Cholesterol-mediated Lysosomal Dysfunction in APOE4 Astrocytes Promotes α-Synuclein Pathology in Human Brain Tissue

Cholesterol-mediated Lysosomal Dysfunction in APOE4 Astrocytes Promotes α-Synuclein Pathology in miBrains, a Human Brain Microphysiological System | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Cholesterol-mediated Lysosomal Dysfunction in APOE4 Astrocytes Promotes α-Synuclein Pathology in miBrains, a Human Brain Microphysiological System View ORCID Profile Louise A. Mesentier-Louro , View ORCID Profile Camille Goldman , View ORCID Profile Sebastian Gaese , View ORCID Profile Alice Buonfiglioli , View ORCID Profile Dimitrios Kyriakis , View ORCID Profile Ashley Harlock , View ORCID Profile Alain Ndayisaba , View ORCID Profile Emily R. Sartori , View ORCID Profile Abigail Uchitelev , John F. Fullard , View ORCID Profile Evelyn Hennigan , Donghoon Lee , View ORCID Profile Braxton R. Schuldt , View ORCID Profile Rikki B. Rooklin , View ORCID Profile Jonathan Barra , View ORCID Profile Jose Javier Bravo-Cordero , Panos Roussos , View ORCID Profile Vikram Khurana , View ORCID Profile Joel W. Blanchard doi: https://doi.org/10.1101/2025.02.09.637107 Louise A. Mesentier-Louro 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA 5 Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network , Chevy Chase, MD, 20815 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Louise A. Mesentier-Louro Camille Goldman 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA 5 Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network , Chevy Chase, MD, 20815 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Camille Goldman Sebastian Gaese 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sebastian Gaese Alice Buonfiglioli 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alice Buonfiglioli Dimitrios Kyriakis 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 6 Department of Psychiatry , Mount Sinai, New York, NY, USA 7 Department of Genetics and Genomic Sciences , Mount Sinai, New York, NY, USA 8 Center for Disease Neurogenomics , Mount Sinai, New York, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Dimitrios Kyriakis Ashley Harlock 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ashley Harlock Alain Ndayisaba 5 Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network , Chevy Chase, MD, 20815 9 Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital , Boston, MA, USA 10 Division of Movement Disorders, American Parkinson Disease Association (APDA) Center for Advanced Research and MSA Center of Excellence, Department of Neurology, Brigham and Women’s Hospital , Boston, MA, USA 11 Harvard Medical School , Boston, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alain Ndayisaba Emily R. Sartori 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Emily R. Sartori Abigail Uchitelev 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA 12 Macaulay Honors College at Hunter College , New York, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Abigail Uchitelev John F. Fullard 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 6 Department of Psychiatry , Mount Sinai, New York, NY, USA 7 Department of Genetics and Genomic Sciences , Mount Sinai, New York, NY, USA 8 Center for Disease Neurogenomics , Mount Sinai, New York, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Evelyn Hennigan 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 6 Department of Psychiatry , Mount Sinai, New York, NY, USA 7 Department of Genetics and Genomic Sciences , Mount Sinai, New York, NY, USA 8 Center for Disease Neurogenomics , Mount Sinai, New York, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Evelyn Hennigan Donghoon Lee 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 6 Department of Psychiatry , Mount Sinai, New York, NY, USA 7 Department of Genetics and Genomic Sciences , Mount Sinai, New York, NY, USA 8 Center for Disease Neurogenomics , Mount Sinai, New York, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Braxton R. Schuldt 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Braxton R. Schuldt Rikki B. Rooklin 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Rikki B. Rooklin Jonathan Barra 13 Department of Medicine, Division of Hematology and Oncology, The Tisch Cancer Center , Mount Sinai, New York, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jonathan Barra Jose Javier Bravo-Cordero 13 Department of Medicine, Division of Hematology and Oncology, The Tisch Cancer Center , Mount Sinai, New York, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jose Javier Bravo-Cordero Panos Roussos 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 6 Department of Psychiatry , Mount Sinai, New York, NY, USA 7 Department of Genetics and Genomic Sciences , Mount Sinai, New York, NY, USA 8 Center for Disease Neurogenomics , Mount Sinai, New York, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Vikram Khurana 5 Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network , Chevy Chase, MD, 20815 10 Division of Movement Disorders, American Parkinson Disease Association (APDA) Center for Advanced Research and MSA Center of Excellence, Department of Neurology, Brigham and Women’s Hospital , Boston, MA, USA 11 Harvard Medical School , Boston, MA, USA 14 The Broad Institute of MIT and Harvard , Cambridge, MA, USA 15 Harvard Stem Cell Institute , Cambridge, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Vikram Khurana Joel W. Blanchard 1 Icahn School of Medicine , Mount Sinai, New York, NY, USA 2 Nash Family Department of Neuroscience , Mount Sinai, New York, NY, USA 3 Friedman Brain Institute , Mount Sinai, New York, NY, USA 4 Ronald M. Loeb Center for Alzheimer’s Disease , Mount Sinai, New York, NY USA 5 Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network , Chevy Chase, MD, 20815 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Joel W. Blanchard For correspondence: joel.blanchard{at}mssm.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Summary The pathological hallmark of neurodegenerative disease is the aberrant post-translational modification and aggregation of proteins, leading to the formation of insoluble protein inclusion bodies. Genetic factors, like APOE4, are known to increase the prevalence and severity of tau, amyloid, and α-synuclein inclusions. However, the human brain is largely inaccessible during this process, limiting our mechanistic understanding. Here, we developed an iPSC-based 3D model that integrates neurons, glia, myelin, and cerebrovascular cells into a functional human brain-like tissue (“miBrain”). Single-nucleus RNA sequencing of miBrains confirmed the presence of diverse cell populations and revealed cell-type-specific transcriptional responses to α-synuclein pathology, including neuronal apoptotic and synaptic gene programs and astrocyte signatures of lipid dysregulation and reactivity. Like the human brain, we found that pathogenic phosphorylation and aggregation of α-synuclein are increased in the APOE4/4 miBrain. Combinatorial experiments revealed that endolysosomal dysfunction caused by cholesterol accumulation in APOE4/4 astrocytes impairs the degradation of α-synuclein and leads to a pathogenic transformation that seeds neuronal inclusions of α-synuclein. Collectively, this study establishes a robust model for investigating protein inclusions in human iPSC-derived brain tissue and highlights the role of astrocytes and cholesterol in APOE4 -mediated pathologies, opening therapeutic opportunities. Introduction Alzheimer’s disease (AD) is canonically associated with amyloid-β and tau pathology 1 . However, neuronal intracellular inclusions of aggregated α-synuclein (α-Syn) are present in 50-90% of AD cases 2 – 5 . Phosphorylated α-Syn often aggregates, forming Lewy Bodies and Lewy neurites, which are frequently found in the brains of individuals with AD 2 – 4 . The occurrence of α-Syn inclusions with amyloid-β and tau exacerbates neurodegeneration, particularly in brain regions associated with memory and executive functions 5 – 10 . Indeed, clinical studies show that AD patients with α-Syn pathology exhibit faster cognitive decline compared to those with only amyloid-β and tau pathology 11 , 12 . The strongest genetic risk factor for late-onset AD, APOE4 , significantly increases both the prevalence and severity of α-Syn pathology in AD 12 , 13 and is one of the most well-replicated genetic risk factors for Lewy Body Dementia (LBD) 14 , 15 . However, the mechanisms by which genetic factors like APOE4 influence the presence and severity of α-Syn pathology are largely unclear. Insights into the mechanisms underlying non-amyloid-β co-pathologies could lead to much-needed therapeutic and diagnostic opportunities in AD and LBD. The development of model systems that faithfully recapitulate α-Syn pathology and the genetic and environmental context of the human brain is essential to uncovering how ancillary genetic factors, such as APOE4 , modify α-Syn-mediated neurodegeneration. The addition of pre-formed fibrils (PFFs) of α-Syn are commonly employed in mice 16 , 17 and in vitro models 18 – 20 to induce α-Syn pathology. PFFs are reported to spread across the brain in a prion-like manner, corrupting endogenous α-Syn and promoting the propagation of pathology 18 , 21 , 22 . However, animal models and in vitro systems with α-Syn PFFs are highly variable and often fail to induce phosphorylated α-Syn-rich inclusions while having significant biohazard concerns due to the use of prion-like particles 23 . This highlights the need to develop tractable models that do not rely on PFFs and can dissect multicellular mechanisms of disease. For instance, the induction of neurodegenerative phenotypes in cells cultured in traditional two-dimensional (2D) conditions may be limited by a chemical and mechanical microenvironment that is vastly different from in vivo conditions 24 . In contrast, three-dimensional (3D) in vitro systems have proven more efficient than 2D systems at replicating key pathological features such as amyloid-β plaques and tau tangles 25 , 26 . Combining genetic approaches with 3D tissue engineering is a promising alternative for developing more physiological models of neurodegenerative disease. We recently developed the human m ulti-cellular i ntegrated Brain ( miBrain ), an induced pluripotent stem cell (iPSC)-derived three-dimensional human brain-like tissue that incorporates neurons, glia, and microvasculature into a brain-like system for modeling neurodegeneration in vitro 27 . The miBrain contains the major cellular components of the human brain, including functionally active neurons, oligodendrocytes, astrocytes, microglia, and a blood-brain barrier-like vasculature. The miBrain can be generated from patient-derived iPSCs. Because it is an engineered tissue, this permits the generation of genetically mixed tissue. For example, coupled with CRISPR-edited iPSC lines, we can generate genetically identical miBrains with AD risk genes such as APOE4 in specific cell types. Using this system, we previously developed reproducible models of amyloid-β and tau neuropathology in the miBrains 27 . Here, we further advance the miBrain platform by developing cryopreservation methods that enable batch production of complete or partial tissues, markedly reducing the batch-to-batch variability and improving the scalability of the model system. Leveraging this advance, we established a highly reproducible model of α-Syn neuropathological phenotypes in an iPSC-derived human brain-like tissue. We then apply this system to investigate how APOE4 influences α-Syn phosphorylation and aggregation in a human multicellular brain context. We found that APOE4 increases α-Syn phosphorylation and neuronal inclusions via non-cell-autonomous mechanisms mediated by lipid accumulation in APOE4/4 astrocytes. Our results establish robust methods for modeling α-synuclein pathological phenotypes in human brain tissue models and highlight a causal role of astrocytes and lipids in APOE4 -mediated α-Syn pathologies, opening new therapeutic opportunities for AD, LBD, and other neurodegenerative diseases. Results miBrains: A human brain microphysiological system Intracellular neuronal inclusions of phosphorylated and aggregated α-Syn have been challenging to reproduce in human brain cells or tissue, typically requiring very long maturation protocols 28 and the concomitant use of PFFs 29 . Therefore, we sought to develop a robust, high-fidelity model of α-Syn intracellular inclusions leveraging the multi-cellular integrated Brain (miBrain). The miBrain is a human brain-like tissue generated by encapsulation of iPSC-derived neurons 29 , 30 , astrocytes 31 , 32 , endothelial cells 33 – 36 , mural cells 33 , 37 , oligodendrocyte precursor cells (OPCs) 38 , and microglia 39 . miBrains displayed homogenous TUJ1 + neuronal networks and PECAM1 + vascular structures ( Figure 1a ). Staining for multiple markers revealed interactions and co-localization between S100β + and AQP4 + astroglia and PECAM1 + vascular structures, vascular coverage with NG2 + mural cells, myelin basic protein (MBP) + /neurofilament + neuro-myelin structures, and the presence of IBA1 + microglia ( Figure 1b ), consistent with the specific cell types encapsulated in the miBrain. All miBrains used in this study contained all the above-mentioned cell types, unless indicated in the figure legend. Download figure Open in new tab Figure 1. Induction of α-Syn intracellular inclusions in a multi-cellular integrated Brain (miBrain) tissue. a . Cartoon and immunofluorescence (IF) of m ulticellular i ntegrated human brain (miBrain) tissue generated from human iPSCs differentiated into six brain cell types. IF of four-week-old miBrains for TUJ1 (cyan) and PECAM-1 (red). Scale bar: 500 µm. b . IF images of two- to four-week-old miBrains stained for cell-specific markers of neurons (Neurofilament-H, TUJ1, NGN2-sfGFP; cyan), astrocytes (S100b, AQP4; green), endothelial cells (PECAM-1; red), mural cells (NG2; green), myelin (MBP; green), and microglia (IBA1, CD68; green, magenta). Scale bar: 50 µm. c. Representative IF images of 18-days-old miBrains containing control or SNCA -A53T overexpression neurons. α-Syn pS129 (red) volume was measured within TUJ1 (cyan) and normalized to control miBrains. Scale bar: 50 µm. Data represents SEM (n = 4 biological replicates). P-value was calculated using Welch’s two-tailed t-test d. Representative IF of α-Syn pS129 (red) inclusion co-localized within sfGFP (green) and TUJ1 (magenta) cells. Scale bar: 50 µm. e. UMAP of annotated cellular clusters in miBrains (n = 43,820 nuclei, including Control, APOE3/3 A53T and APOE4/4 A53T; n = 2 biological replicates per condition, each one containing 2 pooled miBrains). f. Correlation analysis mapping miBrain cell types to human postmortem brain dataset (T. Clarence et al) 122 . g. Split UMAPs of control and APOE3/3 SNCA-A53T miBrains showing similar cluster composition. h. Number of differentially expressed genes (DEGs) per cell type between APOE3/3 A53T and control. DEGs were defined as adj. p 0.5. i. Volcano plot illustrating DEGs in neurons. Upregulated (red) and downregulated (blue) genes are defined by |log2 fold change| > 1.5 and p-value < 0.05. j. Gene Ontology (GO) biological processes enriched in A53T APOE3/3 neurons. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. To functionally validate neuronal network activity within miBrains, we performed multielectrode array (MEA) recordings ( Figure S1a ). miBrains exhibited robust spontaneous electrical activity, with a mean firing rate of 1.968 Hz (± 0.171 SEM; Figure S1b , i ) with near-complete electrode engagement (15–16 active electrodes per array; Figure S1b , ii ). These values confirm the presence of functionally active neuronal populations in miBrains. Additionally, miBrains demonstrated organized network behavior characterized by frequent spontaneous bursts (504 ± 56 SEM; Figure S1b , iii ). Notably, we observed synchronized network bursts involving an average of 6.157 electrodes (± 0.223 SEM; Figure S1b , iv ), comparable to synchronized network activity observed in human brain organoids measured by microelectrode arrays 40 , 41 , indicative of large-scale network coordination. Together, these data suggest that miBrains recapitulate key features of developing neural networks, spatial propagation of activity across electrodes, and emergent synchronization at the network level. In other in vitro platforms, such as brain organoids, significant variability in cell composition has been reported, leading to substantial experimental variability 40 . To minimize miBrain batch-to-batch variability and increase the scalability of the system, we developed methods to cryopreserve large batches of miBrain tissue containing multiple cell types at defined ratios ( Figure S1c ). This strategy provides flexibility and scalability by enabling the thawing of pre-mixed supporting cell populations and the addition of any desired cell type, such as neurons with genetic modifications, at the time of tissue assembly. This eliminates the need for synchronized differentiation of multiple individual cell types before each experiment, ensuring reproducibility and reducing variability. Cryopreserved miBrains retain more than 90% cell viability upon thawing and express specific cell markers two weeks into the 3D culture system ( Figure S1c , d) . The ratio of neurons to nuclei did not significantly differ between three different batches of thawed miBrain tissue (p = 0.292, Figure S1d ). Induction of α-Syn intracellular inclusions in miBrains Phosphorylation of α-Syn on S129 is the predominant pathological modification associated with α-Syn aggregation and neuronal inclusions, and therefore, is an established method for detecting pathogenic transformation of α-Syn 42 , 43 . We first investigated whether the conventionally employed α-Syn PFFs 16 – 20 can increase phosphorylated α-Syn (p-Syn) in the miBrains. Inoculating miBrain culture media with α-Syn PFFs significantly increased p-Syn levels when compared to control miBrains (p = 0.0175, Figure S1e ), indicating the suitability of the tissue to develop α-Syn pathological phenotypes. However, using this approach, p-Syn was mostly seen as dispersed puncta ( Figure S1e ) rather than within the typical neuronal inclusions that are hallmarks of synucleinopathies 44 . In addition, there was a high degree of variability in the presence and induction of p-Syn in miBrains ( Figure S1e ), consistent with reports showing highly variable PFF seeding across different research groups 17 . Therefore, we sought to identify more robust methods for inducing pathogenic α-Syn phenotypes in the miBrain. A recent study found that iPSC-derived neurons express low levels of the gene encoding α-Syn ( SNCA) compared to adult human brain tissue and, therefore, used SNCA overexpression to increase α-Syn to physiological levels and induce its phosphorylation and neuronal inclusions 29 . To achieve brain-like levels of SNCA and induce pathological phenotypes, we generated neurons from iPSCs derived from a donor with familial Parkinson’s disease with inducible expression of SNCA bearing the A53>T mutation ( SNCA- A53T), known to enhance α-Syn’s aggregation 29 , 45 , 46 . SNCA -A53T was fused to a superfolder green fluorescent protein (sfGFP), a variant engineered for robust folding and monomeric stability even when attached to aggregation-prone proteins 47 – 49 , enabling live imaging and direct visualization of α-Syn accumulation. The sfGFP tag has been validated to preserve α-Syn’s aggregation and seeding behavior 50 . Using this approach, we observed that in 2D monocultures, neurons with only endogenous SNCA expression (control) and SNCA- A53T neurons exhibited similar basal levels of p-Syn (p = 0.959), which significantly increased selectively in SNCA- A53T neurons upon addition of PFFs (p< 0.0001, Figure S1f ). This increase was not observed in neurons overexpressing SNCA -A53T lacking the α-Syn non-amyloid component ( SNCA- A53T-ΔNAC) domain (p = 0.952), known to be required for α-Syn aggregation, suggesting that the observed phosphorylation arises from α-Syn biology rather than from the sfGFP fusion. In contrast to 2D cultures, miBrains with SNCA- A53T overexpression in neurons ( SNCA -A53T miBrains) developed a 10.29-fold increase (±1.55 SEM) in neuronal p-Syn compared to isogenic miBrains harboring control neurons (p = 0.0004, Figure 1c ), even in the absence of exogenous PFFs. Monocultures of SNCA- A53T neurons in 3D also displayed PFF-independent increases in p-Syn compared to control neurons (p = 0.0008; Figure S1g ) , suggesting that the more physiological 3D environment is inherently more permissive to α-Syn pathology. We found the addition of PFFs in SNCA- A53T miBrains further increased p-Syn levels compared to SNCA- A53T miBrains without PFFs (p = 0.038, Figure S1h ), consistent with the amplification of pathological phenotypes after seeding with PFFs. A fraction of the SNCA-A53T-sfGFP signal co-localized with p-Syn ( Figure 1d and Video S1 ), indicating that, while not all SNCA-A53T gets phosphorylated, it is phosphorylated to a similar extent with or without PFFs in the miBrain environment (p = 0.275, Figure S1i ). When further analyzing the localization of p-Syn, we observed that p-Syn primarily colocalized with sfGFP, indicating the phosphorylation of overexpressed SNCA-A53T (Control: 86.7% ± 1.9 SEM, PFFs: 88.0% ± 1.4 SEM). Additionally, we found a fraction p-Syn that did not co-localize with sfGFP, indicating that endogenous, non-A53T α-Syn in neuronal and possibly non-neuronal cells is also phosphorylated (Vehicle: 13.3% ± 1.9 SEM, PFFs: 12.0% ± 1.4 SEM ; Figure S1j ). Collectively, these results show that SNCA -A53T miBrains developed p-Syn-rich inclusions via corruption of both induced (A53T) and endogenous α-Syn without requiring the use of PFFs. Single-nucleus RNA sequencing (snRNA-seq) was performed to define the cellular composition of miBrains and to assess transcriptional changes associated with SNCA- A53T expression specifically in neurons within isogenic miBrains. Distinct neuronal and glial populations including neurons, astrocytes, microglia, endothelial cells, mural cells, and OPCs were identified based on canonical marker expression and transcriptional similarity to a published dataset from postmortem human Parkinson’s disease brain tissue⁵¹ ( Figure 1e, f ). Quantitative analysis of cell-type proportions revealed comparable representation of major cell types between miBrains with SNCA- A53T neurons and miBrains with control neurons ( Figure S1k ), indicating that neuronal α-Syn pathology does not induce large-scale shifts in overall cellular composition ( Figure 1g ). These findings suggest that the model preserves multicellular architecture while enabling the assessment of cell-type-specific transcriptional responses. Differential gene expression analysis of all cellular types showed that neurons have the highest number of differentially expressed genes (DEGs) in SNCA- A53T compared to control miBrains (153 upregulated, 149 downregulated, adjusted p 0.5, Figure 1h , I, Table S1 ), consistent with specific induction of SNCA -A53T in these cells. Gene ontology analysis revealed a significant upregulation of biological processes related to neuronal apoptosis, morphological changes, and synaptic changes ( Figure 1j , Table S2 ). Gene set enrichment analysis (GSEA) further showed significant modulation of gene sets associated with α-Syn pathology (P = 0.006), synaptic vesicle maturation (P = 0.004), and protein dephosphorylation (P = 0.02; Figure S1l ). Collectively, these transcriptional changes are consistent with neuronal dysfunction and responses to α-Syn pathogenic accumulation in SNCA- A53T miBrains. α-Syn inclusions in miBrain tissue exhibit pathological features of Lewy body-like inclusions To assess the pathological relevance of α-Syn inclusions formed in the miBrain tissue, we examined their association with cellular features commonly observed in or near Lewy body pathology in the human brain, including lipid droplets 51 , mitochondria 52 , and protein co-pathologies 53 – 56 such as amyloid-β and hyperphosphorylated tau. In SNCA- A53T miBrains, the neutral lipid marker Lipid Spot showed significant spatial overlap with both SNCA-A53T-sfGFP and phosphorylated α-Syn. Quantitative volumetric analysis demonstrated a significant increase in Lipid Spot and p-Syn co-localized in SNCA- A53T miBrains compared with control miBrains (p = 0.0006; Figure 2a ), consistent with prior reports describing lipid droplet-associated α-Syn-positive neurotoxic inclusions in human iPSC-derived neurons 29 . The volume of aggregated α-Syn overlapping with mitochondrial marker TOM20 in SNCA -A53T miBrains was significantly increased compared to control miBrains (p = 0.017, Figure S2a ), in agreement with studies demonstrating mitochondrial association of aggregated α-Syn + inclusions in the human Lewy Body pathology 57 . In addition, SNCA- A53T miBrains exhibited significantly increased amyloid-β-immunoreactivity (D54D2; p < 0.0001) and hyperphosphorylated tau (PHF1; total: p = 0.0021, Figure 2b ; somatodendritic: p = 0.0002, Figure S2b ) compared to controls, suggesting that miBrains can model co-pathological features commonly observed alongside α-Syn inclusion. Collectively, these data show that α-Syn-rich inclusions in the miBrain are co-associated with lipid, mitochondrial, and proteopathic characteristics of Lewy Body-related pathology, supporting the pathological relevance of this model system. Download figure Open in new tab Figure 2: α-Syn inclusions in miBrain tissue share pathological characteristics of Lewy bodies. a . Representative IF images of SNCA-A53T-sfGFP (green), α-Syn pS129 (red) and LipidSpot (magenta) in control or SNCA- A53T 18-days-old miBrains. Arrowhead in high magnification images points to a lipid droplet within a α-Syn pS129 inclusion. The volume of α-Syn pS129 and LipidSpot co-localization was normalized to control miBrains. Data represents mean ± SEM (n = 8 biological replicates). P-value was calculated by two-tailed, unpaired t-test. Scale bar: 50 µm (low magnification) and 10 µm (high magnification). b. Representative IF images of amyloid-β (D54D2; red), hyperphosphorylated tau (PHF1; cyan) and SNCA-A53T-sfGFP (green) in control and SNCA- A53T 18-days-old miBrains. D54D2 volume and somatic PHF1 were normalized by the number of Hoechst + nuclei (blue) and control miBrains. Data represents mean ± SEM (n = 6 biological replicates). P-values were calculated by two-tailed, unpaired t-tests. Scale bar: 50 µm. c. Representative images of live microscopy for SNCA-A53T-sfGFP (green) in cell bodies (i), neurites (ii), and varicose-like inclusions (iii). Number of somatic and neuritic inclusions overtime were normalized by sfGFP volume. Data represents mean ± SEM (n = 4 biological replicates). P-values were calculated by one-way ANOVA and Dunnett’s test. Scale bars: 25 µm (i, ii) and 15µm (iii). d. Representative IF images of miBrains with control or SNCA -A53T neurons after 2 weeks or 24 weeks in culture. TUJ1 (cyan) volume was normalized to control miBrains for each timepoint. Data represents mean ± SEM (n = 3-4 biological replicates). P-values were calculated by 2-way ANOVA and Fisher’s test. Scale bar: 50 µm. e. Representative IF images of SNCA -A53T miBrains stained for α-Syn pS129 (red) and aggregated α-Syn after 24 weeks in culture. SNCA-A53T-sfGFP (green) volume co-localized with α-Syn pS129 or aggregated α-Syn was measured in 2-week and 24-week miBrains and normalized to 2-week miBrains. Data represents mean ± SEM (n = 4-6 biological replicates). P-values were calculated by Mann-Whitney tests. Scale bar: 25 µm. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. The A53T neurons utilized in c-e were from the A53T-1A CORR28 line (donor with familial Parkinson’s disease). Lewy bodies are resistant to extraction with non-ionic detergents such as Triton X-100 and become solubilized only in stronger detergents such as SDS 58 . To determine whether α-Syn inclusions formed in the miBrain exhibit similar biochemical properties, we performed sequential detergent extraction of the neuronal lysates followed by Western blotting for total α-Syn and p-Syn. In control and SNCA -A53T 2D neurons, α-Syn was detected exclusively in the Triton-X-100 soluble fraction, with little to no signal in the SDS fraction. In contrast, the SNCA- A53T neurons with PFFs showed both total α-Syn and p-Syn in the SDS-soluble fraction in addition to the Triton-soluble pool ( Figure S2c ), demonstrating the presence of detergent-resistant aggregates in the SNCA -A53T neurons akin to Lewy Body pathology found in the human brain. These biochemical features are consistent with the detergent solubility profile of Lewy Body-associated proteins 29 . They are also concordant with immunostaining results using p-Syn antibodies in 2D neurons ( Figure S1f ), further supporting the specificity and the suitability of p-Syn staining as a biomarker for pathogenic α-Syn inclusions. Neuronal α-Syn inclusion pathology in the human brain manifests as multiple inclusion morphologies, including dense spherical Lewy Bodies, less dense “pale bodies”, and Lewy neurites with thread-like or varicose appearance 44 . Using longitudinal live imaging, we observed both somatic and neuritic SNCA-A53T-sfGFP inclusions in miBrain tissue ( Figure 2c i-iii ), spanning a range of morphologies resembling those described in human synucleinopathies. Over the first 12 weeks in culture, the number of somatic α-Syn inclusions in miBrains increased significantly (1.81 ± 0.09-fold; p < 0.0001), whereas the neuritic inclusion counts remained stable (p = 0.52; Figure 2c ), indicating preferential accumulation in neuronal cell bodies over time. Because α-Syn aggregation is associated with neuronal injury in vivo , we next assessed neurotoxicity in miBrains 59 , 60 . Soluble biomarkers of cell death (lactate dehydrogenase (LDH)) were significantly elevated in the media of SNCA- A53T miBrains compared with control miBrains (p = 0.026). In parallel, total sfGFP-labeled α-Syn volume significantly declined between weeks 2 and 22 (p < 0.0001, Figure S2d ), consistent with progressive cell loss. Neuronal content was likewise significantly reduced in SNCA- A53T compared to control miBrains, as measured by TUJ1-positive volume at both 2 weeks (p = 0.002) and 24 weeks (p = 0.007; Figure 2d ). Over this interval, the fraction of sfGFP signal co-localizing with pS129 α-Syn (p = 0.0095) and aggregated α-Syn (p = 0.0381) increased significantly ( Figure 2e ), consistent with increased aggregation of α-Syn over time. Collectively, these results demonstrate that miBrains phenocopy morphologically and biochemically complex neuronal α-Syn pathology that is accompanied by neuronal injury. APOE4 increases α-Syn phosphorylation and aggregation through non-cell autonomous mechanisms in miBrain tissue APOE4 is a genetic risk factor for α-Syn in LBD 14 and AD 61 , 62 , and is associated with increased disease severity across human studies, animal models 63 , 64 , and in vitro systems 65 . To investigate how APOE4 promotes α-Syn pathology, we used isogenic iPSC lines derived from an APOE3/3 donor and CRISPR-edited to APOE4/4 66 , 67 . In monocultures, APOE4/4 SNCA- A53T neurons exhibited comparable levels of p-Syn to isogenic APOE3/3 SNCA -A53T neurons, both with and without PFF exposure ( Figure S3a ), indicating no detectable neuronal cell-autonomous effects of APOE genotype under these conditions. We therefore hypothesized that APOE4 enhances α-Syn pathology through non-neuronal cell types. Using the same isogenic lines, we generated astrocytes, OPCs, endothelial cells, mural cells, and microglia, confirming comparable cell type-specific markers across APOE genotypes for each cell type ( Figure S3b ). We then assembled isogenic APOE3/3 and APOE4/4 miBrains containing APOE3/3 SNCA -A53T or APOE4/4 SNCA -A53T neurons respectively. Consistent with clinical studies, APOE4/4 miBrains displayed significantly increased neuronal p-Syn compared to APOE3/3 miBrains (p = 0.0016, Figure 3a ). The volume of p-Syn outside the sfGFP signal was also significantly increased in APOE4/4 miBrains (p = 0.0263, Figure S3c ), indicating enhanced phosphorylation of endogenous (non-A53T) α-Syn in the APOE4/4 miBrains compared to isogenic controls. To assess whether increased phosphorylation of α-Syn in the APOE4/4 miBrain is a direct cell-autonomous effect of APOE4/4 neurons, we generated miBrains that were all APOE4/4 except for APOE3/3 SNCA -A53T neurons. Strikingly, we observed a significant increase in p-Syn even when APOE3/3 SNCA -A53T neurons were placed in an otherwise APOE4/4 miBrain (p = 0.0001, Figure S3d ). These results demonstrate that APOE4/4 promotes neuronal α-Syn pathological phenotypes through non-cell autonomous mechanisms within a multicellular human brain-like tissue environment. Download figure Open in new tab Figure 3. APOE4 increases the phosphorylation and aggregation of α-Syn via astrocytes. a. Representative IF images of α-Syn pS129 (red) in isogenic APOE3/3 and APOE4/4 18-days-old miBrains, with SNCA-A53T-sfGFP (green) expressing neurons. α-Syn pS129 volume within SNCA-A53T-sfGFP neurons (green) was normalized to total SNCA-A53T-sfGFP volume and APOE3/3 miBrains. Data represent mean ± SEM (n = 8 biological replicates). P-value was calculated by a two-tailed, unpaired t-test. Scale bar: 50 µm (low magnification) and 25 µm (high magnification insets). b. Representative IF images of α-Syn pS129 (red) in APOE3/3, APOE4/4, and APOE3/3 with APOE4/4 astrocytes 18-days-old miBrains. APOE3/3 cells are represented by blue boxes, and APOE4/4 cells are represented by yellow boxes. Permutations were done for neurons, endothelial cells, mural cells, and OPCs, but IF images are not shown. miBrains did not include microglia. α-Syn pS129 volume within SNCA-A53T-sfGFP neurons (green) was normalized to total SNCA-A53T-sfGFP volume and APOE3/3 miBrains. Data represent mean ± SEM (n = 8 biological replicates). P-values were calculated by one-way ANOVA and Dunnett’s test. Scale bar: 50 µm. c. Representative IF images of GFAP (magenta) in APOE3/3 and APOE4/4 18-days-old miBrains. miBrains did not include microglia. Measured GFAP overlap with SNCA-A53T-sfGFP (green; left), circularity of GFAP cells (center), and GFAP volume normalized to APOE3/3 miBrains (right). Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by two-tailed, unpaired t-tests. Scale bar: 50 µm. d. Volcano plot illustrating DEGs in APOE4/4 vs. APOE3/3 astrocytes. Upregulated (red) and downregulated (blue) genes are defined by |log2 fold change| > 1.5 and p-value < 0.05. e. Gene set enrichment analysis (GSEA) plots showing enrichment of genes associated with inflammatory astrocytes, extracellular matrix remodeling, lipid droplet biogenesis, and α-synuclein pathology, in APOE4/4 astrocytes compared with APOE3/3 . *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 APOE4/4 astrocytes mediate increased α-Syn pathological phenotypes in miBrains Our results suggest that non-neuronal cell types are responsible for increased p-Syn in the APOE4/4 miBrains. Because microglia are implicated in α-Syn clearance 68 , 69 and have been reported to enhance tau hyperphosphorylation in APOE4 brain tissue 27 , we first examined whether microglia modulate α-Syn pathology in our system. In 2D monocultures, microglia exposed to conditioned media from SNCA- A53T neurons showed increased expression of activation and phagocytic markers, including IBA1 (p = 0.0553) and CD68 (p = 0.0122, Figure S3e ), consistent with microglial activation and phagocytic activity. However, inclusion of microglia in miBrains did not significantly alter p-Syn levels compared to miBrains without microglia for either APOE3/3 (p = 0.943) or APOE4/4 (p = 0.585) miBrains ( Figure S3f ). To further test microglial genotype effects, we replaced APOE3/3 microglia with APOE4/4 microglia in an otherwise APOE3/3 miBrain and observed no significant increase in α-Syn phosphorylation (p = 0.349; Figure S3g ) . Together, these results demonstrate that microglia, regardless of their APOE genotype, are not a major determinant of α-Syn phosphorylation in miBrains. To identify which APOE4/4 cell types promote increased α-Syn pathology, we generated a series of isogenic hybrid miBrains in which individual APOE3/3 cell types were selectively substituted with isogenic APOE4/4 counterparts ( Figure 3b ). Based on the results above ( Figure S3f-g ), microglia were excluded to reduce combinatorial complexity. Consistent with previous results ( Figure 3a ), all APOE4/4 miBrains had significantly increased p-Syn staining compared to isogenic all APOE3/3 miBrains (p = 0.0005). Replacement of APOE3/3 neurons, endothelial cells, mural cells, or OPCs with APOE4/4 isogenic cells did not significantly increase p-Syn levels in the miBrain ( Figure 3b ). In contrast, selective substitution of APOE4/4 astrocytes into an otherwise APOE3/3 miBrain was sufficient to significantly increase in p-Syn immunoreactivity (p = 0.0004), reaching levels comparable to APOE4/4 miBrains ( Figure 3b ). Collectively these results demonstrate that APOE4/4 astrocytes are responsible for increasing α-Syn pathology in APOE4/4 miBrain. Because astrocytes contribute to neuronal α-Syn uptake and degradation, we next examined astrocyte-α-Syn interactions 70 – 72 . Compared to isogenic APOE3/3 miBrains, in APOE4/4 miBrains GFAP-positive astrocytes showed significantly reduced spatial overlap with SNCA-A53T-sfGFP (p = 0.0348) and displayed a more amoeboid reactive morphology characterized by increased circularity (p = 0.0398) and elevated GFAP expression (p = 0.010 ( Figure 3c and Videos S2 and S3 ). snRNA-seq analysis of APOE3/3 and APOE4/4 miBrains showed that APOE4/4 astrocytes exhibit transcriptional alterations consistent with altered astrocytic α-Syn handling associated with increased reactivity ( Figure 3d ). In APOE4 /4 astrocytes the number of DEGs (1007 DEGs, adjusted p 0.5) was more than double that of APOE4/4 neurons harboring SNCA -A53G (420 DEGs) when compared to their APOE3/3 counterparts ( Table S1 ). GSEA of astrocytes showed altered expression of genes associated with inflammatory states (P = 0.03), matrisome (P = 0.0004), α-Syn pathology (P = 0.04), and lipid droplets biogenesis (P = 0.04) in APOE4/4 astrocytes ( Figure 3e , Table S2 ). These findings indicate that the APOE4/4 genotype promotes astrocyte activation consistent with astrogliosis and enhanced responses to α-Syn pathology and/or the miBrain environment. Collectively, these results demonstrate that astrocytes play a dominant non-cell-autonomous role in promoting neuronal α-Syn phosphorylation and aggregation in miBrains. APOE4/4 astrocytes exhibit impaired uptake and degradation of exogenous α-Syn To define the mechanisms by which APOE4/4 astrocytes increase the phosphorylation and aggregation of neuronal α-Syn, we first asked whether increased astrocytic SNCA expression contributes to the increased α-Syn burden in the APOE4/4 miBrain and human brain tissue. Analysis of single-nucleus transcriptomics data from post-mortem human brain 73 showed that SNCA mRNA is significantly reduced in astrocytes from APOE4 carriers ( APOE3/4 and APOE4/4 ) compared to control age-matched APOE3/3 individuals (p = 0.019; Figure 4a ). We observed a similar decrease in SNCA transcript levels in isogenic APOE4/4 versus APOE3/3 iPSC-derived astrocytes 66 (p = 0.017) ( Figure S4a ), indicating that transcriptional upregulation of SNCA in astrocytes is unlikely to account for increased α-Syn pathology in APOE4 contexts. In contrast, immunoblotting of astrocyte monocultures revealed increased total and phosphorylated α-Syn protein in APOE4/4 astrocytes compared with isogenic APOE3/3 astrocytes across two donors (Total α-Syn: Donor #1: p = 0.023; Donor #2: p= 0.043 and phosphorylated α-Syn; Donor #1: p = 0.0047; Donor #2: p = 0.0137; Figure 4b ; Figure S4b ) suggesting that post-translational mechanisms underlie increased α-Syn abundance in APOE4/4 astrocytes. Download figure Open in new tab Figure 4. Impaired lysosomal function of APOE4/4 astrocytes seeds α-Syn phosphorylation in neurons. a. Pseudobulk analysis of human astrocytes from Haney et al. 2024 for SNCA normalized gene count (TPM). Bars represent mean ± SEM (n = 8 APOE3/3 and n = 10 APOE4 carriers). P-value was calculated by a two-tailed, unpaired t-test. b Western blots of APOE3/3 and APOE4/4 astrocytes for total α-Syn protein and phosphorylated α-Syn protein. β-Actin was used as a loading control. Quantifications normalized to β-Actin and APOE3/3. Data represent mean ± SEM (n = 4 replicates). P-values were calculated by Welch’s one-tailed t-test c. Representative IF images of uptake and degradation of exogenous, fluorescently labeled α-Syn-HiLyte (green). α-Syn-HiLyte was removed from the culture media after 24 hours. α-Syn-HiLyte intensity was normalized by Hoechst (blue) area and APOE3/3 at the first time point. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. Scale bar = 50 µm. d. DQ-BSA Green mean fluorescence intensity measured in DAPI negative cell population by flow cytometry after 24 hours in two isogenic iPSC lines. Data represent mean ± SEM (n = 3-4 biological replicates). P-values were calculated by two-tailed, unpaired t-tests. e. Representative IF images of pS129 α-Syn (red) in APOE3/3 and APOE4/4 astrocytes after exposure to fresh or conditioned neuron media. pS129 α-Syn mean intensity was normalized to cell area (CD44; cyan) and APOE3/3 astrocytes exposed to fresh media. Data represent mean ± SEM (n = 6 biological replicates). P-values were calculated by 2-way ANOVA and Fisher’s LSD. Scale bar = 50 µm. f. Representative IF images of pS129 α-Syn (red) in SNCA -A53T neurons treated with neuron conditioned media (left) or neuron and astrocyte conditioned media from either APOE3/3 or APOE4/4 astrocytes (right). pS129 α-Syn volume was normalized to SNCA- A53T-sfGFP (green) volume and neuron-conditioned media samples. Data represent mean ± SEM (n = 5 biological samples). P-values were calculated by one-way ANOVA and Tukey’s test. Scale bar = 50 µm. g. Dot blots of SNCA -A53T neuron conditioned media or double conditioned media from SNCA-A53T neurons and isogenic APOE3/3 or APOE4/4 astrocytes for total αSyn, phosphorylated αSyn, and aggregated αSyn. All dots were on one blot; the image was cropped to fit the figure. Signal was normalized to protein concentration for each sample as measured by BCA assay. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Astrocytes have a well-described protective and homeostatic function of taking up and degrading neuronal α-Syn 70 – 72 . Given this role and our findings that APOE4/4 astrocytes increase neuronal α-Syn phosphorylation and co-localize less with SNCA-A53T-sfGFP in the miBrain ( Figure 3c ), we tested whether APOE4/4 astrocytes have impaired processing of exogenous α-Syn. Isogenic APOE3/3 and APOE4/4 astrocytes were exposed to fluorescently labeled α-Syn-HiLyte, and uptake and degradation were monitored by live imaging. APOE3/3 astrocytes showed rapid uptake of α-Syn with significant intracellular accumulation by 4.5 hours (p = 0.001) and 6 hours (p < 0.0001) ( Figure 4c ). In contrast, isogenic APOE4/4 astrocytes showed delayed uptake, with no detectable increase of α-Syn at 4.5 hours (p = 0.9997) and only a modest increase by 6 hours (p = 0.0006) ( Figure 4c ). To assess degradation, extracellular α-Syn was removed after 24 hours, and intracellular α-Syn-HiLyte signal was tracked for an additional 24 hours. APOE3/3 astrocytes showed a significant reduction in intracellular α-Syn-HiLyte signal (p < 0.0001), whereas APOE4/4 astrocytes showed no significant decrease (p = 0.694; Figure 4c ), indicating impaired degradation of α-Syn. Together, these results demonstrate that APOE4/4 astrocytes accumulate α-Syn protein despite lower SNCA transcript levels and exhibit defects in both uptake kinetics and intracellular clearance of exogenous α-Syn. APOE4/4 astrocytes exhibit impaired lysosomal proteolytic function Because intracellular protein turnover is primarily mediated by lysosomal and proteasomal pathways 74 , we next determined which pathway is responsible for α-Syn degradation in astrocytes. We treated the cells with the lysosomal inhibitor bafilomycinA1 or the proteasomal inhibitor MG-132 and monitored the degradation of fluorescent α-Syn-HiLyte. Lysosomal inhibition significantly blocked the degradation of α-Syn-HiLyte (p = 0.0241), whereas proteasomal inhibition had no significant effect (p = 0.079; Figure S4c ), consistent with prior reports that astrocytic α-Syn clearance occurs predominantly through the endolysosomal pathway 75 . These findings support a model in which impaired lysosomal function promotes α-Syn accumulation. We therefore tested whether APOE4/4 astrocytes exhibited endolysosomal dysfunction relative to isogenic APOE3/3 astrocytes. Lysosomal proteolytic capacity was assessed using DQ-BSA, a self-quenched substrate that fluoresces upon lysosomal cleavage. APOE4/4 astrocytes showed significantly reduced lysosomal DQ-BSA signal compared to isogenic control APOE3/3 astrocytes across two isogenic donor pairs (Donor #1: p= 0.0032; Donor #2: p < 0.0001, Figure 4d ), indicating decreased lysosomal proteolytic activity. Consistent with this, immunoreactivity for the lysosomal membrane protein LAMP1 was also significantly reduced in APOE4/4 astrocytes compared to isogenic APOE3/3 astrocytes (Donor #1: p = 0.0002 and Donor #2: p = 0.0001, Figure S4d ). To distinguish between reduced lysosomal number and reduced lysosomal function per organelle, we normalized DQ-BSA fluorescence to co-internalized dextran, which accumulates in the lysosomes but is resistant to proteolysis 76 . Even after dextran normalization, APOE4/4 astrocytes retained significantly lower proteolytic activity (p = 0.0098; Figure S4e ), indicating functional impairment rather than solely reduced lysosome abundance. As expected, bafilomycinA1 suppressed DQ-BSA cleavage in both APOE3/3 (p < 0.0001) and APOE4/4 astrocytes (p = 0.0174; Figure S4e ), confirming lysosome-dependent signal generation. Collectively, these results demonstrate that APOE4/4 astrocytes exhibit both reduced lysosomal mass and diminished lysosomal proteolytic function, providing a mechanistic basis for impaired lysosomal clearance of α-Syn. APOE4 astrocytes take up neuronal α-synuclein and release modified pathogenic seeds Since phosphorylated α-Syn is a key readout of α-Syn pathology, we next determined whether astrocytes can phosphorylate neuronal α-Syn. Therefore, we exposed Isogenic APOE3/3 and APOE4/4 astrocytes to fresh media or conditioned media from SNCA- A53T neurons. At baseline, APOE4/4 astrocytes exhibited higher endogenous p-Syn levels than APOE3/3 astrocytes ( Figure 4e ; p < 0.0001), consistent with our immunoblotting results ( Figure 4b ). APOE4/4 astrocytes incubated with media previously exposed to SNCA-A53T neurons for 3 days showed a further increase in p-Syn (p = 0.007) while APOE3/3 astrocytes were unaffected (p = 0.232) ( Figure 4e ), indicating that APOE4/4 astrocytes increase α-Syn phosphorylation. However, in the miBrain and post-mortem human brain, inclusions of α-Syn are primarily found inside neurons. We found that cell culture media collected from SNCA- A53T neurons and then inoculated onto fresh SNCA- A53T neuronal cultures itself does not increase phosphorylation of neuronal α-Syn ( Figure 4f ), suggesting that non-cell-autonomous mechanisms likely modify α-synuclein’s pathogenicity. Therefore, we hypothesized that APOE4/4 astrocytes fail to degrade α-Syn due to impaired endolysosomal function. Instead, APOE4/4 astrocytes phosphorylate α-Syn and release the more pathogenic forms of a-Syn into the extracellular space allowing them to be taken up by neurons and promote the formation of neuronal α-Syn inclusions. To test this hypothesis, we first exposed SNCA- A53T neurons to conditioned media from only APOE3/3 or APOE4/4 astrocytes. Astrocyte-conditioned media itself did not induce significant p-Syn in SNCA- A53T neurons, and no significant difference was observed between APOE3/3 and APOE4/4 conditioned media ( APOE3/3 : p = 0.9903; APOE4/4 : p = 0.9092; Figure S4f ). We reasoned the low levels of α-Syn produced by astrocytes alone is not sufficient to induce phosphorylation and aggregation of neuronal α-Syn. Therefore, we performed a double conditioned media experiment where conditioned media was first collected from SNCA- A53T neurons and subsequently cultured with either APOE3/3 or APOE4/4 astrocytes. This double-conditioned media was then collected and inoculated onto fresh SNCA- A53T neuron monocultures ( Figure 4f ). Neurons grown in APOE3/3 double-conditioned media did not show a significant increase in α-Syn phosphorylation (p = 0.601). In contrast, APOE4/4 double-conditioned media led to a 2.25-fold increase (± 0.30 SEM) in α-Syn phosphorylation (p < 0.0001, Figure 4f ). To assess whether the induction of p-Syn by APOE4/4 double-conditioned media was a failure of astrocytes to degrade α-Syn or a modification of α-Syn, we analyzed the α-Syn species in the double-conditioned media via dot blot. Although the total levels of α-Syn in the media were not different between APOE3/3 and APOE4/4 astrocytes (p = 0.999), p-Syn and aggregated α-Syn were both significantly increased (p = 0.0002 and p = 0.0232) in media conditioned by APOE4/4 astrocytes compared to APOE3/3 astrocytes ( Figure 4g ). APOE3/3 astrocyte double-conditioned media appeared not to change having similar p-Syn and aggregated α-Syn levels to the original SNCA -A53T media that was not conditioned by astrocytes (p = 0.971 and p = 0.999; Figure 4g ). To determine whether these pathogenic α-Syn species originated from astrocytic endogenous α-Syn or from neuronal-derived α-Syn processed by astrocytes, we generated APOE4/4 astrocytes with >90% SNCA knockdown using two independent shRNA constructs (shRNA#1: 94.25% ± 0.55 SEM knockdown efficiency; shRNA#2: 94.70% ± 1.5 SEM knockdown efficiency; Figure S4g ). SNCA knockdown in APOE4/4 astrocytes did not reduce the ability of double-conditioned media to induce neuronal p-Syn compared to control APOE4/4 astrocytes (no shRNA and scrambled shRNA; shRNA #1: p = 0.997, shRNA #2: p = 0.998; Figure S4h ). Collectively, these results indicate that APOE4/4 astrocytes do not contribute to pathology through the secretion of their endogenous α-Syn. Instead, APOE4/4 astrocytes take up neuronal-derived α-Syn, promote its pathogenic modification, and release seeding-competent α-Syn that promotes neuronal α-Syn inclusion formation. Cholesterol accumulation in APOE4/4 astrocytes leads to lysosomal dysfunction and pathogenic α-Syn processing We next investigated how APOE4 in astrocytes leads to lysosomal dysfunction and the spread of α-Syn pathogenic forms. In the brain, APOE is primarily expressed in astrocytes and regulates cholesterol transport to neurons to support membrane and synapse homeostasis 77 – 79 . APOE4 is associated with reduced lipid transport capacity 80 , cholesterol accumulation within astrocytic lysosomes, and impaired lysosomal function 67 , 81 . In agreement with previous reports, transcriptomic analysis of APOE4/4 astrocytes showed differential expression of genes (p < 0.05) involved in lipid storage and transport, as well as response to lipopolysaccharide and oxidative stress, which are associated with a neurotoxic reactive phenotype ( Figure S5a ) 67 , 82 , 83 . Consistent with altered lipid metabolism, APOE4/4 astrocytes showed significantly increased BODIPY-cholesterol accumulation compared to isogenic APOE3/3 astrocytes generated from two different individuals (Donor #1: p = 0.001; Donor #2: p = 0.002, Figure 5a ). Analysis of APOE4/4 astrocytes within miBrains by snRNA-seq indicate an enrichment of gene programs associated with lipid droplet biogenesis ( Figure 3e , Table S2 ). Download figure Open in new tab Figure 5. Reducing cholesterol improves APOE4/4 astrocyte lysosomal and α-Syn homeostasis. a. Representative IF images of live astrocytes with BODIPY-cholesterol (green) in two isogenic lines. BODIPY-cholesterol mean intensity was normalized to Hoechst (blue) area and APOE3/3 for each isogenic pair. Data represent mean ± SEM (n= 3 biological replicates). P-values were calculated by two-tailed, unpaired t-tests. Scale bar = 50 µm. b. Top: DQ-BSA Red integrated intensity, in astrocytes with 2HβCD, MβCD, atorvastatin, efavirenz, LXR-623, or T0901317 treatment, measured over 24 hours on an Incucyte (Sartorius). Data represent mean ± SEM (n = 4 biological replicates). Bottom: area under the curve calculation for DQ-BSA. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. c. Representative IF images of BODIPY (green) staining in astrocytes treated with 2HβCD or MβCD. BODIPY puncta were normalized to Hoechst (blue) count. Data represent mean ± SEM (n = 6 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. d. Representative IF images of LysoTracker (magenta) in astrocytes treated with 2HβCD or MβCD. LysoTracker mean intensity was normalized by Hoechst (blue) area and APOE3/3 astrocytes. Data represent mean ± SEM (n = 5-6 biological replicates). P-values were calculated by 2-way ANOVA and Sidak test. Scale bar = 50 µm. e. Representative IF images of astrocytes treated with cyclodextrins after a 24h incubation with fluorescently labeled α-Syn-HiLyte (green), in two isogenic lines. α-Syn-HiLyte intensity was normalized to Hoechst (blue) area and APOE3/3 astrocytes. Data represent mean ± SEM (n = 6 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. Scale bar = 50 µm. f. Representative IF images of pS129 α-Syn (red) in isogenic APOE3/3 , APOE4/4 , and APOE4/4 treated with MβCD miBrains. pS129 α-Syn volume within SNCA-A53T-sfGFP (green) normalized to total sfGFP volume and APOE3/3 18-days-old miBrains. Data represent mean ± SEM (n = 8 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. Scale bar = 50 µm. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Given the coexistence of cholesterol accumulation and lysosomal impairment, we hypothesized that excess intracellular cholesterol contributes to impaired degradation of α-Syn. We conducted a primary screen for improved lysosomal proteolytic activity, as measured by DQ-BSA cleavage, in APOE4/4 astrocytes treated with small molecules known to reduce cholesterol bioavailability. Treatment with 2-hydroxypropyl-β-cyclodextrin (2HβCD) and methyl-β-cyclodextrin (MβCD) significantly increased lysosomal proteolysis (2HβCD: p = 0.0002; MβCD: p = 0.019) ( Figure 5b ), whereas the other interventions had neutral or negative effects on APOE4/4 lysosomal proteolytic activity ( Figure 5b ). Treatment with cyclodextrins significantly decreased neutral lipids in APOE4/4 astrocytes as measured by BODIPY staining (2HβCD: p = 0.0013; MβCD: p = 0.0063) to levels comparable to APOE3/3 astrocytes ( Figure 5c ). Filipin staining additionally revealed a significant increase in endogenous free cholesterol in APOE4/4 astrocytes compared to APOE3/3 astrocytes, which was significantly reduced following MβCD treatment (p = 0.0167) to levels comparable to APOE3/3 astrocytes ( Figure S5b ). Increased lysosomal proteolytic activity with MβCD was replicated in astrocytes from a second donor (p = 0.0045; Figure S5c ). Consistent with improved lysosomal capacity, MβCD increased LysoTracker-positive lysosomal signal in APOE4/4 astrocytes (p = 0.044; Figure 5d ), with similar effects observed across donors (2HβCD: p < 0.0001 ; MβCD: p < 0.0001, Figure S5d ). We next tested whether cholesterol reduction improves astrocytic α-Syn processing. Cyclodextrin-treated APOE4/4 astrocytes showed significantly increased uptake of α-Syn-HiLyte at 24 hours (2HβCD: p = 0.0009; MβCD: p = 0.0001) compared to vehicle-treated APOE4/4 astrocytes ( Figure 5e ). This effect was replicated in isogenic astrocytes from a second individual (2HβCD: p = 0.0002; MβCD: p = 0.0001) ( Figure S5e ). To validate that the α-Syn was being endocytosed into the endolysosomal pathway, we incubated astrocytes with α-Syn-HiLyte for 4 hours and co-stained with LysoTracker. In agreement with our other findings that APOE4/4 astrocytes have impaired α-Syn uptake, the percentage of α-Syn-HiLyte that co-localized with LysoTracker decreased in APOE4/4 astrocytes compared to APOE3/3 astrocytes (p = 0.0395; Figure S5f ). However, APOE4/4 astrocytes treated with MβCD showed increased colocalization of α-Syn-HiLyte with LysoTracker compared to vehicle-treated APOE4/4 astrocytes (p = 0.0343). Strikingly APOE4/4 astrocytes treated with MβCD showed similar α-Syn lysosomal localization as vehicle-treated APOE3/ 3 astrocytes (p = 0.946; Figure S5f ). Taken together, these results indicate that intracellular cholesterol accumulation impairs lysosomal uptake and degradation of α-Syn in APOE4/4 astrocytes and that extracting cholesterol with cyclodextrin restores these functions. Our findings implicate astrocytes as a critical cell type in α-Syn processing in the genetic context of APOE4. However, α-Syn pathology in Lewy body diseases is characterized by inclusions found within neuronal projections and soma. To investigate whether improved lysosomal activity in cyclodextrin-treated astrocytes affected neuronal α-Syn phosphorylation, we returned to the miBrain model. After 7 days of treatment with MβCD, the levels of neuronal phosphorylated α-Syn were significantly reduced in MβCD-treated APOE4/4 miBrains (p = 0.0172) when compared to untreated APOE4/4 miBrains and restored phosphorylation to levels that were not statistically different from APOE3/3 miBrains (p = 0.059) ( Figure 5f ). These results show that MβCD treatment reduces α-Syn phosphorylation in neurons, likely via restoration of lysosomal activity and α-Syn processing in astrocytes, alleviating cells of the cytotoxic burden of α-Syn aggregation. This may open a therapeutic avenue for cholesterol-lowering pharmacological interventions in the treatment of synucleinopathies and Alzheimer’s disease with Lewy Bodies, particularly in APOE4 carriers. Discussion By combining stem cell and genetic engineering, we extended the miBrain platform 27 , 84 to model α-Syn pathological phenotypes and dissect disease-relevant cellular and molecular mechanisms in an iPSC-derived human brain-like tissue. Multicellular miBrains containing neurons, glia, and vascular cells developed progressive α-Syn phosphorylation, aggregation, and neuronal loss over weeks to months in culture. Single-nucleus RNA sequencing of miBrains confirmed the presence of diverse neuronal, glial, and vascular populations and revealed coordinated, cell-type-specific transcriptional responses to α-Syn pathology. These included alterations in neuronal gene programs related to apoptosis and synaptic function, as well as astrocyte-associated signatures of reactivity, extracellular matrix remodeling, and lipid dysregulation. Cryopreservation of pre-assembled tissue improved reproducibility and reduced batch variability, enabling complex combinatorial genetic and cell-type-specific perturbations. Using an isogenic mix-and-match replacement strategy unique to this system, we identified astrocytes as the principal mediators of APOE4-dependent neuronal α-Syn pathology. Our results support a mechanistic model in which APOE4-induced cholesterol accumulation impairs astrocytic endolysosomal function, disrupts α-Syn, and promotes the release of pathogenic α-Syn species that enhance neuronal aggregation and phosphorylation. Pharmacologically promoting cholesterol efflux restored astrocytic lysosomal function and reduced neuronal p-Syn burden in miBrains. Together, these results establish a causal link between cholesterol dysregulation in APOE4/4 astrocytes and α-Syn pathology with translational implications for synucleinopathies and AD with Lewy Bodies. Cholesterol is tightly regulated under physiological conditions, balancing uptake, synthesis, storage and efflux 85 . APOE4/4 astrocytes have been repeatedly linked to impaired lipid transport, reduced cholesterol efflux 67 , and lysosomal cholesterol acculmulation 66 , 81 , 86 , 87 . Consistent with these reports, we observed both neutral lipids, which includes cholesteryl esters and triglycerides, and free cholesterol increase in APOE4/4 astrocytes, in agreement with recent lipidomic analyses of the human AD brain reporting increased cholesteryl ester content and reactivity in APOE4 astrocytes 88 . Interestingly, cholesterol accumulation within APOE4/4 astrocytes has been associated with endolysosomal dysfunction 81 , which is aligned with our findings of reduced lysosomal pool and function in APOE4/4 astrocytes. We speculate that, in APOE4/4 astrocytes, a reduced transfer of cholesterol from late endosomes/lysosomes to downstream compartments such as the endoplasmic reticulum and plasma membrane would favor sequestration of free cholesterol within the endolysosomal system and promote secondary accumulation of esterified cholesterol and other neutral lipids into lipid droplets. Excess free cholesterol interferes with lysosomal membrane composition and function and impairs proteolysis 89 , 90 , while cholesteryl ester accumulation reflects impaired sterol mobilization and export 91 , 92 . Our data showing reduced lysosomal proteolytic capacity and decreased LAMP1 signal in APOE4/4 astrocytes are consistent with this framework. Indeed, cyclodextrins reduced intracellular lipid burden, increased lysosomal proteolytic activity, and restored delivery and degradation of α-Syn. Collectively, these findings support a mechanistic model that cholesterol trafficking defects are an upstream mediator of astrocytic lysosomal dysfunction. Astrocytes normally contribute to extracellular α-Syn clearance through uptake and degradation of neuron-derived protein. We show that APOE4/4 astrocytes instead shift towards pathological α-Syn handling: they incompletely degrade internalized α-Syn, promote its pathogenic modification, and re-secrete aggregation-competent species associated with enhanced neuron seeding. While neuronal secretion and astrocytic uptake of α-Syn have been described previously 70 – 72 , 93 , the conversion and release of pathogenic α-Syn species by dysfunctional astrocytes has not, to our knowledge, been directly demonstrated. Cholesterol accumulation has been linked to increased extracellular vesicle and exosome release in other cell types 94 , raising the possibility that lipid-loaded APOE4/4 astrocytes adopt a secretory inflammatory state marked by increased cytokines that may contribute to α-Syn propagation. This is consistent with the inflammatory and morphogenic transcriptional signatures we identified in APOE4/4 astrocytes by snRNA-seq. Defining the precise carriers and conformations of astrocyte-released α-Syn species will be an important direction for future work. Beyond effects on intracellular trafficking and degradation, cholesterol and other lipid environments can directly influence α-Syn phenotypes upstream of phosphorylation and aggregation 95 , 96 . Membrane and lipid-surface interactions are central to α-synuclein physiology but can also promote misfolding and aggregation upstream of phosphorylation 97 – 101 , which itself is not exclusively pathological 102 . Lysosomal lipid imbalance is a convergent feature across several genetic synucleinopathies, including disorders involving GBA1 , NPC1 , and LRRK2 , where disrupted lipid metabolism impairs α-Syn clearance and promotes aggregation-prone species 103 – 107 . Our findings place APOE4/4 astrocytes within this broader lipid-lysosome-α-Syn axis, identifying cholesterol trafficking defects as a mechanism that shifts astrocytic α-Syn processing from degradation to secretory and pathogenic. Therapeutically, we show that pharmacological reduction of intracellular cholesterol with methyl-β-cyclodextrin reduces neuronal α-Syn phosphorylation in APOE4/4 miBrain tissue, linking correction of astrocytic lipid imbalance to downstream neuronal benefit. Cyclodextrins are currently under clinical investigation for Neimann-Pick Type C (NPC), a devastating juvenile neurodegenerative disorder caused by lysosomal cholesterol accumulation. Early trials suggest symptomatic benefits of cyclodextrin with manageable toxicity 108 . More broadly, cholesterol-lowering strategies such as statins have shown mixed results in synucleinopathy models and clinical studies 109 , 110 . Our results suggest that APOE genotype and cell-type-specific cholesterol handling may influence therapeutic responsiveness, raising the possibility that genetically stratified lipid-targeting therapies could be more effective. This study also highlights the value of engineered human multicellular brain tissues for mechanistic dissection of non-cell-autonomous neurodegenerative processes. The miBrain platform enables patient-derived modeling, cell-type-specific CRISPR-based editing and allele control, and genetic mixing within a reproducible, cryopreservable, brain tissue context, features that are difficult to achieve in self-organizing organoids or animal models. We applied the miBrain platform to dissect cell-specific mechanisms of α-Syn pathology in APOE4 carriers. Collectively, our findings demonstrate that APOE4/4 astrocytes are sufficient to promote pathogenic α-Syn accumulation in miBrain tissue, linking astrocytic cholesterol dysregulation to pathogenic modification and propagation of neuronal α-Syn. Limitations of the Study While miBrains represent a novel multicellular tissue platform with user-defined cell composition, some cellular types like oligodendroglia progenitors still might retain lineage plasticity, resulting in unintended differentiation upon different experimental conditions. The SNCA-A53T expression system utilized here may not fully recapitulate Lewy pathology. While we identify lipid accumulation and lysosomal dysfunction as central features of APOE4/4 astrocytes, the precise lipid species and subcellular pools responsible for dysfunction remain to be identified. Lipidomics, targeted metabolomics, and organelle-enriched analysis will be required to resolve compartment-specific lipid alterations in APOE4/4 astrocytes and their contributions to α-Syn pathogenic conversion. While our results suggest that astrocytes modify α-Syn, the engagement of astrocytic kinases, the relative contribution of additional astrocyte-derived factors, and the persistence of non-astrocytic pathogenic α-Syn were not resolved in this study. Targeted immunodepleting of α-Syn and kinase perturbation approaches can help elucidate the mechanisms through which APOE4/4 astrocytes lead to accumulation of pathogenic α-Syn. Additionally, while microglia and other cell types did not substantially modify the α-Syn phenotypes examined here, they may influence pathological features or treatment responses. Continued refinement of the miBrain system, including multicellular functional validation, vascular perfusion and in vivo validation of pharmacological treatments will further expand its utility for modeling human neurodegeneration and accelerating therapeutic discovery. Author Contributions Conceptualization: L.A.M.L, C.G., and J.W.B.; Methodology: L.A.M.L., C.G., S.G, A.B., D.K, A.H., E.R.S., A.N., J.F.F., E.H., A.U., B.R.S., R.B.R., J.B., J.J.B.C..; Analysis: L.A.M.L., C.G., S.G., A.B., D.K., D.L., J.B., J.J.B.C, P.R..; Writing – Original Draft: L.A.M.L and C.G.; Writing – Review & Editing: L.A.M.L., C.G., J.W.B., A.B., A.H., A.N., D.L., J.B., J.J.B.C., J.F.F, and V.K; Supervision: J.W.B.; Funding Acquisition: J.W.B. Declaration of Interests J.W.B is Co-founder and senior advisor of MCM6 Therapeutic. V.K. is a cofounder of and senior advisor to DaCapo Brainscience and Yumanity Therapeutics, companies focused on CNS diseases. L.A.M.L, J.W.B., C.G., A.B., and R.B.R. are inventors on patent applications filed by Mount Sinai Innovation Partners on the methods described in this study. A.N. and V.K. are inventors on a patent application filed by Brigham and Women’s Hospital related to the induced inclusion iPSC models. Methods Key Resources Table View this table: View inline View popup Resource availability Lead Contact Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Dr. Joel W. Blanchard ( joel.blanchard{at}mssm.edu ). Material availability This study did not generate new, unique reagents Data and code availability All raw data will be made available on Mendeley upon paper acceptance and will be made publicly available. Original code relating to snRNAseq analysis and scRNAseq pseudobulk analysis will be made available on Mendeley upon paper acceptance and will be publicly available. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request. Human iPSC cultures All human iPSCs were maintained in feeder-free conditions in StemFlex TM medium (Gibco) on Geltrex TM Matrix (Thermo Fisher Scientific) pre-coated plates. All iPSC lines used in this study are listed in the Key Resource Table. Isogenic APOE3/3 and APOE4/4 pairs were generated previously via CRISPR/Cas9 66 . Human iPSCs were grown as colonies in StemFlex TM medium until they reached 60-70% confluency. At this point, iPSCs were either passaged for maintenance using 0.5 mM EDTA to gently lift colonies or harvested using Accutase TM cell detachment solution for 5-10 minutes at 37°C to start a differentiation protocol as singularized cells. A total of four donor cell lines were used in this study (see Key Resources Table). For all figures where the donor number is not indicated, we have used Donor 1 (AG09173 iPSCs). Donor 2 corresponds to KOLF2.1J iPSCs and donor 3 to ADRC5 iPSCs. The cell line A53T-1A CORR28 was obtained from a patient harboring the SNCA A53>T mutation, which was mutation-corrected, and then received the plasmid for overexpression of SNCA-A53>T. This strategy was used to introduce the mutation on SNCA at overexpressed levels while keeping the rest of the patient’s “synucleinopathy-permissive” genetic background. This line was kindly provided by Dr. Vikhram Khurana after extensive characterization 29 , 111 , and its use is indicated in the methods section and figure legends. Differentiation of human iPSCs into neurons Neuron differentiation was adapted from Zhang et al . 30 and Lam et al . 29 . Briefly, iPSCs were transfected with PiggyBac plasmids to confer doxycycline-inducible expression of the Neurogenin-2 gene ( NGN2 , Addgene Plasmid #209077) alone or in combination with SNCA-A53T-sfGFP (Addgene Plasmid: 209080) or A53T-ΔNAC-SNCA-sfGFP (Addgene Plasmid: 209081), using Lipofectamine TM Stem Transfection Reagent. Briefly, dissociated iPSCs were plated at ∼104,000 cells/cm 2 onto Geltrex TM -coated plates, in StemFlex™ supplemented with 10 µM Y27632 and 5 µg/mL doxycycline (day 0). At day 1, medium was replaced with Neurobasal N2B27 medium (Neurobasal, 1x B-27, 1x N-2, 1x MEM-NEAA, 1x GlutaMAX, 1% penicillin-streptomycin) supplemented with 10 µM SB431542, 100 nM LDN, 5 µg/mL doxycycline, and 5 µg/mL Blasticidin. On day 2, the medium was replaced with Neurobasal N2B27 media supplemented with 10 µM SB431542, 100 nM LDN, 5 µg/mL doxycycline, and 1 µg/mL puromycin. On days 3-6, the medium was replaced daily with Neurobasal N2B27 media supplemented with 5 µg/mL doxycycline and 1 µg/mL puromycin. At day 7, cells were dissociated with Accutase and either seeded into miBrains (see below) or seeded into 2D monocultures on Poly-L-Ornithine and laminin pre-coated plates at 156,250 cells/cm 2 , in Neurobasal N2B27 with 5 µg/mL doxycycline and 10 µM Y27632. For 2D cultures, on day 8, wells were gently topped with Neurobasal N2B27 supplemented with 20 ng/mL BDNF, 20 ng/mL GDNF, 1 mM dcAMP, 2 µg/mL laminin, and 1 µM AraC, using the same volume of medium in the wells. At day 11, media is replaced with Neurobasal N2B27 supplemented with 10 ng/mL BDNF, 10 ng/mL GDNF, 0.5 mM dcAMP, and 1 µg/mL laminin. This medium was used for half-media changes every 3-4 days. Differentiation of human iPSCs into astrocytes Astrocytes were generated using previously published protocols for iPSC-derived NPC (Chambers et al .) 31 and astrocyte (TCW et al .) 32 differentiations. Briefly, dissociated iPSCs were plated at 100,000 cells/cm 2 onto Geltrex TM -coated plates, in pre-warmed StemFlex™ supplemented with 10 µM Y27632. Cells were fed every other day with StemFlex™ until they reached >95% confluence. Once cells reached confluence, the medium was replaced with NPC medium (1:1 DMEM/F12: Neurobasal Medium, 1x N-2 Supplement, 1x B-27 Serum-Free supplement, 1x GlutaMAX Supplement, 1x MEM-NEAA, 1% penicillin-streptomycin) supplemented with 10 µM SB43152 and 100 nM LDN193189 (day 0). From days 1 to 9, cells were fed daily with NPC medium plus 10 µM SB43152 and 100 nM LDN193189. At day 10, cells were split with Accutase and replated onto fresh Geltrex TM -coated plates, in NPC media supplemented with 20 ng/mL bFGF and 10 µM Y27632. From days 11 to 13, cells were fed with NPC media plus 20 ng/mL bFGF. At day 14, cells were split with Accutase and re-seed onto fresh Geltrex TM -coated plates, in NPC media plus 20 ng/mL bFGF and 10 µM Y27632. Starting from day 15, cells were fed every 2-3 days with Astrocyte Medium (AM, ScienCell) and passaged using Accutase once they reached 90% confluence. From this point, NPCs were fully differentiated into astrocytes in 30 days. NPCs and fully differentiated astrocytes were cryopreserved in a freezing medium consisting of 90% knockout serum replacement (KSR) and 10% dimethyl sulfoxide (DMSO). Differentiation of human iPSC into brain microvascular endothelial cells Brain endothelial cell differentiation was adapted from the protocols from Blanchard et al. , Qian et al., and Wang et al . 33 , 36 , 112 . Briefly, iPSCs were transfected with a PiggyBac plasmid to confer doxycycline-inducible expression of the ETS variant transcription factor 2 ( ETV2 , Addgene Plasmid #168805), using Lipofectamine TM Stem Transfection Reagent. Inducible ETV2-iPSCs were grown until 60-70% confluency, dissociated with Accutase, and plated at 20,800 cells/cm 2 onto Geltrex TM -coated plates in StemFlex™ supplemented with 10 µM Y27632 (day 0). On day 1, the medium was replaced with DeSR1 medium (DMEM/F12 with GlutaMAX, 1× MEM-NEAA, 1× penicillin-streptomycin) supplemented with 10 ng/mL BMP4, 6 µM CHIR99021, and 5 µg/mL doxycycline. On day 3, the medium was replaced with DeSR2 medium (DeSR1 media, 1x N-2, 1× B-27) supplemented with 5 µg/mL doxycycline. At days 5 and 7, the medium was replaced with hECSR medium (Human Endothelial Serum-free Medium, Gibco, 1× MEM-NEAA, 1× B-27, 1% penicillin-streptomycin) supplemented with 50 ng/mL VEGF-A, 2 μM Forskolin, and 5 µg/mL doxycycline. At day 8, cells were dissociated using Accutase and re-seed onto fresh Geltrex TM -coated plates in hECSR supplemented with 50 ng/mL VEGF-A and 5 µg/mL doxycycline. This medium was used for every 2-3 days medium change to maintain cells for up to 1 week until ready for tissue assembly (miBrain or JAMs). Differentiation of human iPSCs into mural cells Mural cells were differentiated using previously published protocol from Patsch et al. 37 . Dissociated iPSCs were plated at 37,000 to 40,000 cells/cm 2 onto Geltrex TM -coated plates, in StemFlex™ supplemented with 10 µM Y27632 (day 0). On day 1, the medium was replaced with N2B27 medium (1:1 DMEM/F12: Neurobasal media, 1x B-27, 1x N-2, 1x MEM-NEAA, 1x GlutaMAX, 1% penicillin-streptomycin) supplemented with 25 ng/mL BMP4 and 8 μM CHIR99021. At days 3 and 4, the medium was replaced with N2B27 media supplemented with 10 ng/mL Activin A and 10 ng/mL PDGF-BB. At day 5, mural cells were dissociated with Accutase and re-seeded onto fresh 0.1% gelatin-coated plates at 35,000 cells/cm 2 , in N2B27 supplemented with 10 ng/mL PDGF-BB. This medium was used every 2-3 days medium was change for another 5–7 days. Cells were then banked in freezing medium (90% KSR/ 10% DMSO) and expanded in N2B27 until ready for tissue assembly (miBrain or JAMs). Differentiation of human iPSCs into oligodendrocyte progenitor cells (OPCs) OPC differentiation was adapted from Douvaras et al, 2014 113 . Briefly, iPSCs were dissociated into single cells using Accutase and seeded at near-confluent density. Differentiation began the next day (designated as day 0) by culturing the cells in DMEM/F12 (1:1) medium supplemented with N2, 10 μM SB431542, 100 nM LDN 193189, and 100 nM all-trans retinoic acid (RA), with daily medium changes. On day 8, 1 μM SAG was added to the differentiation medium. By day 12, adherent cells were detached and transferred to low-attachment plates to form cell spheres. These spheres were cultured in DMEM/F12 (1:1) medium containing N2, RA, and SAG. On day 30, spheres were plated onto poly-L-ornithine/laminin-coated plates to allow cells to migrate outward. At this stage, the medium was replaced with DMEM/F12 (1:1) supplemented with N2, B27, 10 ng/ml PDGF-AA, 10 ng/ml IGF, 5 ng/ml HGF, 10 ng/ml NT3, 25 μg/ml insulin, 100 ng/ml biotin, 1 μM cAMP, and 60 ng/ml T3. By day 75, cells were harvested, dissociated, and purified using NG2-specific magnetic-activated cell sorting (MACS). The enriched cells were expanded in DMEM/F12 (1:1) medium supplemented with N2, B27 without Vitamin A, 10 ng/ml PDGF-AA, 10 ng/ml β-FGF, and 10 ng/ml NT3 until ready for tissue assembly (miBrain or JAMs). Differentiation of human iPSCs into microglia iPSC-derived microglia were differentiated as previously shown 39 , 114 via an intermediate differentiation step into hematopoietic progenitor cells (HPCs). For the generation of HPCs, the STEMdiff Hematopoietic Kit was used, according to the manufacturer’s manual. Briefly, when 70% confluent (day 0), iPSCs were harvested and passaged at a density of 20-40 colonies per well in a 6-well coated with 0.1mg/mL Matrigel. On day 1, Medium A was added to the culture, and on day 4, it was switched to Medium B until complete HPC maturation on days 11-13. Fully differentiated HPCs, floating in the medium and detached from the colonies, were collected for microglial differentiation or frozen in Stem-CellBanker supplemented with microglial cytokines. For the generation of mature microglia, differentiated HPCs were collected and transferred into Matrigel coated 6-well plate at a confluency of 350k HPCs per well. The differentiation takes 25-28 days, during which HPCs are cultured in microglia media consisting of DMEM/F12, with 2X B27, 0.5X N2, 1X Glutamax, 1X non-essential amino acids, 400 mM Monothioglycerol, and 5 ug/mL human insulin, freshly supplemented with 100 ng/mL IL-34, 50 ng/mL TGFβ1, and 25 ng/mL M-CSF. Microglia were added to miBrains within the pool of Geltrex encapsulated cells at the time of miBrain assembly. MiBrains were maintained in miBrain media supplemented with 100 ng/mL IL-34 and 25 ng/mL M-CSF for 1 week and then switched to miBrain media supplemented with 25 ng/mL M-CSF until downstream experiments. 3D Tissue Assembly for miBrains Neurons, astrocytes, endothelial cells, mural cells, and OPCs were dissociated using Accutase or TryplE Select (astrocytes). Cells were resuspended in corresponding media, counted, and resuspended at 1 x 10 6 cells/ mL. For miBrains, a tube was prepared to contain 5 x 10 6 neurons, 5 x 10 6 endothelial cells, 1 x 10 6 astrocytes, 1 x 10 6 OPCs, and 1 x 10 6 mural cells per 1mL of miBrain. Microglia were added for a subset of miBrains (indicated in the figure legends) at a ratio of 1.67 x 10 6 per 1 mL. Pooled cells were spun down at 200 x g for 5 min at RT. Media was aspirated carefully, leaving the cell pellet undisturbed. The cell pellet was placed on ice and resuspended in 1 mL Geltrex TM supplemented with 10 µM Y27632 and 5 µg/mL doxycycline, avoiding air bubbles and keeping it on ice to prevent premature Geltrex polymerization and inability to seed miBrains properly. To generate miBrain tissue that adopted a free-floating, organoid-like morphology over time, 25-50 µL of encapsulated cell suspension were seeded per inner glass-bottom well of a 48-well MatTek plate (MatTek). To generate miBrain tissue that remained attached to the plate (more suitable for automated imaging) while conserving 3D morphology, 10 µL of encapsulated cell suspension were seeded per well of a 96-well µClear plastic-bottom plate (Greiner). After miBrains were seeded, the plates were transferred into a 37 °C 95%/5% Air/CO2 incubator for 30 minutes to allow the Geltrex TM to polymerize. After polymerization of the gel, miBrain week-1 medium (Human Endothelial Serum-free Medium, 1x Pen/Strep, 1X MEM-NEAA, 1X CD Lipids, 1x Astrocyte Growth Supplement (ScienCell), 1x B27 Supplement, 10µg/mL Insulin, 1µM cAMP-dibutyl, 50µg/mL ascorbic acid, 10ng/mL NT3, 10ng/mL IGF, 100ng/mL biotin, 60 ng/mL T3, 50 ng/mL VEGF, 1µM SAG, 5 µg/mL doxycycline) was added to each well, ensuring complete submersion of the culture in media (250-500uL per well of a 48-well matTek plate, 100 to 200 uL per well of a 96-well plate). Half media was changed every 2-3 days. On day 8 after miBrain seeding, the media was changed to miBrain week-2 medium (Human Endothelial Serum-free Medium, 1x Pen/Strep, 1X MEM-NEAA, 1X CD Lipids, 1x Astrocyte Growth Supplement (ScienCell), 1x B27 Supplement, 10µg/mL Insulin, 1µM cAMP-dibutyl, 50µg/mL ascorbic acid, 10ng/mL NT3, 10ng/mL IGF, 100ng/mL biotin, 60 ng/mL T3, 5 µg/mL doxycycline). Cultures were used for downstream assays after 18 days, unless otherwise indicated. Cryopreservation of miBrains For JAMs assembly and cryopreservation, a tube containing 5 x 10 6 endothelial cells, 1 x 10 6 astrocytes, 1 x 10 6 OPCs, and 1 x 10 6 mural cells per 1 mL was prepared. Pooled cells were spun down at 200 x g for 5 min at RT and cryopreserved in miBrain freezing media (60% KSR, 30% hECSR medium, 10% DMSO, 10 µM Y27632, 50 ng/mL VEGF-A). Upon thaw, cell viability was assessed, and the appropriate volume of neurons needed to conserve the original miBrain cell-to-cell ratio was added to the pooled cell suspension, which was spun again, encapsulated, and seeded as described above. Basal electrophysiological activity in miBrains To functionally validate the neuronal networks within miBrains, we performed microelectrode array (MEA) recordings under basal conditions. Basal electrophysiological activity of miBrains was assessed, as described previously 115 , with minor modifications, using 48-well CytoView MEA plates containing 16 electrodes per well. Briefly, plates were pre-coated with 0.1% polyethylenimine in borate buffer, rinsed, air-dried overnight, and coated with 20 µg/ml laminin immediately before use. Individual miBrains were transferred to coated MEA wells and allowed to settle for 24 h before recording. Spontaneous extracellular activity was recorded at 37 °C using a Maestro Pro MEA system and AxIS Spontaneous Neural configuration. Spikes were detected using an adaptive threshold set to 5X the standard deviation of the estimated noise per electrode. Electrodes detecting ≥5 spikes/min were classified as active, and network bursts were defined as events containing ≥5 spikes with inter-spike intervals <100 ms occurring in at least 20% of active electrodes; synchrony index was calculated using a 20 ms cross-correlogram window. Mean firing rate, burst parameters, network burst frequency, and synchrony index, among other parameters, were quantified using Neural Metric Tool (Axion Biosystems), and brightfield images were acquired to assess electrode coverage by miBrains organoids. Exposure of tissue to exogenous α-Synuclein miBrains were exposed to 4 µg/ml of Human Recombinant Alpha Synuclein Protein Aggregates (Pre Formed Fibrils, PFFs, from StressMarq, #SPR-322, or Abcam, #ab218819) or 4 µg/mL patient-derived PFFs (gift from Vik Khurana). PFFs were sonicated in a water bath (VWR Ultrasonic Cleaner) immediately before adding to the cultures, using 10 cycles of 30 sec on and 30 sec off. Free-floating miBrains incubated with α-Syn had a media change after 48h and were fixed in 4% paraformaldehyde after 2 weeks. Induction of α-Syn pathology via expression of SNCA-A53T Neurons with inducible expression of SNCA with the A53>T mutation (A53T) were generated from iPSC as described above. Cells were harvested on day 7 of the differentiation and cultured in 2D on Poly-L-Ornithine and laminin pre-coated plates at 156,250 cells/cm 2 ,or encapsulated for 3D cultures in Geltrex™ at 50,000 cells for 10 µL of Geltrex™, or added to JAMs for miBrain assembly as described above. The cultures were maintained for 18 days with or without PFFs. For the cultures that received PFFs, 4 µg/ml PFFs (gift from Vik Khurana) were added to the media on day 4 after assembly. The media was half-changed every 2-3 days. Immunofluorescence 2D cultures were fixed in 4% paraformaldehyde for 15 min at room temperature and rinsed with PBS. 2D cultures (non-neuronal) were blocked in 0.3% Triton-X100, 5% normal donkey serum in PBS for 30 min., and then with primary antibodies diluted in blocking buffer overnight at 4°C. Cultures were rinsed 3 times with 0.3% Triton-X100 in PBS for 15 min each, and incubated with secondary antibodies (and Hoechst 33342) diluted at 1:1000 in blocking buffer for 2h at room temperature. Cultures were rinsed 3 times with PBS for 15 minutes and left in PBS for image acquisition. 2D neuronal cultures were blocked in 0.1% Triton-X100, and 10% normal donkey serum in PBS, antibodies were diluted in 0.02% Triton-X100 and 2% normal donkey serum in PBS, and washes were done with PBS. All other conditions were kept the same as the other cell types. 3D cultures and miBrains were fixed in 4% paraformaldehyde overnight at 4°C and rinsed with PBS. 3D cultures and miBrains were incubated in blocking solution (0.3% Triton-X100, 5% normal donkey serum, in PBS) overnight at 4°C and then with primary antibodies diluted in blocking solution for 2-3 nights at 4°C. All antibodies were diluted at 1:500 except for α-Synuclein pS129 (EP1536Y) which was diluted at 1:300. Cultures were rinsed 5 times with 0.3% Triton-X100 PBS for 30 min each and incubated with secondary antibodies and Hoechst 33342 (Thermo 62249) diluted at 1:1000 in blocking solution for 2-3 nights at 4°C. Cultures were rinsed 5 times with 0.3% Triton-X100 PBS for 30 min each then rinsed and left in PBS for image acquisition. Image acquisition and quantification Images were acquired using a confocal microscope (Leica Stellaris, Nikon AX R, or Thermo Scientific CellInsight CX7). For quantification, single optical sections or 10-20 μm Z-stack images were acquired at 10x or 20x, 4-8 fields per sample. Area, Intensity or Volume measurements on single images or Z-stacks were performed using Nikon AX R built-in quantification software, ImageJ, or CellProfiler. Statistical analyses were performed using GraphPad Prism Software. Normality and Lognormality tests D’Agostino & Pearson, Anderson-Darling, Shapiro-Wilk, and Kolmogorov-Smirnov were performed to determine the choice for parametric or non-parametric testing. Post hoc tests on ANOVAs were conducted based on GraphPad recommendations. Preparation of miBrains for single-nucleus RNA sequencing (snRNA-seq) miBrains were cultured in standard conditions for 18 days, rinsed with PBS and frozen without media. Fresh frozen miBrains were processed using the Chromium Nuclei Isolation Kit (10x Genomics), with RNase inhibitors. Nuclei were quantified via DAPI staining using a Countess II FL automated cell counter (Life Technologies). 20,000 nuclei per sample were processed using 3’ GemX v4 reagents (10x Genomics), and libraries prepared according to the manufacturer’s instructions. All libraries were sequenced at Azenta using the NovaSeq X platform (Illumina). miBrain snRNA-seq Data Processing Raw sequencing reads were aligned to the human reference genome (GRCh38) and per-nucleus count matrices generated using Cell Ranger (10x Genomics, v9.0.1). Six libraries were processed — two replicates each for Control, APOE3/3-SNCA- A53T, and APOE4/4-SNCA- A53T conditions. Nuclei were filtered out if they had unique molecular identifier (UMI) counts or number of detected genes outside ±4 median absolute deviations (MADs) from the sample median, or if the fraction of mitochondrial reads exceeded 5%. Doublets were identified and removed using the simulation-based inference implemented in pegasus v1.10.0 116 , stratified by sample, prior to final clustering. Library-size normalization followed by log(x+1) transformation was then applied using scanpy v1.9.8 117 . Highly variable genes (HVGs) were identified using a Cell Ranger-flavored dispersion method using scanpy 117 , computed within each sample independently to account for inter-library variability, and restricted to protein-coding autosomal genes, excluding ribosomal (RPL/RPS), mitochondrial, and MitoCarta-annotated genes 118 . Principal component analysis (PCA) was performed on the 6,000 HVG-filtered, normalized matrix using pegasus v1.10.0, retaining 30 informative PCs identified from an elbow plot. Technical covariates (total UMI count, mitochondrial fraction, and cell cycle score) were regressed from the PCA embedding. Cross-sample batch effects were corrected using Harmony 119 . A k-nearest neighbor graph was constructed on the corrected embedding (K = 100) and Leiden community detection (resolution =0.2) 120 . UMAP embeddings were computed on the harmonized PCA space. To annotate the clusters, we first identified the most specific genes in each cluster using the cellTypeSpecificity function in dreamlet v1.9 121 . We then calculated the Spearman correlation between the average cluster-level expression of cell-type-specific genes and the annotated related cell types from Tereza Clarence et al. 122 . Cell-level metadata, including QC metrics and cell-type annotations, are provided in Table S3 . QC metrics per sample are available in Table S4 . Annotated cell numbers per sample are available in Table S5 . Following cell type annotation, for pseudo-bulk differential expression, raw counts were aggregated per cell type and sample using aggregateToPseudoBulk from dreamlet v1.9 121 , producing one pseudo-bulk profile per cell type–sample combination. Within each cell type, counts were normalized and precision weights estimated using the voom method via processAssays (minimum count per gene = 5). Pairwise differential expression between conditions was performed per cell type using linear mixed models implemented in dreamlet, with condition as the fixed effect and number of detected features as a covariate. To test whether biologically focused gene programs were transcriptionally dysregulated in A53T APOE3/3 excitatory neurons compared to controls and in APOE4/4 astrocytes compared to APOE3/3 , we performed gene set enrichment analysis (GSEA). We used manually curated gene sets directly relevant to Parkinson’s disease and lipid biology ( Table S2 ). Genes were ranked by their t-statistic from the dreamlet pseudo-bulk linear model (coefficient: A53T-APOE3 vs. control, neurons; A53T-APOE4 vs. A53T-APOE3 , astrocytes). We then ran GSEA on these custom gene sets using clusterProfiler v4.8.1 123 . In parallel, we tested the same ranked gene list against Gene Ontology (GO) Biological Process relevant to protein phosphorylation regulation (protein dephosphorylation, GO:0006470). Human iPSC-derived astrocyte bulk RNAseq analysis Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values were obtained from published bulk RNA-seq data of isogenic human iPSC-derived astrocytes expressing either APOE3/3 or APOE4/4 66 . FPKM values were log2-transformed with an offset of 0.1 and genes with zero variance across all the samples were excluded. To focus on genes with meaningful variability, an additional filtering step was applied to retain genes above the 10th percentile (variance > 0.033) after the removal of the zero-variance genes. Differential expression analysis was performed using the limma package in R. A design matrix was constructed to model the experimental conditions (APOE3 vs. APOE4) and sample-specific array weights were estimated using the array Weights function with a prior.n value of 100 to help stabilize weight estimation. A linear model was then fit to the log-transformed, filtered expression data using lmFit, and empirical Bayes moderation was applied via the eBayes function, with trend and robust both set to TRUE. DEGs were defined as having an absolute log2 fold change > 0.5 and adjusted p-value (false discovery weight) < 0.05. A volcano plot was then generated using the ggplot2 package and genes meeting the DEG thresholds were highlighted. Enrichment analysis was performed on the upregulated and downregulated DEGs separately using the clusterProfiler package. Pathways were identified through Gene Ontology (GO) database. The top 10 pathways for each direction (upregulated and downregulated) were selected based on adjusted p-values. Human astrocyte scRNAseq pseudobulk analysis The processed dataset was downloaded from Haney et al 73 . Unless otherwise stated, all following analyses were performed in R using the package Seurat 124 . Aligning with the quality control protocol from the source publication, cells with nFeature < 500, nCount 10% were discarded. Doublets were removed using the DoubletFinder package 125 . Following the standard Seurat pipeline with default parameters, raw gene counts were normalized, the top 2,500 highly variable genes were identified, and the data were scaled. Harmony was used to integrate the patient samples, and the top 20 principal components were used in Seurat’s FindNeighbors, FindClusters (0.2 resolution), and RunUMAP functions. Cell-type annotation was manually performed using the marker genes described in Haney et al., and clusters not enriched for these marker genes were removed from further analysis. Pseudobulked samples were generated by summing the raw counts for each patient sample and normalized using Seurat’s AggregateExpression() function. Isogenic iPSC-derived astrocyte RNAseq analysis The raw counts from iPSC-derived astrocyte bulk RNAseq were downloaded from Lin et al. 66 Raw counts were processed using the DeSeq2 package 126 and normalized using the counts() function with normalized set to TRUE. DQ-BSA proteolytic activity assay Astrocytes were seeded at 10,000 cells/well of a 96 well µClear plastic bottom plate (Greiner 655090) in AM. The following day, the media was changed to FBS-free maturation media (50% DMEM/F12, 50% Neurobasal, 1X B27 without Vitamin A, 1X N2, 1X NEAA, 1X GlutaMAX, 1% penicillin-streptomycin). Half of the wells were treated with 100 nM BafilomycinA1 to inhibit lysosomal function as a negative control. The next day, cells were pulsed with 1µg/mL DQ-BSA (Thermo D12051) in maturation media for 30 minutes. Media was replaced with fresh media (and fresh bafilomycin in the appropriate wells), and the red fluorescence and bright field were imaged at 20x with an Incucyte (Sartorius) every hour for 24 hours. Alternatively, astrocytes were seeded at 50K cells/well of a 12-well plate. Media changes were followed as above. Cells were lifted to single-cell suspension with TrypLE Select 24 hours after the DQ-BSA pulse and filtered into flow cytometry tubes with DAPI. Red fluorescence in live cells was analyzed with a BD Celesta flow cytometer. Live Imaging of α-Syn-HiLyte Uptake and Degradation Astrocytes were seeded 10,000 cells/well of a 96-well µClear plastic bottom plate (Greiner) in AM. The following day, the media was changed to FBS-free maturation media (50% DMEM/F12, 50% Neurobasal, 1X B27 without Vitamin A, 1X N2, 1X NEAA, 1X GlutaMAX, 1% penicillin-streptomycin) and cultured for 2 more days. α-Syn-HiLyte (AnaSpec AS-55457) was added to the media at a final concentration of 2 µg/mL, and nuclei were stained with 10 µg/mL Hoechst 33342. Images were acquired every 30-90 minutes for the first 6 hours on a Nikon AX R. At 24 h, the media was changed to fresh FBS-free maturation media to remove any excess α-Syn. Images were acquired at 24 h and 48 h using the same parameters and laser settings. Live Imaging of BODIPY-Cholesterol Astrocytes were seeded 10,000 cells/well of a 96-well µClear plastic bottom plate (Greiner) in AM. The following day, the media was changed to FBS-free maturation media (50% DMEM/F12, 50% Neurobasal, 1X B27 without Vitamin A, 1X N2, 1X NEAA, 1X GlutaMAX, 1% penicillin-streptomycin) and cultured for 3 more days. Astrocytes were incubated with 2 µM BODIPY-Cholesterol (Cayman 24618) for 2 hours. Cells were then incubated with 10 µg/mL Hoechst 33342 for 10 minutes to stain nuclei. Media was replaced with fresh media and cells were imaged using a CX7 High Content Screening Platform with a 20x objective lens (Thermo; LUCPLFLN20x). Western blotting and dot blotting Sequential detergent extraction was performed to biochemically separate detergent-soluble and detergent-insoluble α-synuclein species, adapted from Lam et al., 2024 29 . Briefly, cells lysed in 1% (vol/vol) Triton X-100 in TBS supplemented with protease and phosphatase inhibitors. Lysates were subjected to water bath sonication (VWR Symphony Ultrasonic Cleaner; 30 s on/30 s off, 5 cycles), incubated on ice for 30 min, and centrifuged at 15,000 × g for 30 min at 4 °C. The resulting supernatant was collected as the Triton X-100–soluble fraction, and protein concentration was determined by BCA assay. The remaining pellet was resuspended in Triton X-100 buffer, re-sonicated, and centrifuged again at 15,000 × g for 30 min. The insoluble pellet was then resuspended in 2% (vol/vol) SDS in TBS containing protease and phosphatase inhibitors and subjected to additional water bath sonication (30 s on/30 s off, 5 cycles) to generate the SDS-soluble fraction. The SDS-soluble supernatant was collected and adjusted to twice the volume of the matched Triton X-100 fraction to enrich for detergent-insoluble α-synuclein species and facilitate visualization on immunoblots. Samples were heated at 65 °C for 5 min prior to gel loading. Equal volumes of Triton X-100–soluble and SDS-soluble fractions (20 µL per lane, corresponding to 30 µg of protein for the Triton fraction) were resolved on 4–12% SDS-PAGE gels (BioRad) and transferred to PVDF membranes using the Trans-Blot Turbo dry transfer system. Immunoblots were subsequently performed as described for PVDF membranes below. For all other Western blots, cells were lysed in RIPA Buffer supplemented with protease and phosphatase inhibitors. The protein concentration of each sample was measured using Pierce BCA Protein Assay (Thermo Fisher). Volumes corresponding to 20 µg of protein for each sample were loaded into 4-12% SDS-PAGE gels (BioRad), and a current of 120V was applied for approximately 60 min. The gel proteins were transferred to a PVDF membrane using BioRad TransBlot Turbo Transfer System, fixed in 4% PFA for 40 min and blocked in 5% w/v non-fat milk in 0.1% Tween in TBS (TBST) for 1 hour. For antibodies against phosphorylated proteins, blots were blocked in 5% w/v bovine serum albumin (BSA) in 0.1% TBST. Blots were then incubated with primary antibodies diluted at 1:1000 in blocking buffer overnight at 4°C. Membranes were washed in 0.1% TBST 3 times for 5 min each, incubated with secondary antibodies conjugated with horseradish peroxidase for 2h at room temperature in blocking buffer, and exposed to chemiluminescence activator before imaging using LI-COR Odyssey XF system. For dot blots, 3 µL of media was added onto nitrocellulose membranes and allowed to dry. Blocking and antibody incubation were performed as described for Western blots. Protein concentration in the media was quantified by Piece BCA Protein Assay and used to normalize dot blot signal. Collection and treatment with conditioned media To generate neuron-conditioned media A53T-1A CORR28 neurons were plated at ∼150,000/cm2 on poly-L-ornithine and laminin-coated plates on day 7 of differentiation. The media was changed following the differentiation protocol described above. Starting day 14 of differentiation, the media was collected, centrifuged at 2000xg for 5 minutes to pellet debris, and stored at -20°C. Media was collected with each half media change, every 3-4 days. To generate astrocyte-conditioned media, astrocytes were plated at ∼30,000/cm2 on 0.1% gelatin-coated plates in AM (ScienCell). The following day, media was changed to either fresh neuron media (Neurobasal, 1x B-27, 1x N-2, 1x MEM-NEAA, 1x GlutaMAX, 1% penicillin-streptomycin, 10ng/mL BDNF, 10ng/mL GDNF, 0.5 mM dcAMP, 1ug/mL laminin) supplemented with 10ng/mL CNTF or neuron conditioned media supplemented with 10ng/mL CNTF. After 3 days, media was collected, centrifuged at 2000xg for 5 minutes to pellet debris, and stored at -20°C. To treat neurons with conditioned media, SNCA-A53T overexpressing neurons were plated at ∼150,000/cm2 on poly-L-ornithine and laminin-coated 96-well µClear plates (Greiner) on day 7 of differentiation, following the normal neuron differentiation protocol described above. On day 11 of differentiation, the media were changed to conditioned media supplemented with 5 µg/mL doxycycline and 1 µg/mL laminin. Half media changes with conditioned media supplemented with doxycycline and laminin were continued every 3-4 days until day 25 of differentiation, when cultures were fixed. To treat microglia with conditioned media, SNCA-A53T neuron conditioned media was collected as described above and incubated with microglia cultured in 2D conditions after seeding at ∼85,000/cm2 on geltrex-coated 96-well µClear plates (Greiner). SNCA Knockdown Astrocyte Generation with shRNAs SNCA and scramble MISSION lentiviral shRNAs were purchased from Sigma Aldrich. SNCA shRNA lentivirus was produced using standard protocols. iPSC-derived Astrocytes were plated at ∼21,000 cells/um in a 6-well plate. The following day, cells were transduced at a 1:40 dilution in Astrocyte Medium. 24 hours post-transduction media was replaced with fresh Astrocyte Media. Selection was started 72 hours post-transduction by adding fresh media supplemented with 2 ug/ml puromycin for two consecutive days. Treatment with cholesterol-lowering drugs Astrocytes were seeded into 0.1% gelatin-coated 6-well plates in AM (ScienCell). After 2-3 days, the media was changed to AM without FBS supplemented with cholesterol-lowering drugs (concentrations below) or DMSO as a vehicle. After 4 days, cells were seeded for final assays in 0.1% gelatin-coated 96-well µClear plates (Greiner) in AM with treatment. The following day, media was changed to FBS-free maturation media (50% DMEM/F12, 50% Neurobasal, 1X B27 without Vitamin A, 1X N2, 1X NEAA, 1X GlutaMAX, 1% penicillin-streptomycin) with treatment. Assays were started 2-3 days later, as described above. miBrains were treated with methyl-β-cyclodextrin (concentration below) or DMSO from day 0 of assembly to day 18, with half-media changes performed 3 times a week. The following drug concentrations were used: 2-hydroxypropyl-β-cyclodextrin: 100 µM (Sigma C0926) methyl-β-cyclodextrin: 100 µM (Cayman 21633) atorvastatin: 50 nM (Sigma SML3030) efavirenz: 10 µM (MedChemExpress HY10572) LXR-623: 10 µM (MedChemExpress HY-10629) T0901317: 10 µM (MedChemExpress HY-10626) Supplemental information Document S1. Figures S1-S5; Legends for Videos S1, S2, and S3 Video S1. Neurons with α-Synuclein pathological phenotypes within the miBrain; related to Figure 1 Video S2. APOE3/3 astrocytes co-localize with neuronal-derived α-Synuclein; related to Figure 2 Video S3. APOE4/4 reactive astrocytes poorly co-localize with neuronal-derived α-Synuclein; related to Figure 2 Table S1. Differentially expressed genes (DEGs). Unfiltered DEGs in APOE3/3 A53T vs. Control and in APOE4/4 vs APOE3/3. Table S2. Pathway analysis. Gene ontology biological processes enrichment and curated gene sets utilized for gene set enrichment analysis. Table S3. Metadata. Cell-level metadata, including QC metrics and cell-type annotations. Table S4. QC. QC metrics per sample. Table S5. Cell number. Number of nuclei per sample and cellular cluster. Figure Legends Download figure Open in new tab Figure S1. miBrain cryopreservation and development of α-synuclein intracellular inclusions. a. Representative microelectrode array (MEA) raster plot showing spontaneous neuronal firing across electrodes in 1-week old miBrains. Scale bar: 400 µm b. Quantification of MEA recordings: (i) mean firing rate (Hz), (ii) number of active electrodes per array, (iii) frequency of spontaneous bursts, and (iv) number of electrodes participating in synchronized network bursts. Data represents SEM (n = 8 biological replicates). c. Cartoon of the cryopreservation approach to preserve miBrains or smaller tissue units (miVasC: microvascular combo; BBB: blood-brain barrier; JAM: just add missing cell type). Representative images of two-week-old, thawed tissue stained with markers of neurons (neurofilament; cyan), astrocytes (S100b, GFAP; green), and endothelial cells (PECAM-1; red). Scale bars: 50 µm. d. Left: cell viability (% live) upon thawing the cryopreserved tissue compared with fresh cells harvested and counted. Data represent mean ± SEM (n = 1-4 biological replicates). Right: quantification of the ratio between neurons (TUJ1) and nuclei (Hoechst) volume in 18-day-old thawed miBrain tissue from three different batches. Microglia were not included in these frozen miBrains. Data represent mean ± SEM (n = 3 batches with 4-8 biological replicates each). e. Representative IF images of miBrains exposed to α-Syn pre-formed fibrils (PFFs) for 48h at week-2 in culture and stained after 14 days. Microglia were not included in these miBrains. α-Syn pS129 (red) intensity was normalized by nuclei (blue) and vehicle-treated miBrains; TUJ1 (cyan). Scale bars: 500 µm (low magnification) and 50 µm (high magnification). Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by a two-tailed, unpaired t-test. The left graph shows the quantification of the experiment represented by the images. The right graph shows the quantification across three different experiments (n = 4 biological replicates each). f . Representative IF images of α-Syn pS129 (red) in 25-DIV 2D-cultured neurons (TUJ1; cyan) generated from control (endogenous SNCA ), SNCA -A53T, or SNCA -A53T-ΔNAC iPSCs, 14 days after vehicle or PFF treatment. α-Syn pS129 volume was normalized to TUJ1 volume and vehicle-treated control. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. Scale bars: 50 µm. g . Representative IF images of α-Syn pS129 (red) in 25-DIV 3D-cultured neurons (TUJ1; cyan) generated from control (endogenous SNCA ), SNCA -A53T, or SNCA -A53T-ΔNAC iPSCs, 14 days after vehicle or PFF treatment. α-Syn pS129 volume was normalized to TUJ1 volume and vehicle-treated control. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. Scale bars: 50 µm. h. Representative IF images of α-Syn pS129 (red) in 18-days-old miBrains with control or SNCA- A53T neurons, 14 days after vehicle or PFF treatment. Microglia were not included in these miBrains. α-Syn pS129 volume within TUJ1 (cyan) was normalized to vehicle-treated control miBrains. Data represent mean values ± SEM (n = 6 biological replicates). P-values were calculated by 2-way ANOVA and Fisher’s LSD. i. Quantification of % area of sfGFP-SNCA co-stained with α-Syn pS129. Data represent mean values ± SEM (n = 4 biological replicates). P-values were calculated by a two-tailed, unpaired t-test. j. Quantification of α-Syn pS129 co-localized with sfGFP or external to sfGFP. Data represent mean values ± SEM (n = 4 biological replicates). P-values were calculated by 2-way ANOVA and Fisher’s LSD. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. k. Number of cells normalized by the control group of each cell type, in control and A53T miBrains. P-values were calculated by 2-way ANOVA and Sidak’s multiple comparisons test (n = 2 biological replicates, each one containing 2 pooled miBrains). l. Representative Gene set enrichment analysis (GSEA) plots showing α-synuclein pathology, synaptic maturation and protein dephosphorylation are modulated in SNCA -A53T miBrains compared to control. Download figure Open in new tab Figure S2: Characterization of α-Syn inclusions in miBrain tissue. a. Representative IF images of control and SNCA -A53T 18-days-old miBrains stained for aggregated α-Syn (cyan) and TOM20 (magenta). Volume of co-localized aggregated α-Syn and TOM20 was normalized to control miBrains. Data represent mean ± SEM (n = 6 biological replicates). P-value was calculated by the Mann-Whitney test. Scale bar: 25 µm. b. Quantification of total hyperphosphorylated tau (PHF1) in control and SNCA -A53T miBrains. Representative images in Figure 2b . PHF1 volume normalized to the number of nuclei and control miBrains. Data represent mean ± SEM (n = 6 biological replicates). P-value was calculated by a two-tailed, unpaired test. c. Western blots of total α-Syn (left) and α-Syn pS129 (right). Protein was extracted sequentially in Triton X-100 and SDS lysis buffers from control or SNCA- A53T neurons grown in 2D monoculture, with or without PFF treatment. Actin was used as a loading control. d. Quantification of relative lactate dehydrogenase (LDH) levels in control and SNCA -A53T miBrain media after 14 days of culture. Bars represent mean ± SEM (n = 4 biological replicates). P-value was calculated by Welch’s two-tailed t-test. e. Representative images of SNCA-A53T-sfGFP in live miBrains after 2 and 22 weeks of culture. Data represent mean sfGFP volume ± SEM (n = 4 biological replicates). P-value was calculated by a two-tailed, unpaired t-test. Scale bar: 100 µm. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Download figure Open in new tab Figure S3. Non-neuronal cells promote α-synuclein pathological phenotypes in APOE4/4 tissue. a. Representative IF images of α-Syn pS129 (red) in 2D-cultured APOE3/3 and APOE4/4 isogenic 25-DIV neurons overexpressing SNCA-A53T-sfGFP, 14 days after vehicle or PFF treatment. α-Syn pS129 volume was normalized to TUJ1 (cyan) volume and APOE3/3 vehicle treated cells. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by 2-way ANOVA and Fisher’s LSD. Scale bar: 50 μm. b. Representative IF images of monocultures of all cell types of the miBrain, stained for cell-specific markers (green). Positive cell area was normalized to the number of nuclei (blue) and APOE3/3 cells. Data represent mean ± SEM (n = 3 biological replicates). P-values were calculated by two-tailed, unpaired t-tests. Scale bar: 50 µm. c. Quantification of α-Syn pS129 outside of sfGFP volume (non-neuronal). Normalized to APOE3/3 miBrains. Data represent mean ± SEM (n = 8 biological replicates). P-value was calculated by Welch’s two-tailed t-test. d. Representative IF images of α-Syn pS129 (red) in APOE3/3 and APOE4/4 18-days-old miBrains with control or SNCA -A53T neurons. The A53T neurons were generated from the A53T-1A CORR28 line (donor with familial Parkinson’s disease). α-Syn pS129 volume was normalized to Hoechst (blue) volume and APOE3/3 miBrains with control neurons. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by 2way ANOVA and Fisher’s LSD. Scale bar: 50 µm. e. Representative IF images of IBA1 (cyan) and CD68 (red) in 2D-microglia monoculture after exposure to fresh or SNCA-A53T neuron conditioned media. IBA1 intensity and CD68 volume were normalized by Hoechst volume (blue) and cells exposed to fresh media conditions. Data represent mean ± SEM (n = 6 biological replicates). P-values were calculated by two-tailed, unpaired t-tests. Scale bar: 50 µm. f. Representative IF images of α-Syn pS129 (red) in APOE3/3 and APOE4/4 18-days-old miBrains, with or without isogenic microglia (IBA1; cyan). α-Syn pS129 volume within SNCA-A53T-sfGFP (green) neurons was normalized to sfGFP volume and APOE3/3 miBrains without microglia. Data represent mean ± SEM (n = 6 biological replicates). P-values were calculated by 2way ANOVA and Fisher’s LSD. Scale bar: 50 µm. g. Representative IF images of α-Syn pS129 (red) in APOE3/3, APOE4/4 and APOE3/3 with APOE4/4 microglia 18-days-old miBrains. APOE3/3 cells are represented by blue boxes and APOE4/4 cells are represented by yellow boxes. α-Syn pS129 volume within SNCA-A53T-sfGFP neurons (green) was normalized to total SNCA-A53T-sfGFP volume and APOE3/3 miBrains. Data represent mean ± SEM (n = 8 biological replicates). P-values were calculated by one-way ANOVA and Tukey’s test. Scale bar: 50 µm. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Download figure Open in new tab Figure S4. Characterization of lysosomal function and α-Synuclein uptake and accumulation in astrocytes. a. RNAseq analysis of isogenic, iPSC-derived astrocytes for SNCA expression using normalized counts (FPKM). Data represent mean ± SEM (n = 3 biological replicates). P-value was calculated by a two-tailed, unpaired t-test. b. Western blots of APOE3/3 and APOE4/4 astrocytes for total α-Syn protein and phosphorylated α-Syn protein. β-Actin was used as a loading control. Quantifications normalized to β-Actin and APOE3/3. Data represent mean ± SEM (n = 3 replicates). P-values were calculated by Welch’s one-tailed t-test (total α-Syn) and unpaired, one-tailed t-test (pS129 α-Syn) c. Representative IF images of astrocytes with α-Syn-HiLyte (green) after 24 hours of uptake and 24 hours of degradation after treatment with BafilomycinA1 and MG-132. αSyn-HiLyte intensity was normalized to Hoechst (blue) area and vehicle-treated astrocytes. Data represent mean ± SEM (n = 5 biological replicates). P-values were calculated by one-way ANOVA and Sidak’s test. Scale bar = 50 µm. d. Representative IF images of LAMP1 immunostaining (magenta) in two different isogenic iPSC lines. LAMP1 intensity normalized to Hoechst (blue) and APOE3/3 for each isogenic pair. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by two-tailed, unpaired t-tests. Scale bar = 50 µm. e. DQ-BSA Red integrated intensity normalized to dextran and measured over 24 hours on an Incucyte (Sartorius). 100 nM bafilomycin A1 was used as a control for non-lysosomal proteolysis of DQ-BSA. Data represents mean ± SEM (n = Data points represent mean values and error bars represent standard error (n = 3-5 biological replicates). P-values were calculated by 2-way ANOVA and Fisher’s LSD on area under the curve values. f. Representative IF images of pS129 α-Syn (red) in SNCA -A53T neurons treated with conditioned media from APOE3/3 or APOE4/4 astrocytes or with fresh neuron media. pS129 α-Syn volume normalized to SNCA-A53T-sfGFP (green) volume and to cells treated with fresh media. Data represent mean ± SEM (n = 6 biological replicates). P-values were calculated by one-way ANOVA and Tukey’s test. Scale bar = 50 µm. g . qPCR validation of lentiviral shRNAs targeting SNCA in astrocytes. Relative gene expression was calculated by ΔΔCt with ACTB as a housekeeping gene. Data represent mean ± SEM (n = 1-3 biological replicates). P-values were calculated by one-way ANOVA and Dunnett’s test. h. Representative IF images of pS129 α-Syn (red) in SNCA -A53T neurons treated with neuron-conditioned media or neuron and astrocyte-conditioned media from APOE3/3, APOE4/4, or APOE4/4 with SNCA shRNA astrocytes. pS129 α-Syn volume was normalized to TUJ1 (magenta) volume and neuron-conditioned media samples. Data represent mean ± SEM (n = 5 biological samples). P-values were calculated by one-way ANOVA and Tukey’s test. Scale bar = 50 µm. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Download figure Open in new tab Figure S5. MβCD treatment in APOE4/4 astrocytes improves lysosomal uptake of α-Synuclein. a. Volcano plot of APOE4/4 vs. APOE3/3 astrocytes showing DEGs (p adj 0.5). Top 10 Gene Ontology (GO) upregulated (red) and downregulated (blue) pathways ranked by adjusted p-value. Genes highlighted in the volcano plot correspond to GO terms related to lipid metabolism b. Representative IF images of Filipin (grey) and LAMP1 (magenta) in astrocytes treated with MβCD. Filipin integrated intensity was normalized by astrocyte area and APOE3/3. Data represent mean ± SEM (n = 6 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. Scale bar = 50 µm. c. Left: DQ-BSA Red integrated intensity in astrocytes with 2HβCD or MβCD treatment, measured over 24 hours on an Incucyte (Sartorius) in a second isogenic donor line. Data represent mean ± SEM (n = 4 biological replicates). Right: Area under the curve calculation for DQ-BSA. Data represent mean ± SEM (n = 4 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. d. Representative IF images of LysoTracker (magenta) in astrocytes treated with cyclodextrins in a second isogenic donor line. LysoTracker intensity was normalized by Hoechst (blue) area and APOE3/3 . Data represent mean ± SEM (n = 5-6 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. Scale bar = 50 µm. e. Representative IF images of astrocytes treated with cyclodextrins after a 24h incubation with fluorescently labeled α-Syn-HiLyte (green) in a second isogenic donor line. α-Syn-HiLyte intensity was normalized by Hoechst (blue) area and APOE3/3 . Data represent mean ± SEM (n = 6 biological replicates). P-values were calculated by 2-way ANOVA and Tukey’s test. Scale bar = 50 µm. f . Representative IF images of fluorescently labeled α-Syn-HiLyte (green) co-localized with LysoTracker (magenta) in astrocytes treated with cyclodextrins. Calculated Mander’s coefficient M2 (amount of α-Syn signal overlapping with LysoTracker signal). Data represent mean ± SEM (n = 8 replicates). P-values were calculated by 2-way ANOVA and Fisher’s test. Scale bar = 50 µm. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Video S1. Neurons with α-synuclein pathological phenotypes within the miBrain . 3D rendering with animated orthogonal projection of SNCA-A53T neurons within the miBrain. Green: SNCA-A53T-sfGFP; red: pS129 α-Syn; magenta: TUJ1, blue: Hoechst. Video S2. APOE3/3 astrocytes co-localize with neuronal-derived α-synuclein. 3D rendering with animated orthogonal projection of astrocytes within an APOE3/3 miBrain. Astrocytes display elongated morphology along neuronal networks. Green: SNCA-A53T-sfGFP; magenta: GFAP, blue: Hoechst. Video S3. APOE4/4 reactive astrocytes poorly co-localize with neuronal-derived α-synuclein. 3D rendering with animated orthogonal projection of astrocytes within an APOE4/4 miBrain. Astrocytes display amoeboid morphology not aligned with neuronal networks. Green: SNCA-A53T-sfGFP; magenta: GFAP, blue: Hoechst. Acknowledgments We would like to thank Tatyana Kareva for technical support and all members of the Blanchard Lab for scientific discussions. We would like to thank Natalie Suhy for help with MEA experiments, Anna Bright and Ana Forton-Juarez for help with cellular differentiations, and Elena Coccia for revising the manuscript. We thank Dr Cristina d’Abramo (The Litwin Zucker Center for Alzheimer’s Disease Research) for producing PHF1 antibody and providing guidance on its use. We acknowledge the use of BioRender for generation of illustrative cartoons. This work has been funded in part with federal funds from NASA under contract #80ARC022CA004 titled “Identification of Biomarkers and Pathological Mechanisms via Longitudinal Analysis of Neurological and Cerebrovascular Responses to Neurotoxic Stress Using a Multi-cellular Integrated Model of the Human Brain.” This research was funded in whole or in part by Aligning Science Across Parkinson’s (ASAP-024297) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF). For the purpose of open access, the author has applied a CC BY public copyright license to all Author Accepted Manuscripts arising from this submission. This work was also supported by funding from the NIH/NINDS/NIA (R01NS114239, UH3NS115064, and 1U54AG090669-01), and the CureAlz Fund. C.G. was supported by funding from the NIH/NIA (T32AG04968) and NIH/NINDS (F31NS13090). Funder Information Declared National Aeronautics and Space Administration, https://ror.org/027ka1x80 , 80ARC022CA004 Aligning Science Across Parkinson's, https://ror.org/03zj4c476 , ASAP-024297 National Institute of Neurological Disorders and Stroke , R01NS114239 , UH3NS115064 , F31NS13090 National Institute on Aging, https://ror.org/049v75w11 , 1U54AG090669-01 , T32AG04968 CureAlz Fund Footnotes ↵ 17. Lead contact This revision has been revised to address comments raised during peer review. 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