ApoE2 lowers Alzheimer’s risk; ApoE4 raises it. But what explains the people who buck this trend—i.e., the ApoE2 carriers who get AD, and ApoE4 carriers who stay free of it into old age? In the December 7 Alzheimer’s and Dementia, researchers led by Olivier Lichtarge at Baylor College of Medicine in Houston used evolutionary genetics to investigate this question. The researchers hunted for genetic variants associated with these so-called paradoxical phenotypes. They identified more than 200 genes that may either shield ApoE4 carriers from AD, or render ApoE2 carriers vulnerable to it.
- Scientists pinpoint 216 genes that counter ApoE2 protection, ApoE4 risk.
- For some, expression was linked to GWAS variants.
- Genes involved in synaptic function, lipoprotein regulation, and inflammation.
Many of the genes were differentially expressed in AD brain samples, had close ties to previously reported AD risk genes, and even predicted a person’s disease status. Their products play roles in familiar processes such as synaptic function, inflammation, and protein trafficking. If validated in larger cohorts, these potential modifiers could help stratify cohorts by disease risk, serve as biomarkers, or even be viable therapeutic targets, the authors propose.
Genetic variation accounts for as much as 80 percent of the population burden of AD, yet much of the heritability remains unexplained. While more than 30 common genetic variants—many in noncoding stretches of the genome—have emerged from genome-wide association studies, sequencing studies have plucked out handfuls of rare variants that hold stronger sway over a person’s risk. While ever-larger studies will unearth more variants, scientists have also devised creative ways of leveraging existing data to dig out more genetic paydirt.
Because ApoE remains the strongest genetic AD risk factor, stratifying genetic data based on ApoE genotype has the potential to shine a light on variants previously hidden within the apolipoprotein’s shadow. In 2018 the Alzheimer’s Disease Sequencing Project published the largest whole-exome sequencing study, which identified two new rare variants (Aug 2018 news). The following year, ADSP researchers stratified the data based on ApoE4 status, identifying unique risk variants (Jun 2019 news).
In a variation on this theme, co-first authors Young Won Kim and Ismael Al-Ramahi and colleagues used the ADSP exome data to fish out genes that influenced disease so much that they counteracted the effects of ApoE genotype. With some 11,000 exomes to choose from, they limited their analysis to those from outliers—that is, 179 ApoE2 carriers who had AD, and 301 ApoE4 carriers who did not.
As evolutionary geneticists, the researchers called on phylogenetic changes over millennia to pick out potentially impactful mutations lurking within the exomes of the two groups. Essentially, this so-called “evolutionary action” approach is a way to gauge the functional impact of an amino acid change within a protein’s coding sequence. EA takes into account a given amino acid’s importance in driving evolution, and also the potential impact of swapping that amino acid with another. The researchers pulled out genes with an unusually high EA load, using some statistical wizardry called differential “imputed deviation in EA load,” aka iDEAL, in the two paradoxical ApoE groups. They fished out 216 iDEAL genes: 148 genes were riddled with potentially pathogenic variants that might have put the ApoE2 carriers at risk, and 68 genes were brimming with potentially beneficial variants that may have fended off disease in the healthy ApoE4 carriers.
For an example of how this approach works, consider one of the hits, i.e. TREM2. Likely pathogenic variants in this gene were significantly more common in ApoE2 carriers who had AD (ApoE2-AD) than they were in healthy controls who carried ApoE4 (ApoE4-HC). The pathogenic changes included the well-known AD risk variant R47H, which was seven times more common in the ApoE2-AD than the ApoE4-HC group.
The EA load calculation also took into account TREM2 rarer variants with a higher impact, such as the T96K variant, as well as a cadre of less-impactful variants. Though many of these variants would have fallen short of statistical significance in a typical GWAS, the EA approach took all of them into account to gauge TREM2’s aggregate mutational burden. The findings suggest that variants that harm TREM2 function could erode disease protection in ApoE2 carriers.
TREM2 variants have been tied to AD risk regardless of ApoE genotype. Could other genes identified with this iDEAL approach also associate with AD independently of ApoE? Perhaps. The researchers found that among ApoE3 homozygotes in the ADSP dataset, potentially protective variants in ApoE4-HC iDEAL genes were enriched in healthy controls compared to cases, and the opposite was true for pathogenic variants in ApoE2-AD iDEAL genes. The genes could therefore influence AD pathogenesis regardless of ApoE, the researchers proposed.
To investigate the wider relevance of iDEAL genes, the researchers looked for them in other AD datasets. Using gene-expression data from the Accelerating Medicines Partnership–AD sequence repository, they found that 75 iDEAL genes were differentially expressed in AD brain samples relative to controls. Referencing GWAS data, they found that iDEAL genes were more closely tied to GWAS hits in protein interaction networks than would be expected by chance. In fact, 25 iDEAL genes interact directly with genes involved in Aβ and tau pathology.
In addition to moving in the same functional circles as GWAS proteins, seven iDEAL genes— GOLGA5, PTBP1, SYTL2, SMARCD2, GAMT, TREM2, and AZU1—landed within 500 kilobases of a GWAS hit, suggesting they could even represent the causal gene behind the disease association.
The researchers also found that 39 of the iDEAL genes interacted with 390 compounds in the Drug Interaction Database, suggesting they could make drug targets. Three genes—ITGA2B, ALDH5A, and HDAC7—interact with two drugs, enoxaparin and valproic acid, that have been tied to lower AD incidence in a population study (Kern et al., 2019). Knocking down or overexpressing 69 iDEAL genes either ameliorated or exacerbated climbing defects in fruit fly models of amyloidosis or neurofibrillary tangles. As flies have no ApoE homolog, this suggests that at least some of these genes alter AD risk independently of the lipoprotein.
Might iDEAL gene variants be used to gauge AD risk? Using a statistical machine-learning approach, the researchers found that they were able to distinguish between ApoE2 carriers with AD and healthy ApoE4 carriers. A subset of just 94 iDEAL gene variants was sufficient to separate the two groups. Moreover, within the larger ADSP dataset, iDEAL variants predicted which ApoE2 carriers would develop AD, and which ApoE4 carriers would remain healthy.
What do these genes do? An analysis of their biological pathways revealed that many are involved in keeping synapses up and running. Axonal projection, protein trafficking, microtubule transport, and dendritic spine pathways featured prominently, as well as ApoE-related functions such as lipoprotein regulation.
The researchers combed through single-cell transcriptomic data from postmortem brain samples, and placed many iDEAL genes within cell-type-specific functional networks (McKenzie et al., 2018, and see below). In neurons, iDEAL genes cropped up in synaptic signaling and plasticity pathways. In microglia, the genes were involved in inflammation, autophagy, and lysosomal function, as well as synaptic pruning. Interestingly, five iDEAL genes in two different cell types—CNTN1 and NCKAP in neurons and NRXN2, ABHD2, and TIA1 in microglia—take part in the same process, i.e. dendritic spine maintenance.
iDEAL Networks. iDEAL genes (green) and genes that directly interact with them (gray) are involved in critical cell-type-specific brain functions. [Courtesy of Kim et al., Alzheimer’s and Dementia, 2020.]
Michael Ewers of Ludwig Maximilian University in Munich called the genetic approaches in the study elegant. “The study revealed a large number of genes harboring either detrimental or protective mutations in ApoE2 and ApoE4 carriers,” he wrote. “These exploratory results will encourage future investigations to follow up these findings in independent exome-sequencing replication cohorts as well as by genome-wide association analyses in larger cohorts. A major question is whether any variants in the depicted genes are modifiers specifically of the effect of ApoE genotype on AD, or are associated with AD risk in general.”
Lichtarge also emphasized that the data will need to be validated in other cohorts, noting that differences in genetic background and even in sequencing protocols can cause variability between studies. He also wants to explore some of the iDEAL genes in human organoid models, and to test therapeutic compounds that cropped up in the drug interaction database.
Adam Naj of the University of Pennsylvania in Philadelphia finds the genes identified in the study interesting because they are in pathways and networks involving AD-susceptibility loci identified in prior GWAS. “Following on these findings, a major question remains: How much do these genes/variants contribute to AD risk in aggregate in larger samples of individuals, and among groups not selected for APOE e4 enrichment and case-control status?” he wrote. “Quantifying their contribution to disease heritability overall may speak to the importance of recruiting sample sets with this kind of enrichment.”—Jessica Shugart
- Largest AD Whole-Exome Study to Date Finds Two New Risk Genes
- Sliced by ApoE Genotype, Whole Exome Data Yield New AD Variants
- Kern DM, Cepeda MS, Lovestone S, Seabrook GR. Aiding the discovery of new treatments for dementia by uncovering unknown benefits of existing medications. Alzheimers Dement (N Y). 2019;5:862-870. Epub 2019 Dec 9 PubMed.
- McKenzie AT, Wang M, Hauberg ME, Fullard JF, Kozlenkov A, Keenan A, Hurd YL, Dracheva S, Casaccia P, Roussos P, Zhang B. Brain Cell Type Specific Gene Expression and Co-expression Network Architectures. Sci Rep. 2018 Jun 11;8(1):8868. PubMed.
No Available Further Reading
- Kim YW, Al-Ramahi I, Koire A, Wilson SJ, Konecki DM, Mota S, Soleimani S, Botas J, Lichtarge O. Harnessing the paradoxical phenotypes of APOE ɛ2 and APOE ɛ4 to identify genetic modifiers in Alzheimer's disease. Alzheimers Dement. 2021 May;17(5):831-846. Epub 2020 Dec 7 PubMed.