autosomal dominant inheritance (Fig.1). We observed compound heterozygous mutations in 10 patients (0.73%, Fig.2) and five controls (0.51%). We confirmed trans configuration in four patients and cis configuration in four other patients. In the remaining two patients, the configuration remains unknown. In the five controls, we confirmed trans configuration in one and cis configuration in the other four.

Conclusions

We observed an enrichment of rare single ABCA7 missense mutations and compound heterozygous carriers in patients. Functional studies of missense mutations are necessary to determine their potential pathogenic effect. In addition, trans compound heterozygous mutations in ABCA7 might modify penetrance and pathogenicity.

Aims

A limited number of studies have looked at the genetics of early onset (≤65 years old) Alzheimer disease (EOAD); hence, there is much unidentified heritability contributing to this form of the disease. This study aims to identify novel genes associated with EOAD risk and investigate its differences compared to late onset AD (LOAD).

Methods

We have combined five cohorts (Knight-ADRC, NIA-LOAD, Cache County, Mayo Clinic and ADSP) to generate the largest to date whole exome sequence (WES) non-Hispanic white EOAD dataset (1,385 cases and 3,867 controls). Sequence data was aligned against GRCh37 reference genome using BWA and GATKv3.5 was used to perform variant calling and QC. Statistical analyses included single variant, gene-based association of rare (MAF<1%) and pathogenic (CADD>20) variants, and pathway analyses.

Results

We found that EOAD is enriched in rare nonsynonymous variants compared to LOAD cases (OR=5.67, p=2.2×10^-16). We identified novel associations (HOXA1 - OR=2.11, p=4.60×10^-14, ADAM29 - OR=6.77, p=2.58×10^-08, DHX16 OR=1.65, p=3.18×10^-08,) and a higher effect of certain variants (TREM2 p.Arg47His, OR=7.28, p=2.02×10^-09) in EOAD compared to previous LOAD studies (OR=2.08-4.07). We identified nine statistically significant (p<0.5×10^-04) genes (SMG5, BCAM, KCNJ1, UBXN6, MIEN1, FRMPD1, ABCD2, ADAT2 and HADHB) in both the MAF<1% and CADD>20 gene-based analysis. These genes are involved in fatty-acid metabolic processes (pval=2.18×10^-04) and in endosome to lysosome transport (p=0.003) and we highlight UBXN6, a known FrontoTemporal Dementia gene.

Conclusions

EOAD is enriched in rare nonsynonymous variants with a higher effect compared to LOAD. The lysosomal pathway arises as important contributor to EOAD with UBXN6 as main character.

Aims

Most Alzheimer’s disease (AD) genetic association studies disregard age or incorrectly account for it, hampering variant discovery.

Methods

Using simulated data, we compared the statistical power of several models: logistic regression on AD diagnosis adjusted and not adjusted for age; linear regression on a score integrating case-control status and age; and multivariate Cox regression on age-at-onset. We applied these models to real exome-wide data of 11,127 sequenced individuals and replicated suggestive associations in 21,631 genotype-imputed individuals (Table1).

Table1. Demographics for discovery and replication samples.

Results

Modelling variable AD risk across age results in 10-20% statistical power gain compared to logistic regression without age adjustment, while incorrect age adjustment leads to critical power loss (Figure1). Applying our novel AD-age score and/or Cox regression, we discovered and replicated novel variants associated with AD (Figure2).

Figure1. Power of different association models evaluated for a common variant with moderate effect size. A-C) Simulation based on 1000/1000 cases/controls at a significance level of α=0.05, for age differences observed in AD cohorts.

Figure2. Manhattan plots of exome-wide-associations in the four models. No suggestive association were observed (p<1×10^-5) for the age adjusted logistic regression. TREM2 known causal variant is exome-wide-significant (p<5×10^-7) in the other models. Among suggestive associations, known AD associations are in red, novel associations which replicate (p<0.05) in an independent dataset are in blue.

Conclusions

Our AD-age score provides a simple means for statistical power gain.

Aims

Alzheimer’s disease (AD) is an incurable neurodegenerative disease with known pathology across a diverse number of cortical regions and well described genetic risk factors yet defined AD disease mechanisms remain undescribed. We leverage cis-genetic variants to impute genetic expression components which are generalizable across multiple affected tissues and implicate 8 genes which have genetic based expression components associated to AD.

Methods

We modified the FUSION TWAS pipeline to ingest 888 expression profiles from multiple neocortical regions (TCX=248, FP=50, IFG=41, STG=34, PHG=34, DLPFC=461) paired to Northern European (CEU) ancestrally matched genotypes. Trained weights imputed expression components across 2003 CEU genotype profiles and we preformed a TWAS to AD.

Results

Cis-variant architecture alone was informative to train weights for 6780 (49.67%) genes, the majority of which significantly correlated with gene expression; FDR < 5%: N=6775 (99.92%), Bonferroni: N=6716 (99.06%). Median correlation to observed gene expression was 0.2176 (IQR = 0.179-0.277). Validation rate within CommonMind Consortium DLPFC and anterior cingulate cortex was (71.08%) and (22.52%) respectively. Correction for joint conditional probability (JCP) and summary mendelian randomization (SMR) yielded 8 genes significantly associated with AD (FDR < 0.05); APOC1 (JCP=2.22e-22, SMR=3.41e-4), EED (JCP=3.373e-5, SMR=2.50e-4), CD2AP (JCP=2.96e-5, SMR=2.66e-4), CEACAM19 (JCP=3.27e-5, SMR=1.00e-2), CLPTM1 (JCP=4.04e-3, SMR=2.58e-3), MTCH2 (JCP=0.011, SMR=3.32e-6), TREM2 (JCP=0.021, SMR=2.64e-3), KNOP1(JCP=0.039, SMR=2.50e-4).

Conclusions

We provide evidence of cis-genetic variation conferring AD risk through 8 genes across six distinct genomic loci. Moreover, we provide a valuable resource to the community in the form of predictive gene expression weights that are abstractable to multiple neocortical regions and neuronal phenotypes.

Aims

In a long-lasting effort to collect clinicopathological data and biomaterials from AD patients for genetic studies, we identified a multigenerational Flanders-Belgian family with autosomal dominant EOAD. We collected DNA, biomaterials and clinicopathological data in 2 consecutive generations: 5 AD patients (onset 64.2±13.2y), 2 with definite neuropathological diagnosis and 9 unaffected or at-risk individuals.

Methods

WES data of 4 patients. Selection of shared rare non-synonymous variants. Validation, co-segregation and frequency assessment using massive parallel-targeted sequencings (MPS). Candidate genes re-sequencing using MPS in a Belgian cohort of 320 EOAD (onset 57.8±5.9y) and 1166 late-onset (LO)AD (onset 77.1±6.5y) patients and a control cohort of 934 persons (inclusion 70.45±9.2y). Variants pathogenicity evaluated by NF-κB luciferase assay. Aβ₄₂ phagocytosis assay performed in iPSC-derived microglia in presence of conditioned media.

Results

TLR9 p.E317D (novel) co-segregated with EOAD in the family and was absent from the controls and public databases of variants. Resequencing identified additional rare variant carriers: 7 in EOAD (7/320, 2.19%) and 19 in LOAD (19/1166, 1.63%) patients and 8 in controls (8/934, 0.86%), while p.E317D was absent. TLR9 is a DNA-sensing receptor expressed in immune cells, activated by unmethylated CpG oligonucleodides leading to innate immune cells activation and mounting acquired responses. The NF-κB luciferase assay showed that p.E317D caused 50% reduction in receptor activation. We also demonstrated that wild-type TLR9 activation in cultured lymphocytes induced Aβ₄₂ phagocytosis when added to human iPSC-derived microglia.

Conclusions

We suggest that TLR9 mutations reduce receptor activation in the periphery with a consequent effect in brain.