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Microglia, the innate immune cells of the brain, influence Alzheimer’s disease (AD) progression and are potential therapeutic targets. However, microglia exhibit diverse functions, the regulation of which is not fully understood, complicating therapeutics development. To better define the transcriptomic phenotypes and gene regulatory networks associated with AD, we enriched for microglia nuclei from 12 AD and 10 control human dorsolateral prefrontal cortices (7 males and 15 females, all aged >60 years) before single-nucleus RNA sequencing. Here we describe both established and previously unrecognized microglial molecular phenotypes, the inferred gene networks driving observed transcriptomic change, and apply trajectory analysis to reveal the putative relationships between microglial phenotypes. We identify microglial phenotypes more prevalent in AD cases compared with controls. Further, we describe the heterogeneity in microglia subclusters expressing homeostatic markers. Our study demonstrates that deep profiling of microglia in human AD brain can provide insight into microglial transcriptional changes associated with AD.

Microglia contribute to Alzheimer’s Disease (AD) progression and are candidate therapeutic targets for disease modulation. Single cell transcriptomics demonstrate microglia adopt multiple phenotypes. However, identifying the human AD microglia profile was limited by small numbers. We employed fluorescence activated nuclei sorting prior to single-nucleus RNA-seq on human prefrontal cortices boosting the number of microglia analyzed per subject. We observed microglia subpopulations previously unrecognized in human brain and mapped their transcriptomic relationships by trajectory inference. We identified three clusters enriched for endolysosomal pathways, one of which showed differential expression of AD GWAS genes, in addition to genes implicated in nucleic acid detection and interferon signaling. We histologically demonstrated a microglia subpopulation with cytosolic nucleic acid and altered endolysosome morphology in AD tissue. Analysis of the “homeostatic” microglia cluster revealed a uniquely AD subpopulation. Our study demonstrates the value of deeply profiling microglia to explore the biological implications of microglia transcriptomic diversity.

Microglia-mediated neuroinflammation is hypothesized to contribute to disease progression in neurodegenerative diseases such as Alzheimer9s Disease (AD). Microglia demonstrate heterogeneous states in health and disease, with proposed beneficial, harmful, and disease specific subtypes. Defining the spectrum of microglia phenotypes is an important step in rational design of neuroinflammation modulating therapies. To facilitate improved phenotype resolution and group comparisons based on disease state we performed single-nucleus RNA-seq on more than 120,000 microglia nuclei from AD and control dorsolateral prefrontal cortex. We identify clusters of microglia enriched for biological pathways implicating defined myeloid roles. We detected several previously unrecognized microglia populations in human AD brain, including three internalization and trafficking subtypes that were heterogeneous in their metabolic and inflammatory signatures. One of these endolysosomal subtypes is larger in AD individuals and was uniquely enriched for genes involved in nucleic acid detection and activation of interferon signaling. This inflammatory endolysosomal cluster also differentially regulated expression of genes associated with AD risk by genome wide association studies. We also identified a cluster of microglia with upregulated cell cycle and DNA repair genes that is proportionately larger in control individuals. Within cluster comparisons demonstrate that in AD brain, homeostatic microglia subpopulations upregulate inflammatory gene expression. These results highlight the heterogenous nature of the microglia response to AD pathology and will inform efforts to target specific subtypes of microglia in the development of novel AD therapies.

Let $\mathcal{X} : y^2 = f(x)$ be a hyperelliptic curve over $\mathbb{Q}(T)$ of genus $g\geq 1$. Assume that the jacobian of $\mathcal{X}$ over $\mathbb{Q}(T)$ has no subvariety defined over $\mathbb{Q}$. Denote by $\mathcal{X}_t$ the specialization of $\mathcal{X}$ to an integer $T=t$, let $a_{\mathcal{X}_t}(p)$ be its trace of Frobenius, and $A_{\mathcal{X},r}(p) = \frac{1}{p}\sum_{t=1}^p a_{\mathcal{X}_t}(p)^r$ its $r$-th moment. The first moment is related to the rank of the jacobian $J_\mathcal{X}\left(\mathbb{Q}(T)\right)$ by a generalization of a conjecture of Nagao: $$\lim_{X \to \infty} \frac{1}{X} \sum_{p \leq X} - A_{\mathcal{X},1}(p) \log p = \operatorname{rank} J_\mathcal{X}(\mathbb{Q}(T)).$$ Generalizing a result of S. Arms, \'A. Lozano-Robledo, and S.J. Miller, we compute first moments for various families resulting in infinitely many hyperelliptic curves over $\mathbb{Q}(T)$ having jacobian of moderately large rank $4g+2$, where $g$ is the genus; by Silverman's specialization theorem, this yields hyperelliptic curves over $\mathbb{Q}$ with large rank jacobian. Note that Shioda has the best record in this directon: he constructed hyperelliptic curves of genus $g$ with jacobian of rank $4g+7$. In the case when $\mathcal{X}$ is an elliptic curve, Michel proved $p\cdot A_{\mathcal{X},2} = p^2 + O\left(p^{3/2}\right)$. For the families studied, we observe the same second moment expansion. Furthermore, we observe the largest lower order term that does not average to zero is on average negative, a bias first noted by S.J. Miller in the elliptic curve case. We prove this bias for a number of families of hyperelliptic curves., Comment: 16 pages