. Brain cell type-specific enhancer-promoter interactome maps and disease-risk association. Science. 2019 Nov 29;366(6469):1134-1139. Epub 2019 Nov 14 PubMed.

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  1. This is an extraordinary study that provides a final piece of evidence for the causal involvement of microglia in Alzheimer’s disease. This work follows up a previous report from the same group, where the authors performed transcriptomic analysis of human microglia isolated from surgical resections (Gosselin et al., 2017). Whereas that report focused on gene expression and critical differences between mouse and human transcriptomes, especially within the context of Alzheimer’s disease risk genes, the present study presents first evidence of functional impact of genetic polymorphisms in noncoding regions in microglia. Previous work by Novikova et al., already reported similar observations in monocyte/macrophage populations (Novikova et al., 2019), but the work from the Glass lab takes this a step further by studying the effect of modifications in those regulatory elements in isolated microglia.

    One of the most exciting observations is perhaps the microglial-specific effect of deleting the BIN1 enhancer region in iPSC-derived cells. This adds an additional level of complexity to the system, as it suggests that the exact same genetic polymorphism in enhancer regions may alter the expression level of target genes only in particular cell types.

    In light of these findings, it is now crucial to carefully study the functional impact of these genetic variants in human systems, starting from in vitro studies using iPSC-derived microglia, but also upgrading to more complex strategies using co-cultures and xenograft models that allow one to explore the response of the cells in their native brain environment (Mancuso et al., 2019; Hasselmann et al., 2019). 

    References:

    . An environment-dependent transcriptional network specifies human microglia identity. Science. 2017 Jun 23;356(6344) Epub 2017 May 25 PubMed.

    . Stem-cell-derived human microglia transplanted in mouse brain to study human disease. Nat Neurosci. 2019 Dec;22(12):2111-2116. Epub 2019 Oct 28 PubMed.

    . Development of a Chimeric Model to Study and Manipulate Human Microglia In Vivo. Neuron. 2019 Sep 25;103(6):1016-1033.e10. Epub 2019 Jul 30 PubMed.

    View all comments by Renzo Mancuso
  2. The current work from the Glass lab provides striking evidences that a significant number of SNPs associated with LOAD likely affect gene expression exclusively in microglia. In particular, in the context of BIN1, the present work confirms what we previously hypothesized, i.e., that SNP rs6733839 in the BIN1 locus would affect BIN1 expression specifically in microglia (Crotti et al., 2019).

    Following up on such hypothesis, and considering the correlation between BIN1 SNPs and tau-PET levels, we investigated the role of BIN1 in microglia in the context of tau pathology. We observed that BIN1-associated, tau-containing extracellular vesicles purified from CSF of AD-affected individuals are seeding-competent. Furthermore, we showed that genetic deletion of Bin1 from microglia resulted in reduction of tau secretion via extracellular vesicles in vitro, and in decrease of tau spreading in vivo. Our observations suggest that BIN1 could contribute to the progression of AD-related tau pathology by altering tau clearance and promoting release of tau-enriched extracellular vesicles by microglia (Crotti et al., 2019). 

    References:

    . BIN1 favors the spreading of Tau via extracellular vesicles. Sci Rep. 2019 Jul 1;9(1):9477. PubMed.

    View all comments by Andrea Crotti
  3. Nott, Holtman, Coufal, and colleagues have produced a tremendous resource by applying several chromatin assays to purified human brain cell types. This builds on their previous work, which was the first to investigate the gene regulatory landscape of human ex vivo microglia (Gosselin et al., 2017). In their recent study they applied nuclear sorting techniques to purify the major cell types of the human brain. They then used several genome-wide assays of chromatin biology to map noncoding elements active in each cell type. Crucially, they identify the long-range interactions between enhancers and genes using assays of chromatin conformation. Linking distal gene regulatory elements to their targets genes is not a trivial task, and when combined with data from common variant studies of disease (e.g., GWAS) can provide crucial links between risk alleles and effector genes (e.g. Miguel-Escalada et al., 2019). 

    While the authors use their data to annotate a variety of neuropsychiatric disease genetic hits, they focus on Alzheimer’s disease. Their analysis shows that Alzheimer’s disease risk variants are likely to operate in microglia, consistent with previous investigations (Tansey et al., 2018). Similar to a recent study using chromatin conformation data from peripheral myeloid cells (Novikova et al., 2019), they are able to link Alzheimer’s disease risk variants to target genes. Importantly, these highlighted genes are often not those most proximal to the associated variants. Together, they nominate cell types (microglia) and target genes important for the genetic risk mechanisms of Alzheimer’s disease.

    Following this large-scale analysis, they functionally validate the interaction between a risk variant containing microglial enhancer and the BIN1 promoter using genome engineering of human stem cell models. The BIN1 locus contains one of the most significantly associated common risk variants for Alzheimer’s disease, but formal links to BIN1 have been lacking. As the authors note, BIN1 is expressed in multiple cell types. However, the risk mechanism appears to be specific to microglia. This information is critical for appropriate downstream biological investigation. Those interested in the biology of Alzheimer’s disease risk genes will need to consider their nominated genes and model systems carefully.

    This study offers much-needed progress along the difficult path from statistical association to biological investigation. However, many risk loci are still poorly annotated. Undoubtedly, similar data from additional cell types and states will be required to fully resolve the genetic risk mechanisms of Alzheimer’s disease. Nevertheless, these data provide high-quality microglial gene targets relevant to the pathogenesis of Alzheimer’s disease that will accelerate biological investigations.

    References:

    . An environment-dependent transcriptional network specifies human microglia identity. Science. 2017 Jun 23;356(6344) Epub 2017 May 25 PubMed.

    . Integration of Alzheimer’s disease genetics and myeloid cell genomics identifies novel causal variants, regulatory elements, genes and pathways. 2019 Jul 6. bioRXiv

    . Genetic risk for Alzheimer's disease is concentrated in specific macrophage and microglial transcriptional networks. Genome Med. 2018 Feb 26;10(1):14. PubMed.

    . Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes. Nat Genet. 2019 Jul;51(7):1137-1148. Epub 2019 Jun 28 PubMed.

    View all comments by Matthew Hill
  4. The Nott et al. paper is of particular interest for those of us who try to decipher how genes can be potentially regulated in different brain cell types through common and specific enhancers.

    In particular, the authors beautifully demonstrated that an enhancer sequence is able to specifically drive BIN1 expression in microglia. This sequence of 360 pb contains the sentinel SNP (rs6733839) of the BIN1 locus, and it is tempting to consider that it is therefore the causal variant because of the convergence of these genetic and biological data. However it is important to note that the real functionality of this SNP has not been assessed in this paper. For this purpose, it would have been necessary to develop iPSC-derived microglia, neurons, and astrocytes specifically mutated for this variant, and to compare the BIN1 expression level in the mutated and corresponding isogenic cells.

    There is no data showing that this variant is able to modulate the microglia enhancer activity. It is thus an overstatement to claim that rs6733839 is the causal variant.

    In addition, we previously reported that the BIN1 causal variant is likely located within a 6.7 kb region encompassing rs6733839 (Chapuis et al., 2013). In this region, we detected three SNPs reaching genome-wide significant level, including rs6733839. However, only one of them, rs59335482, an insertion-deletion variant, was able to modulate the luciferase activity assay in different cell types, including a neuroblastoma cell line (keeping in mind all the limitations of such an approach). This variant unfortunately is not imputed in the IGAP database and Nott et al. have likely missed this information. However, this may, for instance, explain in part why Grubman et al. found no change in microglial BIN1 expression in the entorhinal region of AD cases when compared with controls.

    References:

    . Increased expression of BIN1 mediates Alzheimer genetic risk by modulating tau pathology. Mol Psychiatry. 2013 Nov;18(11):1225-34. Epub 2013 Feb 12 PubMed.

    . Microglia mediate diesel exhaust particle-induced cerebellar neuronal toxicity through neuroinflammatory mechanisms. Neurotoxicology. 2016 Sep;56:204-214. Epub 2016 Aug 16 PubMed.

    View all comments by Jean-Charles Lambert

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  1. Cell-Specific Enhancer Atlas Centers AD Risk in Microglia. Again.