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39 p.-7 fig.-1 graph. abst., Background and Purpose Reperfusion therapy is the standard of care for ischemic stroke; however, there is a need to identify new therapeutic targets able to ameliorate cerebral damage. Neutrophil´s β1 adrenergic receptor (β1AR) has been linked to migration during exacerbated inflammation. Given the central role of neutrophils in cerebral damage during stroke, we hypothesize that β1AR blockade will improve stroke outcomes., Experimental Approach Rats were subjected to middle cerebral artery occlusion–reperfusion to evaluate the effect on stroke of the selective β1AR blocker metoprolol (12.5 mg/Kg) when injected i.v. 10 min before reperfusion., Key Results Magnetic resonance imaging and histopathology analysis showed that pre-reperfusion i.v. metoprolol reduced IS. This was accompanied by reduced cytotoxic edema at 24 h and vasogenic edema at 7 d. Metoprolol-treated rats showed reduced brain neutrophil infiltration and those which infiltrated displayed a high proportion of anti-inflammatory phenotype (N2, YM1+). Additional inflammatory models demonstrated that metoprolol specifically blocked neutrophil migration via β1AR and excluded a significant effect on glia compartment. Consistently, metoprolol did not protect the brain in neutrophil-depleted rats upon stroke. In patients suffering an ischemic stroke, β1AR blockade by metoprolol reduced circulating neutrophil–platelet co-aggregates., Conclusions and Implications Our findings describe that β1AR blockade ameliorates cerebral damage by targeting neutrophils, identifying a novel therapeutic target to improve outcomes in patients with stroke. This therapeutic strategy is in the earliest stages of the translational pathway and should be further explored., This study received funding from the Instituto de Salud Carlos III (ISCIII; PI16/02110 to B.I and PT20/00044 to MD), the European Regional Development Fund (ERDF) “A way of making Europe", the Comunidad de Madrid (S2017/BMD-3867 RENIM-CM to MD and BI) cofunded with European structural and investment funds and by Agencia Estatal de Investigación (PID2019‐110369RB‐I00 to B.I). BI is a recipient of funding from the European Research Council (ERC) under the European Union Horizon 2020 Research and Innovation Programme (ERC-Consolidator Grant agreement No. 819775). EO is a recipient of funds from the Comunidad de Madrid Programa de Atracción de Talento (2017-T1/BMD 5185) and from a Ramón y Cajal grant (RYC2020-028884-I) funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”. ACM is the beneficiary of an FPU fellowship from the Ministerio de Ciencia e Innovación (FPU2017/01932). MCC is the beneficiary of a Miguel Servet contract (MS16/00174). The CNIC is supported by the ISCIII, the Ministerio de Ciencia e Innovación and the Pro CNIC Foundation and is a Severo Ochoa Center of Excellence (CEX2020-001041-S).