Polygenic risk for alcohol use disorder affects cellular responses to ethanol exposure in a human microglial cell model.

paper Primary Public

Authors: Li, Xindi; Liu, Jiayi; Boreland, Andrew J; Kapadia, Sneha; Zhang, Siwei; Stillitano, Alessandro C; Abbo, Yara; Clark, Lorraine; Lai, Dongbing; Liu, Yunlong; Barr, Peter B; Meyers, Jacquelyn L; Kamarajan, Chella; Kuang, Weipeng; Agrawal, Arpana; Slesinger, Paul A; Dick, Danielle; Salvatore, Jessica; Tischfield, Jay; Duan, Jubao; Edenberg, Howard J; Kreimer, Anat; Hart, Ronald P; Pang, Zhiping P
Year: 2024
Journal: Science advances
PMID: 39514655
DOI: 10.1126/sciadv.ado5820
PMCID: PMC11546823

Fig. 1.

Characterization of iPSC-derived PMPs and microglia.(A) Protocols for generation of PMPs and microglial cells from iPSC. (B) Representative images of CD235+ and CD43+ cells in PMPs (line 8864). (C and D) Quantification of CD235+ PMPs derived from all iPSC lines with different PRS (low-PRS, n = 10; high-PRS, n = 8). (E and F) Quantification of CD43+ PMPs derived from all iPSC lines with different PRS (low-PRS, n = 10; high-PRS, n = 8). (G) Representative images of IBA1+, P2Y12+, CX3CR1+, TMEM119+, and PU.1+ microglia from high-PRS line 8864 and low-PRS line 9618. BMP-4, bone morphogenetic protein 4; VEGF, vascular endothelial growth factor; EB, embryonic body; SCF, stem cell factor; IL-3, interleukin-3; M-CSF, macrophage colony stimulating factor; IL-34, interleukin-34; GM-CSF, granulocyte-macrophage colony stimulating factor; DAPI, 4′,6-diamidino-2-phenylindole.

Fig. 2.

Whole-genome transcriptome profile comparison between human microglial cells derived from high-PRS and low-PRS iPSC lines.(A) Volcano plot depicts the DEGs between the high-PRS and low-PRS microglial cells. (B to D) GO analysis depicting the significant terms (top 10 up- and down-regulated terms) associated with microglia when comparing high-PRS versus low-PRS. It includes biological processes (BPs, B), molecular functions (MFs, C), and cellular components (D). P adjusted values are displayed. (E) Heatmap illustrates gene expression patterns related to chromosome separation in both high-PRS (red, n = 4 lines) and low-PRS (blue, n = 5 lines) microglia. (F) Heatmap illustrates gene expression patterns related to antigen processing and presentation in both high-PRS (red, n = 4 lines) and low-PRS (blue, n = 5 lines) microglia.

Fig. 3.

The impact of ethanol exposure on the activation of iPSC-derived microglia.(A) Representative images of CD68+ and IBA1+ microglia derived from high-PRS (line 8528) and low-PRS lines (line 9206) following a 7-day exposure to ethanol (0, 20, and 75 mM). (B) Quantification of CD68 corrected fluorescence-integrated density normalized to each control (0 mM) replicate. Low-PRS (n = 6 lines) versus high-PRS (n = 5 lines), **P < 0.01 and ***P < 0.001. Data are presented as mean ± SEM. (C) Representative images showing the process traced with regions of interest (ROI) using the IBA1 signal in iPSC-derived microglia with high-PRS (line 8864) or low-PRS (line 8838). (D) Morphological analysis of microglia binary outlines using FracLac ImageJ. n = 177 cells in five high-PRS lines, 211 cells in six low-PRS lines for 0 mM; n = 188 cells in five high-PRS lines, 214 cells in six low-PRS lines for 20 mM; n = 164 cells/five high-PRS lines, 219 cells/six low-PRS lines for 75 mM. *P < 0.05, **P < 0.01, and ***P < 0.001. Data are presented as medium ± quartiles.

Fig. 4.

Transcriptomic profiles in high-PRS versus low-PRS human microglia after ethanol exposure.(A and B) Volcano plots depict the DEGs between the different ethanol concentrations (75 mM versus 0 mM) in four high-PRS lines (A) and five low-PRS lines (B) of microglial cells. (C and D) GO analysis of BPs highlighting significant terms (top 10 up- and down-regulated terms) associated with ethanol exposure (75 mM versus 0 mM) in both high-PRS (C) and low-PRS (D) microglia. Adjusted P values (P adjust.) are displayed. (E) GSEA plot depicting the enrichment of the phagocytosis-associated pathway specific to high-PRS microglia following ethanol exposure. P values and P adjust. are displayed. (F) GSEA plot of the MHCII and antigen processing–associated pathway enrichment specific to high-PRS microglia following ethanol exposure. P values and P adjust. are displayed.

Fig. 5.

Differential expression of phagocytosis-related genes between high-PRS and low-PRS microglia in response to ethanol exposure.(A) A heatmap illustration of the gene expression profiles related to antigen processing and presentation in both high-PRS (red) and low-PRS (blue) microglia, with and without ethanol exposure. (B) Box blots comparisons of the differential expression of genes associated with antigen processing and presentation in microglia from both high-PRS (red) and low-PRS (blue) lines, with and without ethanol exposure. Low-PRS/high-PRS lines = 5/4. *P < 0.05 and **P < 0.01. Data are presented as means ± SEM. (C) A heatmap illustration of the gene expression profiles related to the phagocytosis pathway in both high-PRS (red) and low-PRS (blue) microglia, with and without ethanol exposure. (D) Box blots comparison of the representative differential expression of genes associated with the phagocytosis pathway in microglia from both high-PRS (red) and low-PRS (blue) lines, with and without ethanol exposure. Low-PRS/high-PRS lines = 5/4. *P < 0.05 and **P < 0.01. Data are presented as means ± SEM.

Fig. 6.

CLEC7A expression between high-PRS and low-PRS microglia after ethanol exposure.(A) Representative images of CLEC7A+ and IBA1+ microglia derived from PRS lines following ethanol exposure (0 and 75 mM). (B and C) Quantification of CLEC7A+ fluorescence-integrated density (B) and corrected fluorescence-integrated density normalized to each control (0 mM) replicate (C). n = 331 cells/eight high-PRS lines and 365 cells/10 low-PRS lines for 0 mM; n = 315 cells/eight high-PRS lines and 373 cells/10 low-PRS lines for 75 mM; ***P < 0.001. Data are presented as means ± SEM.

Fig. 7.

Enhanced phagocytosis ability in high-PRS iPSC-derived microglia in response to ethanol.(A and B) Representative live-cell imaging of iPSC-derived microglia from low-PRS (line 8092, A) and high-PRS (line 8528, B) engaged in the phagocytosis of zymosan particles at different ethanol concentrations (0, 20, and 75 mM). The upper images are overlapped with bright-field microscopy for reference. (C) Quantification of the fluorescence-integrated density of zymosan bioparticles (beads): The top panel shows the fluorescence-integrated density between high-PRS and low-PRS microglial cells, while the bottom panel shows the corrected fluorescence-integrated density normalized to each control (0 mM). Low-PRS/high-PRS lines = 10/8, **P < 0.01 and ***P < 0.001. Data are presented as means ± SEM. (D) Quantification of the proportion of microglia with zymosan particles (beads): The top panel shows the proportion of microglia with beads, while the bottom panel displays the corrected proportion, which has been normalized to each control (0 mM) replicate. Low-PRS/high-PRS lines = 10/8, **P < 0.01 and ***P < 0.001. Data are presented as means ± SEM.

Fig. 8.

High-PRS iPSC-derived microglia decreases excitatory neurotransmission in coculture.(A) Representative images of coculture consisting of MAP2+ neurons and IBA1+ microglia derived from both high-PRS and low-PRS lines, following treatment with ethanol (0 and 75 mM). (B) Quantification of the proportion of microglia and neurons in coculture with high-PRS and low-PRS microglial cells under 0 and 75 mM conditions (low-PRS = 7 lines, high-PRS = 6 lines). Data are presented as means ± SEM. (C) Representative images illustrating synaptic puncta (green, labeled by synapsin immunofluorescence) associated with dendrites (red, visualized by MAP2 immunofluorescence) in iNs without microglia, with low-PRS microglial cells or with high-PRS microglial cells. (D) Quantification of synapsin puncta densities per MAP2 area. (iN without microglia: 0 mM = 73 images, 75 mM = 73 images; iN + low-PRS microglial cells: 0 mM = 93 images, 75 mM = 85 images; iN + high-PRS microglial cells: 0 mM = 70 images, 75 mM = 75 images). (E) Representative traces of miniature excitatory postsynaptic currents (mEPSCs) in Ngn2-iNs without microglia (gray, 0 mM = 43 cells, 75 mM = 46 cells), Ngn2-iNs with low-PRS microglial cells (blue, 0 mM = 53 cells, 75 mM = 55 cells), and Ngn2-iNs with high-PRS microglial cells (red, 0 mM = 43 cells, 75 mM = 46 cells). (F) Cumulative distribution and quantification (inserts) of mEPSC frequency (top) and amplitude (bottom) in Ngn2-iNs without microglia (gray), Ngn2-iNs with low-PRS microglial cells (blue), and Ngn2-iNs with high-PRS microglial cells (red). Data are means ± SEM; statistical significance (*P < 0.05, **P < 0.01, and ***P < 0.001) was evaluated with the Kolmogorov-Smirnov test (cumulative probability plots) and t test (bar graphs).

#	Section	Preview
40	MATERIALS AND METHODS — Generation of coculture of iPSC-iNs and iPSC-derived microglia	We utilized a mid-PRS line [line 420 (58)] iPSC sourced from the NIAAA/COGA Sharing Repository to…
41	MATERIALS AND METHODS — Generation of coculture of iPSC-iNs and iPSC-derived microglia	The lentivirus generation protocol was previously outlined by Wang et al. (88). Selection with…
42	MATERIALS AND METHODS — Generation of coculture of iPSC-iNs and iPSC-derived microglia	On day 14, iPSC-derived microglia (approximately 30,000 cells per coverslip; table S1) were added…
43	MATERIALS AND METHODS — Intermittent ethanol exposure	Following a 7-day maturation period in DMEM/F12 medium supplemented with N2, IL-34, and GM-CSF,…
44	MATERIALS AND METHODS — Immunohistochemistry	For immunocytochemistry analysis, the cultured cells were fixed using freshly prepared buffered 4%…
45	MATERIALS AND METHODS — Immunohistochemistry	Sigma, catalog #05-636, RRID: AB_309864), chicken anti-MAP2 (EMD Millipore, catalog #AB5543, RRID:…
46	MATERIALS AND METHODS — Image analysis	All images were acquired using Z stack maximal projection in Zeiss Zen blue software.
47	MATERIALS AND METHODS — Image analysis	To analyze microglial morphology at the single-cell level, we used the “FracLac plugin” in…
48	MATERIALS AND METHODS — Image analysis	using the box-counting software FracLac, representing the pixel mass distribution in microglia…
49	MATERIALS AND METHODS — Image analysis	The analysis of synaptic puncta density was performed on iNs at day 35. This analysis was conducted…
50	MATERIALS AND METHODS — RNA library construction, quality control, and sequencing	Total RNA from iPSC and iPSC-derived microglia was extracted using RNeasy Plus kit (QIAGEN, catalog…
51	MATERIALS AND METHODS — Analyses of genomic integrity using e-karyotyping analysis and G-band karyotyping analysis	The genomic integrity of all iPSC lines was assessed using eSNP-karyotyping analysis. The…
52	MATERIALS AND METHODS — Synaptosomes extraction and pHrodo red conjugation	Synaptosomes were extracted from iPSC-derived iNs at day 40 using Syn-PER synaptic protein…
53	MATERIALS AND METHODS — Phagocytosis assay	In the phagocytosis assay, human iPSC-derived microglia were seeded in a 96-well plate following a…
54	MATERIALS AND METHODS — Western blot	Synaptosomes were lysed using radioimmunoprecipitation assay (RIPA) buffer [50 mM tris-HCl, 150 mM…
55	MATERIALS AND METHODS — Western blot	The proteins were then diluted with 2X SDS loading buffer [4% SDS, 125 mM (pH 6.8) tris-HCl, 20%…
56	MATERIALS AND METHODS — Western blot	synaptotagmin 1, Santa Cruz Biotechnology, catalog #sc-136480; PSD95, Synaptic systems, catalog…
57	MATERIALS AND METHODS — Electrophysiology	Functional analyses of iN cells were conducted using whole-cell patch-clamp electrophysiology as…
58	MATERIALS AND METHODS — Statistical analysis	Statistical analyses were performed using GraphPad Prism version 10.0 (GraphPad Software, La Jolla,…

Citation	PMID	DOI	Status
A. Agrawal, S. J. Brislin, K. K. Bucholz, D. Dick, R. P. Hart, E. C. Johnson, J. Meyers, J. Salvatore, P. Slesinger; COGA Collaborators, L. Almasy, T. Foroud, A. Goate, V. Hesselbrock, J. Kramer, S. Kuperman, A. K. Merikangas, J. I. Nurnberger, J. Tischfield, H. J. Edenberg, B. Porjesz, The collaborative study on the genetics of alcoholism: Overview. Genes Brain Behav. 22, e12864 (2023).37736010 10.1111/gbb.12864PMC10550790	—	—	—
A. B. Hart, H. R. Kranzler, Alcohol dependence genetics: lessons learned from genome-wide association studies (GWAS) and post-GWAS analyses. Alcohol Clin. Exp. Res. 39, 1312–1327 (2015).26110981 10.1111/acer.12792PMC4515198	—	—	—
A. F. Carvalho, M. Heilig, A. Perez, C. Probst, J. Rehm, Alcohol use disorders. Lancet 394, 781–792 (2019).31478502 10.1016/S0140-6736(19)31775-1	—	—	—
A. Halikere, D. Popova, M. S. Scarnati, A. Hamod, M. R. Swerdel, J. C. Moore, J. A. Tischfield, R. P. Hart, Z. P. Pang, Addiction associated N40D mu-opioid receptor variant modulates synaptic function in human neurons. Mol. Psychiatry 25, 1406–1419 (2020).31481756 10.1038/s41380-019-0507-0PMC7051890	—	—	—
A. J. Boreland, A. C. Stillitano, H. C. Lin, Y. Abbo, R. P. Hart, P. Jiang, Z. P. Pang, A. B. Rabson, Dysregulated neuroimmune interactions and sustained type I interferon signaling after human immunodeficiency virus type 1 infection of human iPSC derived microglia and cerebral organoids. bioRxiv 563950 [Preprint] (2023).10.1016/j.isci.2024.109628PMC1101928638628961	—	—	—
A. Karperien, H. Ahammer, H. F. Jelinek, Quantitating the subtleties of microglial morphology with fractal analysis. Front. Cell Neurosci. 7, 3 (2013).23386810 10.3389/fncel.2013.00003PMC3558688	—	—	—
A. M. Jurga, M. Paleczna, K. Z. Kuter, Overview of general and discriminating markers of differential microglia phenotypes. Front. Cell. Neurosci. 14, 198 (2020).32848611 10.3389/fncel.2020.00198PMC7424058	—	—	—
A. Maximov, Z. P. Pang, D. G. Tervo, T. C. Südhof, Monitoring synaptic transmission in primary neuronal cultures using local extracellular stimulation. J. Neurosci. Methods 161, 75–87 (2007).17118459 10.1016/j.jneumeth.2006.10.009	—	—	—
A. Mortazavi, B. A. Williams, K. McCue, L. Schaeffer, B. Wold, Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods 5, 621–628 (2008).18516045 10.1038/nmeth.1226	—	—	—
A. Nimmerjahn, F. Kirchhoff, F. Helmchen, Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo. Science 308, 1314–1318 (2005).15831717 10.1126/science.1110647	—	—	—
A. Pellon, A. Ramirez-Garcia, X. Guruceaga, A. Zabala, I. Buldain, A. Antoran, J. Anguita, A. Rementeria, C. Matute, F. L. Hernando, Microglial immune response is impaired against the neurotropic fungus Lomentospora prolificans. Cell Microbiol. 20, e12847 (2018).29582549 10.1111/cmi.12847	—	—	—
A. R. Mantegazza, J. G. Magalhaes, S. Amigorena, M. S. Marks, Presentation of phagocytosed antigens by MHC class I and II. Traffic 14, 135–152 (2013).23127154 10.1111/tra.12026PMC3538944	—	—	—
A. S. Warden, S. A. Wolfe, S. Khom, F. P. Varodayan, R. R. Patel, M. Q. Steinman, M. Bajo, S. E. Montgomery, R. Vlkolinsky, T. Nadav, I. Polis, A. J. Roberts, R. D. Mayfield, R. A. Harris, M. Roberto, Microglia control escalation of drinking in alcohol-dependent mice: Genomic and synaptic drivers. Biol. Psychiatry 88, 910–921 (2020).32680583 10.1016/j.biopsych.2020.05.011PMC7674270	—	—	—
B. Verhulst, M. C. Neale, K. S. Kendler, The heritability of alcohol use disorders: A meta-analysis of twin and adoption studies. Psychol. Med. 45, 1061–1072 (2015).25171596 10.1017/S0033291714002165PMC4345133	—	—	—
C. W. Law, Y. Chen, W. Shi, G. K. Smyth, voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29 (2014).24485249 10.1186/gb-2014-15-2-r29PMC4053721	—	—	—
D. Gosselin, D. Skola, N. G. Coufal, I. R. Holtman, J. C. M. Schlachetzki, E. Sajti, B. N. Jaeger, C. O’Connor, C. Fitzpatrick, M. P. Pasillas, M. Pena, A. Adair, D. D. Gonda, M. L. Levy, R. M. Ransohoff, F. H. Gage, C. K. Glass, An environment-dependent transcriptional network specifies human microglia identity. Science 356, eaal3222 (2017).28546318 10.1126/science.aal3222PMC5858585	—	—	—
D. H. Geschwind, J. Flint, Genetics and genomics of psychiatric disease. Science 349, 1489–1494 (2015).26404826 10.1126/science.aaa8954PMC4694563	—	—	—
D. Lai, E. C. Johnson, S. Colbert, G. Pandey, G. Chan, L. Bauer, M. W. Francis, V. Hesselbrock, C. Kamarajan, J. Kramer, W. Kuang, S. Kuo, S. Kuperman, Y. Liu, V. McCutcheon, Z. Pang, M. H. Plawecki, M. Schuckit, J. Tischfield, L. Wetherill, Y. Zang, H. J. Edenberg, B. Porjesz, A. Agrawal, T. Foroud, Evaluating risk for alcohol use disorder: Polygenic risk scores and family history. Alcohol Clin. Exp. Res. 46, 374–383 (2022).35267208 10.1111/acer.14772PMC8928056	—	—	—
D. Lvovs, O. O. Favorova, A. V. Favorov, A polygenic approach to the study of polygenic diseases. Acta Naturae 4, 59–71 (2012).23150804 PMC3491892	—	—	—
D. P. Schafer, E. K. Lehrman, A. G. Kautzman, R. Koyama, A. R. Mardinly, R. Yamasaki, R. M. Ransohoff, M. E. Greenberg, B. A. Barres, B. Stevens, Microglia sculpt postnatal neural circuits in an activity and complement-dependent manner. Neuron 74, 691–705 (2012).22632727 10.1016/j.neuron.2012.03.026PMC3528177	—	—	—
D. Popova, I. Gameiro-Ros, M. M. Youssef, P. Zalamea, A. D. Morris, I. Prytkova, A. Jadali, K. Y. Kwan, C. Kamarajan, J. E. Salvatore, X. Xuei, D. B. Chorlian, B. Porjesz, S. Kuperman, D. M. Dick, A. Goate, H. J. Edenberg, J. A. Tischfield, Z. P. Pang, P. A. Slesinger, R. P. Hart, Alcohol reverses the effects of KCNJ6 (GIRK2) noncoding variants on excitability of human glutamatergic neurons. Mol. Psychiatry 28, 746–758 (2023).36207584 10.1038/s41380-022-01818-xPMC9542475	—	—	—
D. S. Svoboda, M. I. Barrasa, J. Shu, R. Rietjens, S. Zhang, M. Mitalipova, P. Berube, D. Fu, L. D. Shultz, G. W. Bell, R. Jaenisch, Human iPSC-derived microglia assume a primary microglia-like state after transplantation into the neonatal mouse brain. Proc. Natl. Acad. Sci. U.S.A. 116, 25293–25303 (2019).31772018 10.1073/pnas.1913541116PMC6911218	—	—	—
Diagnostic and statistical manual of mental disorders: DSM-5™ (American Psychiatric Publishing Inc., ed. 5, 2013), pp. 947.	—	—	—
E. C. Johnson, J. E. Salvatore, D. Lai, A. K. Merikangas, J. I. Nurnberger, J. A. Tischfield, X. Xuei, C. Kamarajan, L. Wetherill, J. P. Rice, J. R. Kramer, S. Kuperman, T. Foroud, P. A. Slesinger, A. M. Goate, B. Porjesz, D. M. Dick, H. J. Edenberg, A. Agrawal, The collaborative study on the genetics of alcoholism: Genetics. Genes Brain Behav. 22, e12856 (2023).37387240 10.1111/gbb.12856PMC10550788	—	—	—
E. K. Erickson, E. K. Grantham, A. S. Warden, R. A. Harris, Neuroimmune signaling in alcohol use disorder. Pharmacol. Biochem. Behav. 177, 34–60 (2019).30590091 10.1016/j.pbb.2018.12.007PMC6946054	—	—	—
E. K. Erickson, Y. A. Blednov, R. A. Harris, R. D. Mayfield, Glial gene networks associated with alcohol dependence. Sci. Rep. 9, 10949 (2019).31358844 10.1038/s41598-019-47454-4PMC6662804	—	—	—
E. Layman, J. M. Parrott, H. Y. Lee, Protocol for assessing phagocytosis activity in cultured primary murine microglia. STAR Protoc. 3, 101881 (2022).36595893 10.1016/j.xpro.2022.101881PMC9730218	—	—	—
E. M. Abud, R. N. Ramirez, E. S. Martinez, L. M. Healy, C. H. H. Nguyen, S. A. Newman, A. V. Yeromin, V. M. Scarfone, S. E. Marsh, C. Fimbres, C. A. Caraway, G. M. Fote, A. M. Madany, A. Agrawal, R. Kayed, K. H. Gylys, M. D. Cahalan, B. J. Cummings, J. P. Antel, A. Mortazavi, M. J. Carson, W. W. Poon, M., Blurton-Jones, iPSC-derived human microglia-like cells to study neurological diseases. Neuron 94, 278–293.e9 (2017).28426964 10.1016/j.neuron.2017.03.042PMC5482419	—	—	—
E. N. Oni, A. Halikere, G. Li, A. J. Toro-Ramos, M. R. Swerdel, J. L. Verpeut, J. C. Moore, N. T. Bello, L. J. Bierut, A. Goate, J. A. Tischfield, Z. P. Pang, R. P. Hart, Increased nicotine response in iPSC-derived human neurons carrying the CHRNA5 N398 allele. Sci. Rep. 6, 34341 (2016).27698409 10.1038/srep34341PMC5048107	—	—	—
G. Ni, J. Zeng, J. A. Revez, Y. Wang, Z. Zheng, T. Ge, R. Restuadi, J. Kiewa, D. R. Nyholt, J. R. I. Coleman, J. W. Smoller, J. Yang, P. M. Visscher, N. R. Wray, A comparison of ten polygenic score methods for psychiatric disorders applied across multiple cohorts. Biol. Psychiatry 90, 611–620 (2021).34304866 10.1016/j.biopsych.2021.04.018PMC8500913	—	—	—
G. R. B. Saunders, X. Wang, F. Chen, S.-K. Jang, M. Liu, C. Wang, S. Gao, Y. Jiang, C. Khunsriraksakul, J. M. Otto, C. Addison, M. Akiyama, C. M. Albert, F. Aliev, A. Alonso, D. K. Arnett, A. E. Ashley-Koch, A. A. Ashrani, K. C. Barnes, R. G. Barr, T. M. Bartz, D. M. Becker, L. F. Bielak, E. J. Benjamin, J. C. Bis, G. Bjornsdottir, J. Blangero, E. R. Bleecker, J. D. Boardman, E. Boerwinkle, D. I. Boomsma, M. P. Boorgula, D. W. Bowden, J. A. Brody, B. E. Cade, D. I. Chasman, S. Chavan, Y.-D. I. Chen, Z. Chen, I. Cheng, M. H. Cho, H. Choquet, J. W. Cole, M. C. Cornelis, F. Cucca, J. E. Curran, M. de Andrade, D. M. Dick, A. R. Docherty, R. Duggirala, C. B. Eaton, M. A. Ehringer, T. Esko, J. D. Faul, L. F. Silva, E. Fiorillo, M. Fornage, B. I. Freedman, M. E. Gabrielsen, M. E. Garrett, S. A. Gharib, C. Gieger, N. Gillespie, D. C. Glahn, S. D. Gordon, C. C. Gu, D. Gu, D. F. Gudbjartsson, X. Guo, J. Haessler, M. E. Hall, T. Haller, K. M. Harris, J. He, P. Herd, J. K. Hewitt, I. Hickie, B. Hidalgo, J. E. Hokanson, C. Hopfer, J. J. Hottenga, L. Hou, H. Huang, Y.-J. Hung, D. J. Hunter, K. Hveem, S.-J. Hwang, C.-M. Hwu, W. Iacono, M. R. Irvin, Y. H. Jee, E. O. Johnson, Y. Y. Joo, E. Jorgenson, A. E. Justice, Y. Kamatani, R. C. Kaplan, J. Kaprio, S. L. R. Kardia, M. C. Keller, T. N. Kelly, C. Kooperberg, T. Korhonen, P. Kraft, K. Krauter, J. Kuusisto, M. Laakso, J. Lasky-Su, W.-J. Lee, J. J. Lee, D. Levy, L. Li, K. Li, Y. Li, K. Lin, P. A. Lind, C. Liu, D. M. Lloyd-Jones, S. M. Lutz, J. Ma, R. Mägi, A. Manichaikul, N. G. Martin, R. Mathur, N. Matoba, P. F. Mc Ardle, M. M. Gue, M. B. Mc Queen, S. E. Medland, A. Metspalu, D. A. Meyers, I. Y. Millwood, B. D. Mitchell, K. L. Mohlke, M. Moll, M. E. Montasser, A. C. Morrison, A. Mulas, J. B. Nielsen, K. E. North, E. C. Oelsner, Y. Okada, V. Orrù, N. D. Palmer, T. Palviainen, A. Pandit, S. L. Park, U. Peters, A. Peters, P. A. Peyser, T. J. C. Polderman, N. Rafaels, S. Redline, R. M. Reed, A. P. Reiner, J. P. Rice, S. S. Rich, N. E. Richmond, C. Roan, J. I. Rotter, M. N. Rueschman, V. Runarsdottir, N. L. Saccone, D. A. Schwartz, A. H. Shadyab, J. Shi, S. S. Shringarpure, K. Sicinski, A. H. Skogholt, J. A. Smith, N. L. Smith, N. Sotoodehnia, M. C. Stallings, H. Stefansson, K. Stefansson, J. A. Stitzel, X. Sun, M. Syed, R. Tal-Singer, A. E. Taylor, K. D. Taylor, M. J. Telen, K. K. Thai, H. Tiwari, C. Turman, T. Tyrfingsson, T. L. Wall, R. G. Walters, D. R. Weir, S. T. Weiss, W. B. White, J. B. Whitfield, K. L. Wiggins, G. Willemsen, C. J. Willer, B. S. Winsvold, H. Xu, L. R. Yanek, J. Yin, K. L. Young, K. A. Young, B. Yu, W. Zhao, W. Zhou, S. Zöllner, L. Zuccolo; 23andMe Research Team; The Biobank Japan Project, C. Batini, A. W. Bergen, L. J. Bierut, S. P. David, S. A. Gagliano Taliun, D. B. Hancock, B. Jiang, M. R. Munafò, T. E. Thorgeirsson, D. J. Liu, S. Vrieze, Genetic diversity fuels gene discovery for tobacco and alcohol use. Nature 612, 720–724 (2022).36477530 10.1038/s41586-022-05477-4PMC9771818	—	—	—
G. Yu, L. G. Wang, Y. Han, Q. Y. He, clusterProfiler: An R package for comparing biological themes among gene clusters. Omics 16, 284–287 (2012).22455463 10.1089/omi.2011.0118PMC3339379	—	—	—
H. J. Edenberg, J. N. McClintick, alcohol dehydrogenases, aldehyde dehydrogenases, and alcohol use disorders: A critical review. Alcohol Clin. Exp. Res. 42, 2281–2297 (2018).30320893 10.1111/acer.13904PMC6286250	—	—	—
H. Keren-Shaul, A. Spinrad, A. Weiner, O. Matcovitch-Natan, R. Dvir-Szternfeld, T. K. Ulland, E. David, K. Baruch, D. Lara-Astaiso, B. Toth, S. Itzkovitz, M. Colonna, M. Schwartz, I. Amit, A unique microglia type associated with restricting development of alzheimer’s disease. Cell 169, 1276–1290.e17 (2017).28602351 10.1016/j.cell.2017.05.018	—	—	—
H. Kettenmann, U. K. Hanisch, M. Noda, A. Verkhratsky, Physiology of microglia. Physiol. Rev. 91, 461–553 (2011).21527731 10.1152/physrev.00011.2010	—	—	—
H. Mathys, Z. Peng, C. A. Boix, M. B. Victor, N. Leary, S. Babu, G. Abdelhady, X. Jiang, A. P. Ng, K. Ghafari, A. K. Kunisky, J. Mantero, K. Galani, V. N. Lohia, G. E. Fortier, Y. Lotfi, J. Ivey, H. P. Brown, P. R. Patel, N. Chakraborty, J. I. Beaudway, E. J. Imhoff, C. F. Keeler, M. M. McChesney, H. H. Patel, S. P. Patel, M. T. Thai, D. A. Bennett, M. Kellis, L. H. Tsai, Single-cell atlas reveals correlates of high cognitive function, dementia, and resilience to Alzheimer’s disease pathology. Cell 186, 4365–4385.e27 (2023).37774677 10.1016/j.cell.2023.08.039PMC10601493	—	—	—
H. R. Kranzler, H. Zhou, R. L. Kember, R. Vickers Smith, A. C. Justice, S. Damrauer, P. S. Tsao, D. Klarin, A. Baras, J. Reid, J. Overton, D. J. Rader, Z. Cheng, J. P. Tate, W. C. Becker, J. Concato, K. Xu, R. Polimanti, H. Zhao, J. Gelernter, Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat. Commun. 10, 1499 (2019).30940813 10.1038/s41467-019-09480-8PMC6445072	—	—	—
H. S. Yang, K. D. Onos, K. Choi, K. J. Keezer, D. A. Skelly, G. W. Carter, G. R. Howell, Natural genetic variation determines microglia heterogeneity in wild-derived mouse models of Alzheimer’s disease. Cell Rep. 34, 108739 (2021).33567283 10.1016/j.celrep.2021.108739PMC7937391	—	—	—
I. Gameiro-Ros, D. Popova, I. Prytkova, Z. P. Pang, Y. Liu, D. Dick, K. K. Bucholz, A. Agrawal, B. Porjesz, A. M. Goate, X. Xuei, C. Kamarajan; COGA Collaborators, J. A. Tischfield, H. J. Edenberg, P. A. Slesinger, R. P. Hart, 5. Collaborative study on the genetics of alcoholism: Functional genomics. Genes Brain Behav. 22, e12855 (2023).37533187 10.1111/gbb.12855PMC10550792	—	—	—
J. A. Fantuzzo, V. R. Mirabella, A. H. Hamod, R. P. Hart, J. D. Zahn, Z. P. Pang, Intellicount: High-throughput quantification of fluorescent synaptic protein puncta by machine learning. eNeuro 4, ENEURO.0219-17.2017 (2017).10.1523/ENEURO.0219-17.2017PMC571824629218324	—	—	—
J. A. Pasman, K. J. H. Verweij, J. M. Vink, Systematic review of polygenic gene-environment interaction in tobacco, alcohol, and cannabis use. Behav. Genet. 49, 349–365 (2019).31111357 10.1007/s10519-019-09958-7PMC6554261	—	—	—
J. Cornell, S. Salinas, H. Y. Huang, M. Zhou, Microglia regulation of synaptic plasticity and learning and memory. Neural Regen. Res. 17, 705–716 (2022).34472455 10.4103/1673-5374.322423PMC8530121	—	—	—
J. D. Deak, E. C. Johnson, Genetics of substance use disorders: A review. Psychol. Med. 51, 2189–2200 (2021).33879270 10.1017/S0033291721000969PMC8477224	—	—	—
J. E. Savage, J. E. Salvatore, F. Aliev, A. C. Edwards, M. Hickman, K. S. Kendler, J. Macleod, A. Latvala, A. Loukola, J. Kaprio, R. J. Rose, G. Chan, V. Hesselbrock, B. T. Webb, A. Adkins, T. B. Bigdeli, B. P. Riley, D. M. Dick, Polygenic risk score prediction of alcohol dependence symptoms across population-based and clinically ascertained samples. Alcohol Clin. Exp. Res. 42, 520–530 (2018).29405378 10.1111/acer.13589PMC5832589	—	—	—
J. F. Henriques, C. C. Portugal, T. Canedo, J. B. Relvas, T. Summavielle, R. Socodato, Microglia and alcohol meet at the crossroads: Microglia as critical modulators of alcohol neurotoxicity. Toxicol. Lett. 283, 21–31 (2018).29129797 10.1016/j.toxlet.2017.11.002	—	—	—
J. He, F. T. Crews, Increased MCP-1 and microglia in various regions of the human alcoholic brain. Exp. Neurol. 210, 349–358 (2008).18190912 10.1016/j.expneurol.2007.11.017PMC2346541	—	—	—
J. K. Sun, D. Wu, G. C. Wong, T. M. Lau, M. Yang, R. P. Hart, K. M. Kwan, H. Y. E. Chan, H. M. Chow, Chronic alcohol metabolism results in DNA repair infidelity and cell cycle-induced senescence in neurons. Aging Cell 22, e13772 (2023).36691110 10.1111/acel.13772PMC9924945	—	—	—
J. Su, S. I. Kuo, F. Aliev, J. A. Rabinowitz, B. Jamil, G. Chan, H. J. Edenberg, M. Francis, V. Hesselbrock, C. Kamarajan, S. Kinreich, J. Kramer, D. Lai, V. McCutcheon, J. Meyers, A. Pandey, G. Pandey, M. H. Plawecki, M. Schuckit, J. Tischfield, D. M. Dick, Alcohol use polygenic risk score, social support, and alcohol use among European American and African American adults, in Development and Psychopathology (Cambridge Univ. Press, 2023), pp. 1–13.10.1017/S0954579423001141PMC1098505037781861	—	—	—
J. V. Haure-Mirande, M. Wang, M. Audrain, T. Fanutza, S. H. Kim, S. Heja, B. Readhead, J. T. Dudley, R. D. Blitzer, E. E. Schadt, B. Zhang, S. Gandy, M. E. Ehrlich, Correction: Integrative approach to sporadic Alzheimer’s disease: Deficiency of TYROBP in cerebral Aβ amyloidosis mouse normalizes clinical phenotype and complement subnetwork molecular pathology without reducing Aβ burden. Mol. Psychiatry 24, 472 (2019).30464330 10.1038/s41380-018-0301-4PMC7608234	—	—	—
K. G. Chartier, K. J. Karriker-Jaffe, C. R. Cummings, K. S. Kendler, Review: Environmental influences on alcohol use: Informing research on the joint effects of genes and the environment in diverse U.S. populations. Am. J. Addict 26, 446–460 (2017).28117924 10.1111/ajad.12478PMC5695556	—	—	—
K. Young, H. Morrison, Quantifying microglia morphology from photomicrographs of immunohistochemistry prepared tissue using ImageJ. J. Vis. Exp. 136, 57648 (2018).10.3791/57648PMC610325629939190	—	—	—
L. De Filippis, A. Halikere, H. McGowan, J. C. Moore, J. A. Tischfield, R. P. Hart, Z. P. Pang, Ethanol-mediated activation of the NLRP3 inflammasome in iPS cells and iPS cells-derived neural progenitor cells. Mol. Brain 9, 51 (2016).27160314 10.1186/s13041-016-0221-7PMC4862119	—	—	—
L. G. Chastain, D. K. Sarkar, Role of microglia in regulation of ethanol neurotoxic action. Int. Rev. Neurobiol. 118, 81–103 (2014).25175862 10.1016/B978-0-12-801284-0.00004-X	—	—	—
L. J. Lawson, V. H. Perry, P. Dri, S. Gordon, Heterogeneity in the distribution and morphology of microglia in the normal adult mouse brain. Neuroscience 39, 151–170 (1990).2089275 10.1016/0306-4522(90)90229-w	—	—	—
L. J. Mah, A. El-Osta, T. C. Karagiannis, γH2AX: A sensitive molecular marker of DNA damage and repair. Leukemia 24, 679–686 (2010).20130602 10.1038/leu.2010.6	—	—	—
L. Lan, H. Wang, X. Zhang, Q. Shen, X. Li, L. He, X. Rong, J. Peng, J. Mo, Y. Peng, Chronic exposure of alcohol triggers microglia-mediated synaptic elimination inducing cognitive impairment. Exp. Neurol. 353, 114061 (2022).35367455 10.1016/j.expneurol.2022.114061	—	—	—
L. Wang, V. R. Mirabella, R. Dai, X. Su, R. Xu, A. Jadali, M. Bernabucci, I. Singh, Y. Chen, J. Tian, P. Jiang, K. Y. Kwan, C. Pak, C. Liu, D. Comoletti, R. P. Hart, C. Chen, T. C. Südhof, Z. P. Pang, Analyses of the autism-associated neuroligin-3 R451C mutation in human neurons reveal a gain-of-function synaptic mechanism. Mol. Psychiatry 29, 1620–1635 (2022).36280753 10.1038/s41380-022-01834-xPMC10123180	—	—	—
M. A. S. Khan, S. L. Chang, Alcohol and the brain-gut axis: The involvement of microglia and enteric glia in the process of neuro-enteric inflammation. Cells 12, 2475 (2023).37887319 10.3390/cells12202475PMC10605902	—	—	—
M. Colonna, O. Butovsky, Microglia function in the central nervous system during health and neurodegeneration. Annu. Rev. Immunol. 35, 441–468 (2017).28226226 10.1146/annurev-immunol-051116-052358PMC8167938	—	—	—
M. D. M. Fernandez-Arjona, J. M. Grondona, P. Granados-Duran, P. Fernandez-Llebrez, M. D. Lopez-Avalos, Microglia morphological categorization in a rat model of neuroinflammation by hierarchical cluster and principal components analysis. Front. Cell. Neurosci. 11, 235 (2017).28848398 10.3389/fncel.2017.00235PMC5550745	—	—	—
M. E. Deerhake, M. L. Shinohara, Emerging roles of Dectin-1 in noninfectious settings and in the CNS. Trends Immunol. 42, 891–903 (2021).34489167 10.1016/j.it.2021.08.005PMC8487984	—	—	—
M. E. Price, B. A. McCool, Chronic alcohol dysregulates glutamatergic function in the basolateral amygdala in a projection-and sex-specific manner. Front. Cell Neurosci. 16, 857550 (2022).35496915 10.3389/fncel.2022.857550PMC9050109	—	—	—
M. E. Ritchie, B. Phipson, D. Wu, Y. Hu, C. W. Law, W. Shi, G. K. Smyth, limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).25605792 10.1093/nar/gkv007PMC4402510	—	—	—
M. J. Dolan, M. Therrien, S. Jereb, T. Kamath, V. Gazestani, T. Atkeson, S. E. Marsh, A. Goeva, N. M. Lojek, S. Murphy, C. M. White, J. Joung, B. Liu, F. Limone, K. Eggan, N. Hacohen, B. E. Bernstein, C. K. Glass, V. Leinonen, M. Blurton-Jones, F. Zhang, C. B. Epstein, E. Z. Macosko, B. Stevens, Exposure of iPSC-derived human microglia to brain substrates enables the generation and manipulation of diverse transcriptional states in vitro. Nat. Immunol. 24, 1382–1390 (2023).37500887 10.1038/s41590-023-01558-2PMC10382323	—	—	—
M. Jin, R. Xu, L. Wang, M. M. Alam, Z. Ma, S. Zhu, A. C. Martini, A. Jadali, M. Bernabucci, P. Xie, K. Y. Kwan, Z. P. Pang, E. Head, Y. Liu, R. P. Hart, P. Jiang, Type-I-interferon signaling drives microglial dysfunction and senescence in human iPSC models of Down syndrome and Alzheimer’s disease. Cell Stem Cell 29, 1135–1153.e8 (2022).35803230 10.1016/j.stem.2022.06.007PMC9345168	—	—	—
M. Jin, Z. Ma, P. Jiang, Generation of iPSC-based human-mouse microglial brain chimeras to study senescence of human microglia. STAR Protoc. 3, 101847 (2022).36595906 10.1016/j.xpro.2022.101847PMC9667309	—	—	—
M. Kapoor, J. C. Wang, S. P. Farris, Y. Liu, J. McClintick, I. Gupta, J. L. Meyers, S. Bertelsen, M. Chao, J. Nurnberger, J. Tischfield, O. Harari, L. Zeran, V. Hesselbrock, L. Bauer, T. Raj, B. Porjesz, A. Agrawal, T. Foroud, H. J. Edenberg, R. D. Mayfield, A. Goate, Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism. Transl. Psychiatry 9, 89 (2019).30765688 10.1038/s41398-019-0384-yPMC6376002	—	—	—
M. Prinz, S. Jung, J. Priller, Microglia biology: One century of evolving concepts. Cell 179, 292–311 (2019).31585077 10.1016/j.cell.2019.08.053	—	—	—
M. S. Scarnati, A. Halikere, Z. P. Pang, Using human stem cells as a model system to understand the neural mechanisms of alcohol use disorders: Current status and outlook. Alcohol 74, 83–93 (2019).30087005 10.1016/j.alcohol.2018.03.008PMC6167197	—	—	—
M. S. Scarnati, A. J. Boreland, M. Joel, R. P. Hart, Z. P. Pang, Differential sensitivity of human neurons carrying mu opioid receptor (MOR) N40D variants in response to ethanol. Alcohol 87, 97–109 (2020).32561311 10.1016/j.alcohol.2020.05.004PMC7958146	—	—	—
M. S. Scarnati, A. J. Boreland, M. Joel, R. P. Hart, Z. P. Pang, Differential sensitivity of human neurons carrying μ opioid receptor (MOR) N40D variants in response to ethanol. Alcohol 87, 97–109 (2020).32561311 10.1016/j.alcohol.2020.05.004PMC7958146	—	—	—
N. R. Wray, S. H. Lee, D. Mehta, A. A. Vinkhuyzen, F. Dudbridge, C. M. Middeldorp, Research review: Polygenic methods and their application to psychiatric traits. J. Child. Psychol. Psychiatry 55, 1068–1087 (2014).25132410 10.1111/jcpp.12295	—	—	—
P. B. Barr, A. Ksinan, J. Su, E. C. Johnson, J. L. Meyers, L. Wetherill, A. Latvala, F. Aliev, G. Chan, S. Kuperman, J. Nurnberger, C. Kamarajan, A. Anokhin, A. Agrawal, R. J. Rose, H. J. Edenberg, M. Schuckit, J. Kaprio, D. M. Dick, Using polygenic scores for identifying individuals at increased risk of substance use disorders in clinical and population samples. Transl. Psychiatry 10, 196 (2020).32555147 10.1038/s41398-020-00865-8PMC7303212	—	—	—
P. M. Visscher, N. R. Wray, Q. Zhang, P. Sklar, M. I. McCarthy, M. A. Brown, J. Yang, 10 Years of GWAS discovery: Biology, function, and translation. Am. J. Hum. Genet. 101, 5–22 (2017).28686856 10.1016/j.ajhg.2017.06.005PMC5501872	—	—	—
P. Mews, G. Egervari, R. Nativio, S. Sidoli, G. Donahue, S. I. Lombroso, D. C. Alexander, S. L. Riesche, E. A. Heller, E. J. Nestler, B. A. Garcia, S. L. Berger, Alcohol metabolism contributes to brain histone acetylation. Nature 574, 717–721 (2019).31645761 10.1038/s41586-019-1700-7PMC6907081	—	—	—
Q. Li, D. Liu, F. Pan, C. S. H. Ho, R. C. M. Ho, Ethanol exposure induces microglia activation and neuroinflammation through TLR4 activation and SENP6 modulation in the adolescent rat hippocampus. Neural Plast. 2019, 1648736 (2019).31781182 10.1155/2019/1648736PMC6874951	—	—	—
R. Lieberman, E. S. Levine, H. R. Kranzler, C. Abreu, J. Covault, Pilot study of iPS-derived neural cells to examine biologic effects of alcohol on human neurons in vitro. Alcohol Clin. Exp. Res. 36, 1678–1687 (2012).22486492 10.1111/j.1530-0277.2012.01792.xPMC3424319	—	—	—
R. Xu, A. J. Boreland, X. Li, C. Erickson, M. Jin, C. Atkins, Z. Pang, B. P. Daniels, P. Jiang, Developing human pluripotent stem cell-based cerebral organoids with a controllable microglia ratio for modeling brain development and pathology. Stem Cell Rep. 16, 1923–1937 (2020).10.1016/j.stemcr.2021.06.011PMC836510934297942	—	—	—
R. Xu, X. Li, A. J. Boreland, A. Posyton, K. Kwan, R. P. Hart, P. Jiang, Human iPSC-derived mature microglia retain their identity and functionally integrate in the chimeric mouse brain. Nat. Commun. 11, 1577 (2020).32221280 10.1038/s41467-020-15411-9PMC7101330	—	—	—
S. A. Marshall, C. R. Geil, K. Nixon, Prior binge ethanol exposure potentiates the microglial response in a model of alcohol-induced neurodegeneration. Brain Sci. 6, 16 (2016).27240410 10.3390/brainsci6020016PMC4931493	—	—	—
S. A. Marshall, J. A. McClain, M. L. Kelso, D. M. Hopkins, J. R. Pauly, K. Nixon, Microglial activation is not equivalent to neuroinflammation in alcohol-induced neurodegeneration: The importance of microglia phenotype. Neurobiol. Dis. 54, 239–251 (2013).23313316 10.1016/j.nbd.2012.12.016PMC3629000	—	—	—
S. Bang, C. R. Donnelly, X. Luo, M. Toro-Moreno, X. Tao, Z. Wang, S. Chandra, A. V. Bortsov, E. R. Derbyshire, R. R. Ji, Activation of GPR37 in macrophages confers protection against infection-induced sepsis and pain-like behaviour in mice. Nat. Commun. 12, 1704 (2021).33731716 10.1038/s41467-021-21940-8PMC7969930	—	—	—
S. Mukherjee, M. A. Cabrera, N. I. Boyadjieva, G. Berger, B. Rousseau, D. K. Sarkar, Alcohol increases exosome release from microglia to promote complement C1q-induced cellular death of proopiomelanocortin neurons in the hypothalamus in a rat model of fetal alcohol spectrum disorders. J. Neurosci. 40, 7965–7979 (2020).32887744 10.1523/JNEUROSCI.0284-20.2020PMC7548688	—	—	—
S. R. Guttikonda, L. Sikkema, J. Tchieu, N. Saurat, R. M. Walsh, O. Harschnitz, G. Ciceri, M. Sneeboer, L. Mazutis, M. Setty, P. Zumbo, D. Betel, L. D. de Witte, D. Pe’er, L. Studer, Fully defined human pluripotent stem cell-derived microglia and tri-culture system model C3 production in Alzheimer’s disease. Nat. Neurosci. 24, 343–354 (2021).33558694 10.1038/s41593-020-00796-zPMC8382543	—	—	—
S. Zhao, A. D. Umpierre, L. J. Wu, Tuning neural circuits and behaviors by microglia in the adult brain. Trends Neurosci. 47, 181–194 (2024).38245380 10.1016/j.tins.2023.12.003PMC10939815	—	—	—
T. F. Galatro, I. R. Holtman, A. M. Lerario, I. D. Vainchtein, N. Brouwer, P. R. Sola, M. M. Veras, T. F. Pereira, R. E. P. Leite, T. Möller, P. D. Wes, M. C. Sogayar, J. D. Laman, W. den Dunnen, C. A. Pasqualucci, S. M. Oba-Shinjo, E. Boddeke, S. K. N. Marie, B. J. L. Eggen, Transcriptomic analysis of purified human cortical microglia reveals age-associated changes. Nat. Neurosci. 20, 1162–1171 (2017).28671693 10.1038/nn.4597	—	—	—
T. J. Walter, F. T. Crews, Microglial depletion alters the brain neuroimmune response to acute binge ethanol withdrawal. J. Neuroinflammation 14, 86 (2017).28427424 10.1186/s12974-017-0856-zPMC5439231	—	—	—
T. K. Lim, E. S. Ruthazer, Microglial trogocytosis and the complement system regulate axonal pruning in vivo. elife 10, e62167 (2021).33724186 10.7554/eLife.62167PMC7963485	—	—	—
T. Matsudaira, M. Prinz, Life and death of microglia: Mechanisms governing microglial states and fates. Immunol. Lett. 245, 51–60 (2022).35413354 10.1016/j.imlet.2022.04.001	—	—	—
T. R. Hammond, C. Dufort, L. Dissing-Olesen, S. Giera, A. Young, A. Wysoker, A. J. Walker, F. Gergits, M. Segel, J. Nemesh, S. E. Marsh, A. Saunders, E. Macosko, F. Ginhoux, J. Chen, R. J. M. Franklin, X. Piao, S. A. McCarroll, B. Stevens, Single-cell RNA sequencing of microglia throughout the mouse lifespan and in the injured brain reveals complex cell-state changes. Immunity 50, 253–271.e6 (2019).30471926 10.1016/j.immuni.2018.11.004PMC6655561	—	—	—
T. Vierbuchen, A. Ostermeier, Z. P. Pang, Y. Kokubu, T. C. Sudhof, M. Wernig, Direct conversion of fibroblasts to functional neurons by defined factors. Nature 463, 1035–1041 (2010).20107439 10.1038/nature08797PMC2829121	—	—	—
U. Eyo, A. V. Molofsky, Defining microglial-synapse interactions. Science 381, 1155–1156 (2023).37708287 10.1126/science.adh7906	—	—	—
U. Weissbein, M. Schachter, D. Egli, N. Benvenisty, Analysis of chromosomal aberrations and recombination by allelic bias in RNA-seq. Nat. Commun. 7, 12144 (2016).27385103 10.1038/ncomms12144PMC4941052	—	—	—
V. H. Perry, A revised view of the central nervous system microenvironment and major histocompatibility complex class II antigen presentation. J. Neuroimmunol. 90, 113–121 (1998).9817438 10.1016/s0165-5728(98)00145-3	—	—	—
V. Maneu, A. Yáñez, C. Murciano, A. Molina, M. L. Gil, D. Gozalbo, Dectin-1 mediates in vitro phagocytosis of Candida albicans yeast cells by retinal microglia. FEMS Immunol. Med. Microbiol. 63, 148–150 (2011).21668824 10.1111/j.1574-695X.2011.00829.x	—	—	—
W. S. Cleveland, Robust locally weighted regression and smoothing scatterplots. J. Am. Stat. Assoc. 74, 829–836 (1979).	—	—	—
Y. Guo, Y. Chen, S. Carreon, M. Qiang, Chronic intermittent ethanol exposure and its removal induce a different miRNA expression pattern in primary cortical neuronal cultures. Alcohol Clin. Exp. Res. 36, 1058–1066 (2012).22141737 10.1111/j.1530-0277.2011.01689.xPMC3307858	—	—	—
Y. Hao, S. Hao, E. Andersen-Nissen, W. M. Mauck III, S. Zheng, A. Butler, M. J. Lee, A. J. Wilk, C. Darby, M. Zager, P. Hoffman, M. Stoeckius, E. Papalexi, E. P. Mimitou, J. Jain, A. Srivastava, T. Stuart, L. M. Fleming, B. Yeung, A. J. Rogers, J. M. McElrath, C. A. Blish, R. Gottardo, P. Smibert, R. Satija, Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e29 (2021).34062119 10.1016/j.cell.2021.04.048PMC8238499	—	—	—
Y. Liu, X. Shen, Y. Zhang, X. Zheng, C. Cepeda, Y. Wang, S. Duan, X. Tong, Interactions of glial cells with neuronal synapses, from astrocytes to microglia and oligodendrocyte lineage cells. Glia 71, 1383–1401 (2023).36799296 10.1002/glia.24343	—	—	—
Y. Wang, X. Zhang, Q. Song, Y. Hou, J. Liu, Y. Sun, P. Wang, Characterization of the chromatin accessibility in an Alzheimer’s disease (AD) mouse model. Alzheimers Res. Ther. 12, 29 (2020).32293531 10.1186/s13195-020-00598-2PMC7092509	—	—	—
Y. Zhang, C. Pak, Y. Han, H. Ahlenius, Z. Zhang, S. Chanda, S. Marro, C. Patzke, C. Acuna, J. Covy, W. Xu, N. Yang, T. Danko, L. Chen, M. Wernig, T. C. Südhof, Rapid single-step induction of functional neurons from human pluripotent stem cells. Neuron 78, 785–798 (2013).23764284 10.1016/j.neuron.2013.05.029PMC3751803	—	—	—
Z. P. Pang, N. Yang, T. Vierbuchen, A. Ostermeier, D. R. Fuentes, T. Q. Yang, A. Citri, V. Sebastiano, S. Marro, T. C. Südhof, M. Wernig, Induction of human neuronal cells by defined transcription factors. Nature 476, 220–223 (2011).21617644 10.1038/nature10202PMC3159048	—	—	—

Title	Authors	Journal	Year	Link
Advancing substance use disorder biology by studying underlying gene x environment interactions.	Sidamon-Eristoff AE et al.	—	2026	→
Human microglia in brain assembloids display region-specific diversity and respond to hyperexcitable neurons carrying <i>SCN2A</i> mutation.	Wu J et al.	—	2026	→
Transcription factors implicated in substance use disorder, from immediate early genes to altered gene expression.	Orr E et al.	—	2026	→
Uncovering NMDA receptor-mediated high firing activity in excitatory human neurons.	Gameiro-Ros I et al.	—	2026	→
Microglial activation drives neuronal dysregulation in alcohol-induced seizure susceptibility.	Zhang S et al.	—	2025	→
Molecular mechanisms of 10-butyl ether minocycline, a novel nonantibiotic tetracycline, as a potential treatment for inflammatory and neuroimmune-related disorders.	Shaik AA et al.	—	2025	→
Study on the protective effects and mechanisms of eleutherococcus senticosus on korsakoff syndrome.	Jiang S et al.	—	2025	→
The Psychiatric Genomics Consortium: discoveries and directions.	Agrawal A et al.	—	2025	→

Polygenic risk for alcohol use disorder affects cellular responses to ethanol exposure in a human microglial cell model.

External