Neuroprotectants attenuate hypobaric hypoxia-induced brain injuries in cynomolgus monkeys
Hypobaric hypoxia (HH) exposure can cause serious brain injury as well as life-threatening cerebral edema in severe cases. Previous studies on the mechanisms of HH-induced brain injury have been conducted primarily using non-primate animal models that are genetically distant to humans, thus hindering the development of disease treatment. Here, we report that cynomolgus monkeys (Macaca fascicularis) exposed to acute HH developed human-like HH syndrome involving severe brain injury and abnormal behavior. Transcriptome profiling of white blood cells and brain tissue from monkeys exposed to increasing altitude revealed the central role of the HIF-1 and other novel signaling pathways, such as the vitamin D receptor (VDR) signaling pathway, in co-regulating HH-induced inflammation processes. We also observed profound transcriptomic alterations in brains after exposure to acute HH, including the activation of angiogenesis and impairment of aerobic respiration and protein folding processes, which likely underlie the pathological effects of HH-induced brain injury. Administration of progesterone (PROG) and steroid neuroprotectant 5α-androst-3β,5,6β-triol (TRIOL) significantly attenuated brain injuries and rescued the transcriptomic changes induced by acute HH. Functional investigation of the affected genes suggested that these two neuroprotectants protect the brain by targeting different pathways, with PROG enhancing erythropoiesis and TRIOL suppressing glutamate-induced excitotoxicity. Thus, this study advances our understanding of the pathology induced by acute HH and provides potential compounds for the development of neuroprotectant drugs for therapeutic treatment.
- Acute hypobaric hypoxia /
- Cynomolgus monkeys /
- Brain injury /
- Neuroprotectant /
- Gene regulatory networks
Figure 1. Acute HH-induced behavioral and cerebral impairments were attenuated by PROG and TRIOL treatments
A: Experimental procedure for HH treatment of cynomolgus monkeys (HH group, n=6). Vertical bars along y-axis indicate medical definitions of high, very high, and extreme altitudes. Horizontal bars represent duration spent at each altitude. Blood drop and brain icons indicate altitudes and time points at which blood and brain samples, respectively, were collected for RNA-seq analyses. B: Experimental procedure for drug treatment (HH+ PROG and HH+TRIOL groups, each n=6). Needle tubes indicate altitudes and time points at which drugs were injected; blood drop and brain icons indicate altitudes and time points at which blood and brain samples were collected, respectively. Drugs were injected after blood collection at each stage. Samples from stages highlighted in red were selected for RNA-seq analyses. C: Chemical structures of two neuroprotectants (PROG and TRIOL) used in this study. D: Mean skeletal muscle coordination scores for each experimental group, with higher scores representing a lower degree of coordination, assessed after 2 h at 7 500 m. Each group was compared with HH group (*: Kruskal-Wallis test P<0.05). Data are presented with error bars indicating means±SD, n=6 per group. E: Mean brain water content for each experimental group, measured as 1–dry/wet weight of left hemisphere. Each group was compared with HH group (*: one-way ANOVA P<0.05; **: P<0.01, HH n=5, each other group n=6). Error bars represent SD. F: Representative images showing ultrastructure of capillaries in frontal cortex of each experimental group, taken after 48 h at 7 500 m. Blood-brain barrier (BBB) disruption and vasogenic edema evident in HH group but not in other groups, as characterized by severely shrunken capillaries with fluid penetrating into pericapillary space. Red arrowheads indicate capillary boundary. Scale bar: 2 μm. G: Representative images showing Nissl staining of frontal cortex tissues of each experimental group. Neuronal injuries evident in HH group and markedly attenuated in drug-treated groups. Black squares in first row denote areas magnified in second row. Red arrowheads indicate injured cells with dark staining, condensed nuclei, shrunken cell bodies, or weak staining with irregular shapes. Red scale bar: 75 μm, black scale bar: 20 μm. H: Percentage of injured neurons in frontal cortex of each experimental group based on Nissl staining shown in panel G. Each group was compared with HH group (**: one-way ANOVA P≤0.01; ***: P≤0.001, NN n=5, all other groups n=4). Error bars represent SD.
Figure 2. Transcriptomic dynamics of WBCs in response to acute HH.
A: Principal component analysis (PCA) using genes robustly expressed in at least one of six HH stages (A–F). Colors denote stages of HH at which WBC samples were collected, as described in Figure 1A. B: Numbers of differentially expressed genes (DEGs) between stage A and each of the other five stages. C: Expression patterns of DEGs in three HH-responding modules, shown as log2-transformed reads per kilobase of transcript per million mapped reads (RPKM) fold changes of DEGs in each stage compared to stage A. Red and light blue lines indicate expression patterns of individual DEGs up- and down-regulated by HH, respectively. Bold lines show mean expression levels of all up- or down-regulated DEGs, with error bars indicating SD. UP and DOWN indicate exact number of up- or down-regulated DEGs by HH in each module. D: Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched in three HH-responding modules. Only significantly enriched pathways with a false discovery rate (FDR)-adjusted P-value of <0.05 were plotted. Dot color denotes P-value after FDR correction, and dot size denotes ratio of DEGs versus all expressed genes in each pathway. Different background colors denote classification of pathways. E: Interaction of pathways and symptoms according to reported articles. Blue color denotes pathways of impulse module; red color denotes pathways of late-responding module. Solid arrow line denotes reported direct interaction; dashed arrow line denotes reported associated relationship. F: Local co-expression network revealing genes in vitamin D receptor (VDR) complex as hub genes. Dark blue circles denote DEGs in impulse module; red circles denote genes in VDR complex and HIF1A as hub genes.
Figure 3. Regulation of WBC transcriptomic dynamics by PROG and TRIOL
A: Principal component analysis (PCA) using genes robustly expressed in at least one of nine sample groups (i.e., no-drug treated group, PROG-treated group, and TRIOL-treated group in stages A, D, and F, respectively). Colors denote HH stages at which WBC samples were collected during HH+drug experiments, as described in Figure 1B, whereas shapes denote treatments. B: Number of differentially expressed genes (DEGs) between drug-treated and untreated groups in each HH stage studied. Stage A samples from both PROG and TRIOL groups were collected prior to drug injection; thus, DEGs of A/PROG*-A and A/TRIOL*-A reflect random variations between two groups of experimental monkeys rather than drug-specific effects. C: Erythrocyte-associated DEGs up-regulated by PROG. Red color and arrows denote genes up-regulated by PROG. D: Expression patterns and functions of TRIOL-induced DEGs in three HH-responding modules, shown as log2-transformed reads per kilobase of transcript per million mapped reads (RPKM) fold changes of DEGs in each sample group compared to stage A samples without TRIOL treatment. Light red and blue lines indicate expression patterns of individual DEGs in TRIOL-treated and untreated groups, respectively. Bold lines show mean expression levels of all TRIOL up- or down-regulated DEGs in each group, with error bars representing SD. UP and DOWN indicate exact number of up- or down-regulated DEGs by TRIOL in each module. Text below each module outlines functions associated with TRIOL-induced DEGs, with up and down arrows denoting gene-associated functions up- or down-regulated by TRIOL, respectively.
Figure 4. Transcriptomic changes in frontal cortex in response to acute HH, PROG, and TRIOL
A: Principal component analysis (PCA) using genes robustly expressed in at least one of four sample groups (normobaric normoxia [NN], HH, HH+ PROG, and HH+TRIOL). Colors denote sample group. B: Expression changes of HH-induced differentially expressed genes (DEGs) after PROG or TRIOL treatment, shown as log2-transformed reads per kilobase of transcript per million mapped reads (RPKM) fold changes of DEGs in each sample group compared to NN group. HH-induced DEGs are categorized into strongly responsive genes (SRGs), weakly responsive genes (WRGs), and non-responsive genes (NRGs) according to their degree of expression level recovery after drug treatment. Red and light blue lines denote expression patterns of individual DEGs up- and down-regulated by HH, respectively. Bold lines show mean expression levels of all HH up- or down-regulated DEGs in each group, with error bars representing SD. Percentages of SRGs and WRGs versus all HH-induced DEGs are presented above each plot. C: Expression changes of drug DEGs after PROG or TRIOL treatment, shown as log2-transformed RPKM fold changes of DEGs in each sample group compared to NN group. Red and light blue lines denote expression patterns of individual DEGs up- or down-regulated by drugs, respectively. Bold lines show mean expression levels of all DEGs up- or down-regulated by drugs in each group, with error bars representing SD. D: Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched in HH-induced or drug-recovered DEGs. Only significantly enriched pathways with a false discovery rate (FDR)-adjusted P-value of <0.05 are plotted. In HH DEGs, SRGs, WRGs, and NRGs, red and blue dots denote pathways enriched in DEGs up- and down-regulated by HH, respectively. In drug DEGs (PROG DEGs and TRIOL DEGs), red and blue dots denote pathways enriched in DEGs up- and down-regulated by drugs, respectively. Color intensity of dot indicates level of significance, and size of dot denotes ratio of DEGs versus all expressed genes in each pathway. E: Postulated regulation of excitatory glutamate signaling by TRIOL. Rectangles represent proteins of TRIOL DEGs involved in glutamate signaling pathway. Blue colors denote down-regulation by HH. Gene symbols of DEGs associated with each protein in the pathway are listed below. F: Time-course showing intraneuronal calcium [Ca2+]i in primary cultured rat cortical neurons stimulated by glutamate with different doses of TRIOL. Glutamate stimulation was added at the fiftieth second in the experiment.
 Adams JS, Hewison M. 2008. Unexpected actions of vitamin D: new perspectives on the regulation of innate and adaptive immunity. Nature Clinical Practice Endocrinology and Metabolism, 4(2): 80−90. doi: 10.1038/ncpendmet0716  Ahmad Y, Sharma NK, Garg I, Ahmad MF, Sharma M, Bhargava K. 2013. An insight into the changes in human plasma proteome on adaptation to hypobaric hypoxia. PLoS One, 8(7): e67548. doi: 10.1371/journal.pone.0067548  Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. 2000. Gene Ontology: tool for the unification of biology. Nature Genetics, 25(1): 25−29. doi: 10.1038/75556  Bärtsch P, Swenson ER. 2013. Acute high-altitude illnesses. The New England Journal of Medicine, 368(24): 2294−2302. doi: 10.1056/NEJMcp1214870  Basnyat B, Murdoch DR. 2003. High-altitude illness. The Lancet, 361(9373): 1967−1974. doi: 10.1016/S0140-6736(03)13591-X  Basu M, Pal K, Prasad R, Malhotra AS, Rao KS, Sawhney RC. 1997. Pituitary, gonadal and adrenal hormones after prolonged residence at extreme altitude in man. International Journal of Andrology, 20(3): 153−158. doi: 10.1046/j.1365-2605.1997.00046.x  Benjamini Y, Hochberg Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1): 289−300. doi: 10.1111/j.2517-6161.1995.tb02031.x  Berglund B. 1992. High-altitude training. Sports Medicine, 14(5): 289−303. doi: 10.2165/00007256-199214050-00002  Bergmeier W, Piffath CL, Goerge T, Cifuni SM, Ruggeri ZM, Ware J, Wagner DD. 2006. The role of platelet adhesion receptor GPIbα far exceeds that of its main ligand, von Willebrand factor, in arterial thrombosis. Proceedings of the National Academy of Sciences of the United States of America, 103(45): 16900−16905. doi: 10.1073/pnas.0608207103  Chen J, Leng T, Chen W, Yan M, Yin W, Huang Y, Lin S, Duan D, Lin J, Wu G, Zhang J, Yan G. 2013a. A Synthetic steroid 5α -androst-3β, 5, 6β -triol blocks hypoxia/reoxygenation-induced neuronal injuries via protection of mitochondrial function. Steroids, 78(10): 996−1002. doi: 10.1016/j.steroids.2013.06.004  Chen L, Qiu J-H, Zhang L-L, Luo XD. 2012. Adrenomedullin promotes human endothelial cell proliferation via HIF-1α. Molecular and Cellular Biochemistry, 365(1–2): 263−273.  Chen Y, Zhang J, Ge X, Du J, Deb DK, Li YC. 2013b. Vitamin D receptor inhibits nuclear factor κB activation by interacting with IκB kinase β protein. The Journal of Biological Chemistry, 288(27): 19450−19458. doi: 10.1074/jbc.M113.467670  Chung I, Han G, Seshadri M, Gillard BM, Yu WD, Foster BA, Trump DL, Johnson CS. 2009. Role of vitamin D receptor in the antiproliferative effects of calcitriol in tumor-derived endothelial cells and tumor angiogenesis in vivo. Cancer Research, 69(3): 967−975. doi: 10.1158/0008-5472.CAN-08-2307  Dunlop EA, Tee AR. 2014. mTOR and autophagy: a dynamic relationship governed by nutrients and energy. Seminars in Cell & Developmental Biology, 36(5): 121−129.  Eyries M, Siegfried G, Ciumas M, Montagne K, Agrapart M, Lebrin F, Soubrier F. 2008. Hypoxia-induced apelin expression regulates endothelial cell proliferation and regenerative angiogenesis. Circulation Research, 103(4): 432−440. doi: 10.1161/CIRCRESAHA.108.179333  Gemmati D, Vigliano M, Burini F, Mari R, El Mohsein HH, Parmeggiani F, Serino ML. 2016. Coagulation factor XIIIA (F13A1): novel perspectives in treatment and pharmacogenetics. Current Pharmaceutical Design, 22(11): 1449−1459. doi: 10.2174/1381612822666151210122954  Giffard RG, Xu L, Zhao H, Carrico W, Ouyang Y, Qiao Y, Sapolsky R, Steinberg G, Hu B, Yenari MA. 2004. Chaperones, protein aggregation, and brain protection from hypoxic/ischemic injury. Journal of Experimental Biology, 207(18): 3213−3220. doi: 10.1242/jeb.01034  Guo P, Luo H, Fan Y, Luo Y, Zhou Q. 2013. Establishment and evaluation of an experimental animal model of high altitude cerebral edema. Neuroscience Letters, 547: 82−86. doi: 10.1016/j.neulet.2013.05.008  Hackett PH, Roach RC. 2004. High altitude cerebral edema. High Altitude Medicine & Biology, 5(2): 136−146.  Han S, Xu W, Wang Z, Qi X, Wang Y, Ni Y, Shen H, Hu Q, Han W. 2016. Crosstalk between the HIF-1 and Toll-like receptor/nuclear factor- κB pathways in the oral squamous cell carcinoma microenvironment. Oncotarget, 7(25): 37773−37789.  Hasegawa T, Yoshida S, Sugeno N, Kobayashi J, Aoki M. 2018. DnaJ/Hsp40 family and Parkinson’ s disease. Frontiers in Neuroscience, 11: 743. doi: 10.3389/fnins.2017.00743  Hatfield KJ, Bedringsaas SL, Ryningen A, Gjertsen BT, Bruserud O. 2010. Hypoxia increases HIF-1α expression and constitutive cytokine release by primary human acute myeloid leukaemia cells. European Cytokine Network, 21(3): 154−164.  Hu H, Zhou Y, Leng T, Liu A, Wang Y, You X, Chen J, Tang L, Chen W, Qiu P, Yin W, Huang Y, Zhang J, Wang L, Sang H, Yan G. 2014. The major cholesterol metabolite cholestane-3β, 5α, 6β -triol functions as an endogenous neuroprotectant. Journal of Neuroscience, 34(34): 11426−11438. doi: 10.1523/JNEUROSCI.0344-14.2014  Huang X, Zhou Y, Zhao T, Han X, Qiao M, Ding X, Li D, Wu L, Wu K, Zhu LL, Fan M. 2015. A method for establishing the high-altitude cerebral edema (HACE) model by acute hypobaric hypoxia in adult mice. Journal of Neuroscience Methods, 245: 178−181. doi: 10.1016/j.jneumeth.2015.02.004  Ikegame Y, Yamashita K, Hayashi S, Yoshimura S, Nakashima S, Iwama T. 2010. Neutrophil elastase inhibitor prevents ischemic brain damage via reduction of vasogenic edema. Hypertension Research, 33(7): 703−707. doi: 10.1038/hr.2010.58  Imray C, Wright A, Subudhi A, Roach R. 2010. Acute mountain sickness: pathophysiology, prevention, and treatment. Progress in Cardiovascular Diseases, 52(6): 467−484. doi: 10.1016/j.pcad.2010.02.003  Jain K, Suryakumar G, Ganju L, Singh SB. 2014. Differential hypoxic tolerance is mediated by activation of heat shock response and nitric oxide pathway. Cell Stress Chaperones, 19(6): 801−812. doi: 10.1007/s12192-014-0504-9  Jung YJ, Isaacs JS, Lee S, Trepel J, Neckers L. 2003. IL-1β mediated up-regulation of HIF-1α via an NFkB/COX-2 pathway identifies HIF-1 as a critical link between inflammation and oncogenesis. The FASEB Journal, 17(14): 2115−2117. doi: 10.1096/fj.03-0329fje  Kanehisa M, Goto S. 2000. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28(1): 27−30. doi: 10.1093/nar/28.1.27  Kato S. 2000. The function of vitamin D receptor in vitamin D action. The Journal Biochemistry, 127(5): 717−722. doi: 10.1093/oxfordjournals.jbchem.a022662  Kilkenny C, Browne WJ, Cuthill IC, Emerson M, Altman DG. 2010. Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. PLoS Biology, 8(6): e1000412. doi: 10.1371/journal.pbio.1000412  Kim D, Langmead B, Salzberg SL. 2015. HISAT: a fast spliced aligner with low memory requirements. Nature Methods, 12(4): 357−360. doi: 10.1038/nmeth.3317  Kimmel HL, Thim L, Kuhar MJ. 2002. Activity of various CART peptides in changing locomotor activity in the rat. Neuropeptides, 36(1): 9−12. doi: 10.1054/npep.2002.0884  Kito G, Nishimura A, Susumu T, Nagata R, Kuge Y, Yokota C, Minematsu K. 2001. Experimental thromboembolic stroke in cynomolgus monkey. Journal Neuroscience Methods, 105(1): 45−53. doi: 10.1016/S0165-0270(00)00351-4  Lambert PD, Couceyro PR, Mcgirr KM, Dall Vechia SE, Smith Y, Kuhar MJ. 1998. CART peptides in the central control of feeding and interactions with neuropeptide Y. Synapse, 29(4): 293−298. doi: 10.1002/(SICI)1098-2396(199808)29:4<293::AID-SYN1>3.0.CO;2-0  Langfelder P, Horvath S. 2008. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics, 9(1): 559. doi: 10.1186/1471-2105-9-559  Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B, Johnson WE, Geman D, Baggerly K, Irizarry RA. 2010. Tackling the widespread and critical impact of batch effects in high-throughput data. Nature Reviews Genetics, 11(10): 733−739. doi: 10.1038/nrg2825  Lissa V-A, Bruno M, Suzana H-H. 2013. Different scaling of white matter volume, cortical connectivity, and gyrification across rodent and primate brains. Frontiers in Neuroanatomy, 7(3).  Liu YW, Li S, Dai SS. 2018. Neutrophils in traumatic brain injury (TBI): friend or foe?. Journal of Neuroinflammation, 15(1): 146. doi: 10.1186/s12974-018-1173-x  Love MI, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12): 550. doi: 10.1186/s13059-014-0550-8  Martin D, Windsor J. 2008. From mountain to bedside: understanding the clinical relevance of human acclimatisation to high-altitude hypoxia. Postgraduate Medical Journal, 84(998): 622−627. doi: 10.1136/pgmj.2008.068296  Minta A, Kao JP, Tsien RY. 1989. Fluorescent indicators for cytosolic calcium based on rhodamine and fluorescein chromophores. The Journal of Biological Chemistry, 264(14): 8171−8178.  Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M. 2007. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Research, 35(suppl_2): W182−W185.  Nei M, Xu P, Glazko G. 2001. Estimation of divergence times from multiprotein sequences for a few mammalian species and several distantly related organisms. Proceedings of the National Academy of Sciences of the United States of America, 98(5): 2497−2502. doi: 10.1073/pnas.051611498  Palazon A, Goldrath AW, Nizet V, Johnson RS. 2014. HIF transcription factors, inflammation, and immunity. Immunity, 41(4): 518−528. doi: 10.1016/j.immuni.2014.09.008  Qiu XB, Shao YM, Miao S, Wang L. 2006. The diversity of the DnaJ/Hsp40 family, the crucial partners for Hsp70 chaperones. Cellular and Molecular Life Sciences, 63(22): 2560−2570. doi: 10.1007/s00018-006-6192-6  Rabinstein AA. 2006. Treatment of cerebral edema. The Neurologist, 12(2): 59−73. doi: 10.1097/01.nrl.0000186810.62736.f0  Ramakrishnan S, Anand V, Roy S. 2014. Vascular endothelial growth factor signaling in hypoxia and inflammation. Journal of Neuroimmune Pharmacology, 9(2): 142−160. doi: 10.1007/s11481-014-9531-7  Ravenna L, Salvatori L, Russo MA. 2015. HIF3a: the little we know. The FEBS Journal, 283(6): 993−1003.  Robinson MD, Mccarthy DJ, Smyth GK. 2010. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26(1): 139−140. doi: 10.1093/bioinformatics/btp616  Rogge G, Jones D, Hubert GW, Lin Y, Kuhar MJ. 2008. CART peptides: regulators of body weight, reward and other functions. Nature Reviews Neuroscience, 9(10): 747−758. doi: 10.1038/nrn2493  Saha D, Patgaonkar M, Shroff A, Ayyar K, Bashir T, Reddy KVR. 2014. Hemoglobin expression in nonerythroid cells: novel or ubiquitous?. International Journal of Inflammation, 2014.  Scannevin RH, Huganir RL. 2000. Postsynaptic organisation and regulation of excitatory synapses. Nature Reviews Neuroscience, 1(2): 133−141. doi: 10.1038/35039075  Schoch HJ, Fischer S, Marti HH. 2002. Hypoxia - induced vascular endothelial growth factor expression causes vascular leakage in the brain. Brain, 125(11): 2549−2557. doi: 10.1093/brain/awf257  Semenza GL. 2009. Regulation of oxygen homeostasis by hypoxia-inducible factor 1. Physiology, 24(2): 97−106. doi: 10.1152/physiol.00045.2008  Simonson TS, Yang Y, Huff CD, Yun H, Qin G, Witherspoon DJ, Bai Z, Lorenzo FR, Xing J, Jorde LB. 2010. Genetic evidence for high-altitude adaptation in Tibet. Science, 329(5987): 72−75. doi: 10.1126/science.1189406  Singh M, Su C. 2013. Progesterone and neuroprotection. Hormones and Behavior, 63(2): 284−290. doi: 10.1016/j.yhbeh.2012.06.003  Soto C, Estrada LD. 2008. Protein misfolding and neurodegeneration. Archives of Neurology & Psychiatry, 65(2): 184−189.  Sparkenbaugh E, Pawlinski R. 2013. Interplay between coagulation and vascular inflammation in sickle cell disease. British Journal of Haematology, 162(1): 3−14. doi: 10.1111/bjh.12336  Stamatovic SM, Dimitrijevic OB, Keep RF, Andjelkovic AV. 2006. Inflammation and brain edema: new insights into the role of chemokines and their receptors. Acta Neurochirurgical Supplementum, 96: 444.  Stein DG. 2008. Progesterone exerts neuroprotective effects after brain injury. Brain Research Reviews, 57(2): 386−397. doi: 10.1016/j.brainresrev.2007.06.012  Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L. 2013. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nature Biotechnology, 31(1): 46−53. doi: 10.1038/nbt.2450  Ward Jr JH. 1963. Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58(301): 236−244. doi: 10.1080/01621459.1963.10500845  Wilson MH, Newman S, Imray CH. 2009. The cerebral effects of ascent to high altitudes. The Lancet Neurology, 8(2): 175−191. doi: 10.1016/S1474-4422(09)70014-6  Won S, Sayeed I, Peterson BL, Wali B, Kahn JS, Stein DG. 2015. Vitamin D prevents hypoxia/reoxygenation-induced blood-brain barrier disruption via Vitamin D receptor-mediated NF-kB signaling pathways. PLoS One, 10(3): e0122821. doi: 10.1371/journal.pone.0122821  Wright AD, Beazley MF, Bradwell AR, Chesner IM, Clayton RN, Forster PJ, Hillenbrand P, Imray CH, Society BMRE. 2004. Medroxyprogesterone at high altitude. The effects on blood gases, cerebral regional oxygenation, and acute mountain sickness. Wilderness & Environmental Medicine, 15(1): 25−31.  Wroge CM, Hogins J, Eisenman L, Mennerick S. 2012. Synaptic NMDA receptors mediate hypoxic excitotoxic death. Journal of Neuroscience, 32(19): 6732−6742. doi: 10.1523/JNEUROSCI.6371-11.2012  Yan G, Zhang G, Fang X, Zhang Y, Li C, Ling F, Cooper DN, Li Q, Li Y, Van Gool AJ, Du H, Chen J, Zhang P, Huang Z, Thompson JR, Meng Y, Bai Y, Wang J, Zhuo M, Wang T, Huang Y, Wei L, Li J, Wang Z, Hu H, Yang P, Le L, Stenson PD, Li B, Liu X, Ball EV, An N, Huang Q, Zhang Y, Fan W, Zhang X, Li Y, Wang W, Katze MG, Su B, Nielsen R, Yang H, Wang J, Wang X, Wang J. 2011. Genome sequencing and comparison of two non-human primate animal models, the cynomolgus and Chinese rhesus macaques. Nature Biotechnology, 29(11): 1019−1023. doi: 10.1038/nbt.1992  Yi X, Liang Y, Huerta-Sanchez E, Jin X, Cuo ZXP, Pool JE, Xu X, Jiang H, Vinckenbosch N, Korneliussen TS, Zheng H, Liu T, He W, Li K, Luo R, Nie X, Wu H, Zhao M, Cao H, Zou J, Shan Y, Li S, Yang Q, As an, Ni P, Tian G, Xu J, Liu X, Jiang T, Wu R, Zhou G, Tang M, Qin J, Wang T, Feng S, Li G, Huasang, Luosang J, Wang W, Chen F, Wang Y, Zheng X, Li Z, Bianba Z, Yang G, Wang X, Tang S, Gao G, Chen Y, Luo Z, Gusang L, Cao Z, Zhang Q, Ouyang W, Ren X, Liang H, Zheng H, Huang Y, Li J, Bolund L, Kristiansen K, Li Y, Zhang Y, Zhang X, Li R, Li S, Yang H, Nielsen R, Wang J, Wang J. 2010. Sequencing of 50 human exomes reveals adaptation to high altitude. Science, 329(5987): 75−78. doi: 10.1126/science.1190371