Worldwide stroke is the second leading cause of death and the third leading cause of death and disability combined. The estimated global economic burden by stroke is over US$891 billion per year. Within three decades (1990-2019), the incidence increased by 70%, deaths by 43%, prevalence by 102%, and DALYs by 143%. Of over 100 million people affected by stroke, about 76% are ischemic stroke (IS) patients recorded worldwide. Contextually, ischemic stroke moves into particular focus of multi-professional groups including researchers, healthcare industry, economists, and policy-makers. Risk factors of ischemic stroke demonstrate sufficient space for cost-effective prevention interventions in primary (suboptimal health) and secondary (clinically manifested collateral disorders contributing to stroke risks) care. These risks are interrelated. For example, sedentary lifestyle and toxic environment both cause mitochondrial stress, systemic low-grade inflammation and accelerated ageing; inflammageing is a low-grade inflammation associated with accelerated ageing and poor stroke outcomes. Stress overload, decreased mitochondrial bioenergetics and hypomagnesaemia are associated with systemic vasospasm and ischemic lesions in heart and brain of all age groups including teenagers. Imbalanced dietary patterns poor in folate but rich in red and processed meat, refined grains, and sugary beverages are associated with hyperhomocysteinaemia, systemic inflammation, small vessel disease, and increased IS risks. Ongoing 3PM research towards vulnerable groups in the population promoted by the European Association for Predictive, Preventive and Personalised Medicine (EPMA) demonstrates promising results for the holistic patient-friendly non-invasive approach utilising tear fluid-based health risk assessment, mitochondria as a vital biosensor and AI-based multi-professional data interpretation as reported here by the EPMA expert group. Collected data demonstrate that IS-relevant risks and corresponding molecular pathways are interrelated. For examples, there is an evident overlap between molecular patterns involved in IS and diabetic retinopathy as an early indicator of IS risk in diabetic patients. Just to exemplify some of them such as the 5-aminolevulinic acid/pathway, which are also characteristic for an altered mitophagy patterns, insomnia, stress regulation and modulation of microbiota-gut-brain crosstalk. Further, ceramides are considered mediators of oxidative stress and inflammation in cardiometabolic disease, negatively affecting mitochondrial respiratory chain function and fission/fusion activity, altered sleep-wake behaviour, vascular stiffness and remodelling. Xanthine/pathway regulation is involved in mitochondrial homeostasis and stress-driven anxiety-like behaviour as well as molecular mechanisms of arterial stiffness. In order to assess individual health risks, an application of machine learning (AI tool) is essential for an accurate data interpretation performed by the multiparametric analysis. Aspects presented in the paper include the needs of young populations and elderly, personalised risk assessment in primary and secondary care, cost-efficacy, application of innovative technologies and screening programmes, advanced education measures for professionals and general population-all are essential pillars for the paradigm change from reactive medical services to 3PM in the overall IS management promoted by the EPMA.

Artificial Intelligence and Data Science Group Fraunhofer SCAI Sankt Augustin Germany

Beijing Municipal Key Laboratory of Clinical Epidemiology Capital Medical University Beijing China

Biomedical Centre Faculty of Medicine in Plzen Charles University Prague Czech Republic

Bonn Aachen International Center for IT University of Bonn 53115 Bonn Germany

Cardio Metabolic Unit Department of Medicine Huddinge and Department of Laboratory Medicine Karolinska Institutet and Medicine Unit of Endocrinology Theme Inflammation and Ageing Karolinska University Hospital Stockholm Sweden

Charité University Medicine Berlin Berlin Germany

CuraMed Tagesklinik Nürnberg GmbH Nuremberg Germany

Department of Anatomy Jessenius Faculty of Medicine Comenius University in Bratislava Martin Slovakia

Department of Biology Faculty of Medicine in Plzen Charles University Prague Czech Republic

Department of Histology and Embryology Faculty of Medicine in Plzen Charles University Prague Czech Republic

Department of Histology and Embryology Jessenius Faculty of Medicine Comenius University in Bratislava Martin Slovakia

Department of Neurology University Hospital Kralovske Vinohrady 3rd Faculty of Medicine Charles University Prague Czech Republic

Department of Neurology University Hospital Plzen and Faculty of Medicine in Plzen Charles University Prague Czech Republic

Department of Nutrition School of Health Sciences Ashkelon Academic College Ashkelon Israel

Department of Psychology Clinical Psychology 2 University of Innsbruck Innsbruck Austria

Department of Radiation Oncology University Hospital Bonn Rheinische Friedrich Wilhelms Universität Bonn 53127 Bonn Germany

Edith Cowan University Perth Australia

Experimental Ophthalmology University of Geneva 1205 Geneva Switzerland

Negentropic Systems Ružomberok Slovakia

Ophthalmology Department University Hospitals of Geneva 1205 Geneva Switzerland

PPPM Centre s r o Ruzomberok Slovakia

Predictive Preventive and Personalised Medicine Department of Radiation Oncology University Hospital Bonn Rheinische Friedrich Wilhelms Universität Bonn 53127 Bonn Germany

Private Institute of Applied Ophthalmology Berlin Germany

Technische Hochschule Nürnberg GSO Nuremberg Germany

The Dental College of Georgia Departments of Neurology and Surgery The Medical College of Georgia Augusta University Augusta USA

University Clinic for Psychiatry and Psychotherapy Paracelsus Medical University Nuremberg Germany

University Clinic of Endocrinology Diabetes and Metabolic Disorders Skopje University Goce Delcev Faculty of Medical Sciences Stip North Macedonia

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GBD 2019 Stroke Collaborators Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol. 2021;20(10):795–820. doi: 10.1016/S1474-4422(21)00252-0. PubMed DOI PMC

Owolabi MO, Thrift AG, Mahal A, et al. Primary stroke prevention worldwide: translating evidence into action. Lancet Public Health. 2022;7(1):e74–85. doi: 10.1016/S2468-2667(21)00230-9. PubMed DOI PMC

Johnson CO, Nguyen M, Roth GA, et al. Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):439–58. doi: 10.1016/S1474-4422(19)30034-1. PubMed DOI PMC

Lindsay MP, Norrving B, Sacco RL, et al. World Stroke Organization (WSO): Global Stroke Fact Sheet 2019. Int J Stroke. 2019;14(8):806–817. doi: 10.1177/1747493019881353. PubMed DOI

Feigin VL, Brainin M, Norrving B, et al. World Stroke Organization (WSO): Global Stroke Fact Sheet 2022. Int J Stroke. 2022;17(1):18–29. doi: 10.1177/17474930211065917. PubMed DOI

GBD 2016 Stroke Collaborators Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):439–58. doi: 10.1016/S1474-4422(19)30034-1. PubMed DOI PMC

Ak C, Gupta R, Warkade V. Study of clinical profile and risk factors for ischemic stroke in young adults. J Assoc Phys India. 2022;70(4):11–12. PubMed

Rodríguez-Campello A, Jiménez-Conde J, Ois Á, et al. Dietary habits in patients with ischemic stroke: a case-control study. PLoS ONE. 2014;9(12):e114716. doi: 10.1371/journal.pone.0114716. PubMed DOI PMC

Lavados PM, Mazzon E, Rojo A, Brunser AM, Olavarría VV. Pre-stroke adherence to a Mediterranean diet pattern is associated with lower acute ischemic stroke severity: a cross-sectional analysis of a prospective hospital-register study. BMC Neurol. 2020;20(1):252. doi: 10.1186/s12883-020-01824-y. PubMed DOI PMC

Tang H, Gong F, Guo H, et al. Malnutrition and risk of mortality in ischemic stroke patients treated with intravenous thrombolysis. Front Aging Neurosci. 2022;14:834973. doi: 10.3389/fnagi.2022.834973. PubMed DOI PMC

Bouziana SD, Tziomalos K. Malnutrition in patients with acute stroke. J Nutr Metab. 2011;2011:167898. doi: 10.1155/2011/167898. PubMed DOI PMC

Yoo S-H, Kim JS, Kwon SU, Yun S-C, Koh J-Y, Kang D-W. Undernutrition as a predictor of poor clinical outcomes in acute ischemic stroke patients. Arch Neurol. 2008;65(1):39–43. doi: 10.1001/archneurol.2007.12. PubMed DOI

Horn JW, Feng T, Mørkedal B, et al. Obesity and risk for first ischemic stroke depends on metabolic syndrome: the HUNT study. Stroke. 2021;52(11):3555–3561. doi: 10.1161/STROKEAHA.120.033016. PubMed DOI

Shiozawa M, Kaneko H, Itoh H, et al. Association of body mass index with ischemic and hemorrhagic stroke. Nutrients. 2021;13(7):2343. doi: 10.3390/nu13072343. PubMed DOI PMC

Bardugo A, Fishman B, Libruder C, et al. Body mass index in 1.9 million adolescents and stroke in young adulthood. Stroke. 2021;52(6):2043–52. doi: 10.1161/STROKEAHA.120.033595. PubMed DOI

Golubnitschaja O, Potuznik P, Polivka J, et al. Ischemic stroke of unclear aetiology: a case-by-case analysis and call for a multi-professional predictive, preventive and personalised approach. EPMA J. 2022;13(4):535–545. doi: 10.1007/s13167-022-00307-z. PubMed DOI PMC

Golubnitschaja O, Liskova A, Koklesova L, et al. Caution, “normal” BMI: health risks associated with potentially masked individual underweight-EPMA Position Paper 2021. EPMA J. 2021;12(3):243–264. doi: 10.1007/s13167-021-00251-4. PubMed DOI PMC

Song DK, Hong YS, Sung Y-A, Lee H. Body mass index and stroke risk among patients with diabetes mellitus in Korea. PLoS ONE. 2022;17(9):e0275393. doi: 10.1371/journal.pone.0275393. PubMed DOI PMC

Chaudhary D, Khan A, Gupta M, et al. Obesity and mortality after the first ischemic stroke: Is obesity paradox real? PLoS ONE. 2021;16(2):e0246877. doi: 10.1371/journal.pone.0246877. PubMed DOI PMC

Oesch L, Tatlisumak T, Arnold M, Sarikaya H. Obesity paradox in stroke – myth or reality? A systematic review. PLoS ONE. 2017;12(3):e0171334. doi: 10.1371/journal.pone.0171334. PubMed DOI PMC

Ho L-C, Wang H-K, Chiu L-T, et al. Protein energy wasting–based nutritional assessment predicts outcomes of acute ischemic stroke and solves the epidemiologic paradox. Nutrition. 2022;93:111431. doi: 10.1016/j.nut.2021.111431. PubMed DOI

Middleton LE, Corbett D, Brooks D, et al. Physical activity in the prevention of ischemic stroke and improvement of outcomes: a narrative review. Neurosci Biobehav Rev. 2013;37(2):133–137. doi: 10.1016/j.neubiorev.2012.11.011. PubMed DOI

Cowan LT, Tome J, Mallhi AK, et al. Changes in physical activity and risk of ischemic stroke: the ARIC study. Int J Stroke. 2023;18(2):173–179. doi: 10.1177/17474930221094221. PubMed DOI PMC

Guo S, Huang Y, Zhang Y, Huang H, Hong S, Liu T. Impacts of exercise interventions on different diseases and organ functions in mice. J Sport Health Sci. 2020;9(1):53–73. doi: 10.1016/j.jshs.2019.07.004. PubMed DOI PMC

Krako Jakovljevic N, Pavlovic K, Jotic A, et al. Targeting mitochondria in diabetes. IJMS. 2021;22(12):6642. doi: 10.3390/ijms22126642. PubMed DOI PMC

Lee Y, Min K, Talbert EE, et al. Exercise protects cardiac mitochondria against ischemia-reperfusion injury. Med Sci Sports Exerc. 2012;44(3):397–405. doi: 10.1249/MSS.0b013e318231c037. PubMed DOI

Di Meo S, Venditti P. Mitochondria in exercise-induced oxidative stress. Biol Signals Recept. 2001;10(1–2):125–140. doi: 10.1159/000046880. PubMed DOI

Layec G, Blain GM, Rossman MJ, et al. Acute high-intensity exercise impairs skeletal muscle respiratory capacity. Med Sci Sports Exerc. 2018;50(12):2409–2417. doi: 10.1249/MSS.0000000000001735. PubMed DOI PMC

Avellaneda-Gómez C, Vivanco-Hidalgo RM, Olmos S, et al. Air pollution and surrounding greenness in relation to ischemic stroke: a population-based cohort study. Environ Int. 2022;161:107147. doi: 10.1016/j.envint.2022.107147. PubMed DOI

Dev P, Gupta P, Mahapatra A, et al. Systematic review and meta-analysis of environmental toxic metal contaminants and the risk of ischemic stroke. Ann Indian Acad Neurol. 2022;25(6):1159–1166. doi: 10.4103/aian.aian_530_22. PubMed DOI PMC

Lee HR, Yoo JE, Choi H, et al. Tuberculosis and risk of ischemic stroke: a nationwide cohort study. Stroke. 2022;53(11):3401–3409. doi: 10.1161/STROKEAHA.122.039484. PubMed DOI

Wei Y, Tang S, Xie Z, et al. Pulmonary tuberculosis-related ischemic stroke: a retrospective case control study. J Inflamm Res. 2022;15:4239–4249. doi: 10.2147/JIR.S368183. PubMed DOI PMC

Li J, Lee DH, Hu J, et al. Dietary inflammatory potential and risk of cardiovascular disease among men and women in the U.S. J Am Coll Cardiol. 2020;76(19):2181–93. doi: 10.1016/j.jacc.2020.09.535. PubMed DOI PMC

Golubnitschaja O, Baban B, Boniolo G, et al. Medicine in the early twenty-first century: paradigm and anticipation - EPMA position paper 2016. EPMA J. 2016;7(1):23. doi: 10.1186/s13167-016-0072-4. PubMed DOI PMC

Leary MC, Saver JL. Annual incidence of first silent stroke in the United States: a preliminary estimate. Cerebrovasc Dis. 2003;16(3):280–285. doi: 10.1159/000071128. PubMed DOI

Vermeer SE, Longstreth WT, Koudstaal PJ. Silent brain infarcts: a systematic review. Lancet Neurol. 2007;6(7):611–619. doi: 10.1016/S1474-4422(07)70170-9. PubMed DOI

Kobayashi S, Okada K, Koide H, Bokura H, Yamaguchi S. Subcortical silent brain infarction as a risk factor for clinical stroke. Stroke. 1997;28(10):1932–9. doi: 10.1161/01.STR.28.10.1932. PubMed DOI

Uehara T, Tabuchi M, Mori E. Risk factors for silent cerebral infarcts in subcortical white matter and basal ganglia. Stroke. 1999;30(2):378–382. doi: 10.1161/01.STR.30.2.378. PubMed DOI

Lee S-C, Park S-J, Ki H-K, et al. Prevalence and risk factors of silent cerebral infarction in apparently normal adults. Hypertension. 2000;36(1):73–77. doi: 10.1161/01.HYP.36.1.73-a. PubMed DOI

Matsui T, Arai H, Yuzuriha T, et al. Elevated plasma homocysteine levels and risk of silent brain infarction in elderly people. Stroke. 2001;32(5):1116–1119. doi: 10.1161/01.STR.32.5.1116. PubMed DOI

Maeshima S, Moriwaki H, Ozaki F, Okita R, Yamaga H, Ueyoshi A. Silent cerebral infarction and cognitive function in middle-aged neurologically healthy subjects. Acta Neurol Scand. 2002;105(3):179–184. doi: 10.1034/j.1600-0404.2002.1o068.x. PubMed DOI

Waldstein SR, Siegel EL, Lefkowitz D, et al. Stress-induced blood pressure reactivity and silent cerebrovascular disease. Stroke. 2004;35(6):1294–1298. doi: 10.1161/01.STR.0000127774.43890.5b. PubMed DOI

Kotani K, Osaki Y, Sakane N, Adachi S, Ishimaru Y. Risk factors for silent cerebral infarction in the elderly. Arch Med Res. 2004;35(6):522–524. doi: 10.1016/j.arcmed.2004.07.003. PubMed DOI

Kwon H-M, Kim BJ, Lee S-H, Choi SH, Oh B-H, Yoon B-W. Metabolic syndrome as an independent risk factor of silent brain infarction in healthy people. Stroke. 2006;37(2):466–470. doi: 10.1161/01.STR.0000199081.17935.81. PubMed DOI

Goldstein LB, Adams R, Becker K, et al. Primary prevention of ischemic stroke. Stroke. 2001;32(1):280–299. doi: 10.1161/01.STR.32.1.280. PubMed DOI

Vogels EA, Lagro-Janssen AL, van Weel C. Sex differences in cardiovascular disease: are women with low socioeconomic status at high risk? Br J Gen Pract. 1999;49(449):963–966. PubMed PMC

Herlitz J, Bang A, Karlson BW, Hartford M. Is there a gender difference in aetiology of chest pain and symptoms associated with acute myocardial infarction? Eur J Emerg Med. 1999;6(4):311. doi: 10.1097/00063110-199912000-00007. PubMed DOI

Holroyd-Leduc JM, Kapral MK, Austin PC, Tu JV. Sex differences and similarities in the management and outcome of stroke patients. Stroke. 2000;31(8):1833–1837. doi: 10.1161/01.STR.31.8.1833. PubMed DOI

Ramani S, Byrne-Logan S, Freund KM, Ash A, Yu W, Moskowitz MA. Gender differences in the treatment of cerebrovascular disease. J Am Geriatr Soc. 2000;48(7):741–745. doi: 10.1111/j.1532-5415.2000.tb04747.x. PubMed DOI

Golubnitschaja O. Changing long-held beliefs is never easy: a proposal for multi-modal approach in female healthcare – an integrative view. In: Healthcare overview - new perpectives. In the book “Healthcare Overview - New Perspectives” (Ed: Vincenzo Costigliola), Springer Dordrecht Heidelberg New York London. 2012. 10.1007/978-94-007-4602-2.

Golubnitschaja O. Mitochondrion – The subordinated partner who agreed to come short but insists in healthy life. In: Wang Wei., editor. All Around Suboptimal Health - Advanced approaches by Predictive, Preventive and Personalised Medicine for Healthy Populations. Switzerland: Springer; 2023.

Hagan S, Martin E, Enríquez-de-Salamanca A. Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine. EPMA J. 2016;7(1):15. doi: 10.1186/s13167-016-0065-3. PubMed DOI PMC

Gerner C, Costigliola V, Golubnitschaja O. Multiomic patterns in body fluids: technological challenge with a great potential to implement the advanced paradigm of 3p medicine. Mass Spectrom Rev. 2020;39(5–6):442–451. doi: 10.1002/mas.21612. PubMed DOI

Zhan X, Li J, Guo Y, Golubnitschaja O. Mass spectrometry analysis of human tear fluid biomarkers specific for ocular and systemic diseases in the context of 3P medicine. EPMA J. 2021;12:449–475. doi: 10.1007/s13167-021-00265-y. PubMed DOI PMC

Kropp M, De Clerck E, Vo T-TKS, Thumann G, Costigliola V, Golubnitschaja O. Short communication: unique metabolic signature of proliferative retinopathy in the tear fluid of diabetic patients with comorbidities - preliminary data for PPPM validation. EPMA J. 2023;14(1):43–51. doi: 10.1007/s13167-023-00318-4. PubMed DOI PMC

Kim J, Campbell AS, de Ávila BE, Wang J. Wearable biosensors for healthcare monitoring. Nat Biotechnol. 2019;37(4):389–406. doi: 10.1038/s41587-019-0045-y. PubMed DOI PMC

Golubnitschaja O, Costigliola V, Olga EPMA. General report & recommendations in predictive, preventive and personalised medicine 2012: white paper of the European Association for Predictive, Preventive and Personalised Medicine. EPMA J. 2012;3(1):14. doi: 10.1186/1878-5085-3-14. PubMed DOI PMC

Golubnitschaja O, Yeghiazaryan K, Cebioglu M, Morelli M, Herrera-Marschitz M. Birth asphyxia as the major complication in newborns: moving towards improved individual outcomes by prediction, targeted prevention and tailored medical care. EPMA J. 2011;2(2):197–210. doi: 10.1007/s13167-011-0087-9. PubMed DOI PMC

Golubnitschaja O, Watson ID, Topic E, Sandberg S, Ferrari M, Costigliola V. Position paper of the EPMA and EFLM: a global vision of the consolidated promotion of an integrative medical approach to advance health care. EPMA J. 2013;4(1):12. doi: 10.1186/1878-5085-4-12. PubMed DOI PMC

Ramsay SL, STÖGGL WM, Weinberger KM, Graber A, Guggenbichler W. Apparatus for analyzing a metabolite profile. Patent 2014;EP1897014B1. Available from: https://patents.google.com/patent/EP1897014B1/en. Accessed 22 Jan 2024.

Ramsay SL, Guggenbichler W, Weinberger KM, Graber A, STÖGGL WM. Device for quantitative analysis of a metabolite profile. Patent 2014;EP1875401B1. Available from: https://patents.google.com/patent/EP1875401B1/en. Accessed 22 Jan 2024.

Takeshita M, Tabara Y, Setoh K, et al. Development of a plasma-free amino acid-based risk score for the incidence of cardiovascular diseases in a general population: The Nagahama study. Clin Nutr. 2023;42(12):2512–2519. doi: 10.1016/j.clnu.2023.10.024. PubMed DOI

Jauhiainen R, Vangipurapu J, Laakso A, Kuulasmaa T, Kuusisto J, Laakso M. The association of 9 amino acids with cardiovascular events in Finnish men in a 12-year follow-up study. J Clin Endocrinol Metab. 2021;106(12):3448–3454. doi: 10.1210/clinem/dgab562. PubMed DOI PMC

Hajsl M, Hlavackova A, Broulikova K, et al. Tryptophan metabolism, inflammation, and oxidative stress in patients with neurovascular disease. Metabolites. 2020;10(5):208. doi: 10.3390/metabo10050208. PubMed DOI PMC

Haikonen R, Kärkkäinen O, Koistinen V, Hanhineva K. Diet- and microbiota-related metabolite, 5-aminovaleric acid betaine (5-AVAB), in health and disease. Trends Endocrinol Metab. 2022;33(7):463–480. doi: 10.1016/j.tem.2022.04.004. PubMed DOI

Tveter KM, Mezhibovsky E, Wu Y, Roopchand DE. Bile acid metabolism and signaling: emerging pharmacological targets of dietary polyphenols. Pharmacol Ther. 2023;248:108457. doi: 10.1016/j.pharmthera.2023.108457. PubMed DOI PMC

Liu J, Yuan J, Zhao J, Zhang L, Wang Q, Wang G. Serum metabolomic patterns in young patients with ischemic stroke: a case study. Metabolomics. 2021;17(2):24. doi: 10.1007/s11306-021-01774-7. PubMed DOI

Miękus N, Olędzka I, Kowalski P, Miękus P, Baczek T. Practical application of biogenic amine profiles for the diagnosis of patients with ischemic stroke. J Stroke Cerebrovasc Dis. 2018;27(4):945–950. doi: 10.1016/j.jstrokecerebrovasdis.2017.10.041. PubMed DOI

Lee E, Kim DJ, Cho J-Y, Jung K. Abstract WMP114: putrescine and kynurenine are associated with large artery atherosclerosis stroke: targeted metabolomics study. Stroke. 2022;53(Suppl_1):AWMP114–AWMP114. doi: 10.1161/str.53.suppl_1.WMP114. DOI

Lee H, Chu Y-K, Shon J-H, Chun K-H, Kim J-I, Lee S-R. Effect of L-deprenyl on the putrescine level and neuronal damage after transient global cerebral ischemia in gerbils. Int J Org Chem. 2017;7(2):171–184. doi: 10.4236/ijoc.2017.72014. DOI

Li Z, Lei H, Jiang H, et al. Saturated fatty acid biomarkers and risk of cardiometabolic diseases: a meta-analysis of prospective studies. Front Nutr. 2022;9:963471. doi: 10.3389/fnut.2022.963471. PubMed DOI PMC

Jung JY, Lee H-S, Kang D-G, et al. 1H-NMR-based metabolomics study of cerebral infarction. Stroke. 2011;42(5):1282–1288. doi: 10.1161/STROKEAHA.110.598789. PubMed DOI

Li M, Xiao H, Qiu Y, et al. Identification of potential diagnostic biomarkers of cerebral infarction using gas chromatography-mass spectrometry and chemometrics. RSC Adv. 2018;8(41):22866–22875. doi: 10.1039/C8RA03132K. PubMed DOI PMC

Tóth OM, Menyhárt Á, Frank R, Hantosi D, Farkas E, Bari F. Tissue acidosis associated with ischemic stroke to guide neuroprotective drug delivery. Biology (Basel) 2020;9(12):460. PubMed PMC

Collister D, Ferguson TW, Funk SE, Reaven NL, Mathur V, Tangri N. Metabolic acidosis and cardiovascular disease in CKD. Kidney Med. 2021;3(5):753–761.e1. doi: 10.1016/j.xkme.2021.04.011. PubMed DOI PMC

Oreshnikov E, Oreshnikova S, Oreshnikov A. 741: Purine metabolites, hormones, and lethal outcome in acute cerebral ischemia: some aspects. Crit Care Med. 2021;49(1):367.

Tariq MA, Shamim SA, Rana KF, Saeed A, Malik BH. Serum uric acid - risk factor for acute ischemic stroke and poor outcomes. Cureus. 2019;11(10):e6007. PubMed PMC

Saini G, Kaur K, Bhatia L, Kaur R, Singh J, Singh G. Single Serum Cortisol Value as a Prognostic Marker in Acute Ischemic Stroke. Cureus. 2023;15(6):e40887. PubMed PMC

Busik JV. Lipid metabolism dysregulation in diabetic retinopathy. J Lipid Research 2021;62:100017. PubMed PMC

Aljanabi NM, Mamtani SS, Acharya A, Gupta Rauniyar RP, Malik BH. Association between cerebrovascular accident and vasculitis: myth or reality? Cureus. 2023;11(12):e6345. PubMed PMC

Elkind MSV, Boehme AK, Smith CJ, Meisel A, Buckwalter MS. Infection as a stroke risk factor and determinant of outcome after stroke. Stroke. 2020;51(10):3156–3168. doi: 10.1161/STROKEAHA.120.030429. PubMed DOI PMC

Nagel MA, Mahalingam R, Cohrs RJ, Gilden D. Virus vasculopathy and stroke: an under-recognized cause and treatment target. Infect Disord Drug Targets. 2010;10(2):105–111. doi: 10.2174/187152610790963537. PubMed DOI PMC

Ziu E, Khan Suheb MZ, Mesfin FB. Subarachnoid hemorrhage. In: StatPearls. Treasure Island (FL): StatPearls Publishing; 2023. http://www.ncbi.nlm.nih.gov/books/NBK441958/. Accessed 22 Jan 2024. PubMed

Katajamäki TT, Koivula M-K, Hilvo M, et al. Ceramides and phosphatidylcholines associate with cardiovascular diseases in the elderly. Clin Chem. 2022;68(12):1502–1508. doi: 10.1093/clinchem/hvac158. PubMed DOI

Huang M, Xu S, Zhou M, et al. Lysophosphatidylcholines and phosphatidylcholines as biomarkers for stroke recovery. Frontiers in Neurology 2022;13:1047101 PubMed PMC

Law S-H, Chan M-L, Marathe GK, Parveen F, Chen C-H, Ke L-Y. An updated review of lysophosphatidylcholine metabolism in human diseases. Int J Mol Sci. 2019;20(5):1149. doi: 10.3390/ijms20051149. PubMed DOI PMC

Cheng L, Han X, Shi Y. A regulatory role of LPCAT1 in the synthesis of inflammatory lipids, PAF and LPC, in the retina of diabetic mice. Am J Physiol-Endocrinol Metab. 2009;297(6):E1276–E1282. doi: 10.1152/ajpendo.00475.2009. PubMed DOI PMC

Jové M, Mauri-Capdevila G, Suárez I, et al. Metabolomics predicts stroke recurrence after transient ischemic attack. Neurology. 2015;84(1):36–45. doi: 10.1212/WNL.0000000000001093. PubMed DOI PMC

Liang H-J, Zhang Q-Y, Hu Y-T, Liu G-Q, Qi R. Hypertriglyceridemia: a neglected risk factor for ischemic stroke? J Stroke. 2022;24(1):21–40. doi: 10.5853/jos.2021.02831. PubMed DOI PMC

Mavroudakis L, Lanekoff I. Ischemic Stroke causes disruptions in the carnitine shuttle system. Metabolites. 2023;13(2):278. doi: 10.3390/metabo13020278. PubMed DOI PMC

Seo W-K, Jo G, Shin M-J, Oh K. Medium-chain acylcarnitines are associated with cardioembolic stroke and stroke recurrence. Arterioscler Thromb Vasc Biol. 2018;38(9):2245–2253. doi: 10.1161/ATVBAHA.118.311373. PubMed DOI

Maida CD, Daidone M, Pacinella G, Norrito RL, Pinto A, Tuttolomondo A. Diabetes and ischemic stroke: an old and new relationship an overview of the close interaction between these diseases. Int J Mol Sci. 2022;23(4):2397. doi: 10.3390/ijms23042397. PubMed DOI PMC

Chen R, Ovbiagele B, Feng W. Diabetes and stroke: epidemiology, pathophysiology, pharmaceuticals and outcomes. Am J Med Sci. 2016;351(4):380–386. doi: 10.1016/j.amjms.2016.01.011. PubMed DOI PMC

Bradley SA, Smokovski I, Bhaskar SMM. Impact of diabetes on clinical and safety outcomes in acute ischemic stroke patients receiving reperfusion therapy: a meta-analysis. Adv Clin Exp Med. 2022;31(6):583–596. doi: 10.17219/acem/146273. PubMed DOI

Hill MD. Stroke and diabetes mellitus. Handb Clin Neurol. 2014;126:167–174. doi: 10.1016/B978-0-444-53480-4.00012-6. PubMed DOI

Johnston KC, Bruno A, Pauls Q, et al. Intensive vs standard treatment of hyperglycemia and functional outcome in patients with acute ischemic stroke: the SHINE randomized clinical trial. JAMA. 2019;322(4):326–335. doi: 10.1001/jama.2019.9346. PubMed DOI PMC

Lin H-B, Li F-X, Zhang J-Y, et al. Cerebral-cardiac syndrome and diabetes: cardiac damage after ischemic stroke in diabetic state. Front Immunol. 2021;12:737170. doi: 10.3389/fimmu.2021.737170. PubMed DOI PMC

Vogrig A, Gigli GL, Bnà C, Morassi M. Stroke in patients with COVID-19: clinical and neuroimaging characteristics. Neurosci Lett. 2021;743:135564. doi: 10.1016/j.neulet.2020.135564. PubMed DOI PMC

Luo W, Liu X, Bao K, Huang C. Ischemic stroke associated with COVID-19: a systematic review and meta-analysis. J Neurol. 2022;269(4):1731–1740. doi: 10.1007/s00415-021-10837-7. PubMed DOI PMC

Nannoni S, de Groot R, Bell S, Markus HS. Stroke in COVID-19: a systematic review and meta-analysis. Int J Stroke. 2021;16(2):137–149. doi: 10.1177/1747493020972922. PubMed DOI PMC

Bourne RRA, Jonas JB, Bron AM, et al. Prevalence and causes of vision loss in high-income countries and in Eastern and Central Europe in 2015: magnitude, temporal trends and projections. Br J Ophthalmol. 2018;102(5):575–585. doi: 10.1136/bjophthalmol-2017-311258. PubMed DOI PMC

Kropp M, Golubnitschaja O, Mazurakova A, et al. Diabetic retinopathy as the leading cause of blindness and early predictor of cascading complications-risks and mitigation. EPMA J. 2023;14(1):21–42. doi: 10.1007/s13167-023-00314-8. PubMed DOI PMC

Hu K, Jiang M, Zhou Q, et al. Association of diabetic retinopathy with stroke: a systematic review and meta-analysis. Front Neurol. 2021;12:626996. doi: 10.3389/fneur.2021.626996. PubMed DOI PMC

Gar C, Rottenkolber M, Prehn C, Adamski J, Seissler J, Lechner A. Serum and plasma amino acids as markers of prediabetes, insulin resistance, and incident diabetes. Crit Rev Clin Lab Sci. 2018;55(1):21–32. doi: 10.1080/10408363.2017.1414143. PubMed DOI

Nemet I, Li XS, Haghikia A, et al. Atlas of gut microbe-derived products from aromatic amino acids and risk of cardiovascular morbidity and mortality. Eur Heart J. 2023;44(32):3085–3096. doi: 10.1093/eurheartj/ehad333. PubMed DOI PMC

McGlone ER, Bloom SR. Bile acids and the metabolic syndrome. Ann Clin Biochem. 2019;56(3):326–337. doi: 10.1177/0004563218817798. PubMed DOI

Chávez-Talavera O, Tailleux A, Lefebvre P, Staels B. Bile acid control of metabolism and inflammation in obesity, type 2 diabetes, dyslipidemia, and nonalcoholic fatty liver disease. Gastroenterology. 2017;152(7):1679–1694.e3. doi: 10.1053/j.gastro.2017.01.055. PubMed DOI

Ferrell JM, Chiang JYL. Understanding bile acid signaling in diabetes: from pathophysiology to therapeutic targets. Diabetes Metab J. 2019;43(3):257–272. doi: 10.4093/dmj.2019.0043. PubMed DOI PMC

Zhang W, Dong XY, Huang R. Gut microbiota in ischemic stroke: role of gut bacteria-derived metabolites. Transl Stroke Res. 2023;14(6):811–828. doi: 10.1007/s12975-022-01096-3. PubMed DOI

Chaurasia B, Tippetts TS, Mayoral Monibas R, et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365(6451):386–392. doi: 10.1126/science.aav3722. PubMed DOI PMC

Yaribeygi H, Bo S, Ruscica M, Sahebkar A. Ceramides and diabetes mellitus: an update on the potential molecular relationships. Diabet Med. 2020;37(1):11–19. doi: 10.1111/dme.13943. PubMed DOI

Mandal N, Grambergs R, Mondal K, Basu SK, Tahia F, Dagogo-Jack S. Role of ceramides in the pathogenesis of diabetes mellitus and its complications. J Diabetes Complicat. 2021;35(2):107734. doi: 10.1016/j.jdiacomp.2020.107734. PubMed DOI PMC

Choi RH, Tatum SM, Symons JD, Summers SA, Holland WL. Ceramides and other sphingolipids as drivers of cardiovascular disease. Nat Rev Cardiol. 2021;18(10):701–711. doi: 10.1038/s41569-021-00536-1. PubMed DOI PMC

Kulikowska E, Kierdaszuk B, Shugar D. Xanthine, xanthosine and its nucleotides: solution structures of neutral and ionic forms, and relevance to substrate properties in various enzyme systems and metabolic pathways. Acta Biochim Pol. 2004;51(2):493–531. doi: 10.18388/abp.2004_3587. PubMed DOI

Ramasubbu K, Devi RV. Impairment of insulin signaling pathway PI3K/Akt/mTOR and insulin resistance induced AGEs on diabetes mellitus and neurodegenerative diseases: a perspective review. Mol Cell Biochem. 2023;478(6):1307–1324. doi: 10.1007/s11010-022-04587-x. PubMed DOI

Zhao H, He Y. Lysophosphatidylcholine offsets the protective effects of bone marrow mesenchymal stem cells on inflammatory response and oxidative stress injury of retinal endothelial cells via TLR4/NF-κB signaling. J Immunol Res. 2021;2021:2389029. doi: 10.1155/2021/2389029. PubMed DOI PMC

Canning P, Kenny B-A, Prise V, et al. Lipoprotein-associated phospholipase A2 (Lp-PLA2) as a therapeutic target to prevent retinal vasopermeability during diabetes. Proc Natl Acad Sci U S A. 2016;113(26):7213–7218. doi: 10.1073/pnas.1514213113. PubMed DOI PMC

Yuan C, Shi L, Sun Z, et al. Regulatory T cell expansion promotes white matter repair after stroke. Neurobiol Dis. 2023;179:106063. doi: 10.1016/j.nbd.2023.106063. PubMed DOI

Alesi S, Ghelani D, Rassie K, Mousa A. Metabolomic biomarkers in gestational diabetes mellitus: a review of the evidence. Int J Mol Sci. 2021;22(11):5512. doi: 10.3390/ijms22115512. PubMed DOI PMC

Lee G, Choi S, Chang J, et al. Association of L-α glycerylphosphorylcholine with subsequent stroke risk after 10 years. JAMA Netw Open. 2021;4(11):e2136008. doi: 10.1001/jamanetworkopen.2021.36008. PubMed DOI PMC

Purroy F, Ois A, Jove M, et al. Lipidomic signature of stroke recurrence after transient ischemic attack. Sci Rep. 2023;13(1):13706. doi: 10.1038/s41598-023-40838-7. PubMed DOI PMC

Callaghan BC, Feldman E, Liu J, et al. Triglycerides and amputation risk in patients with diabetes: ten-year follow-up in the DISTANCE study. Diabetes Care. 2011;34(3):635–640. doi: 10.2337/dc10-0878. PubMed DOI PMC

Jasim OH, Mahmood MM, Ad’hiah AH. Significance of lipid profile parameters in predicting pre-diabetes. Arch Razi Inst. 2022;77(1):277–84. PubMed PMC

Vermeer SE, Den Heijer T, Koudstaal PJ, Oudkerk M, Hofman A, Breteler MMB. Incidence and risk factors of silent brain infarcts in the population-based rotterdam scan study. Stroke. 2003;34(2):392–396. doi: 10.1161/01.STR.0000052631.98405.15. PubMed DOI

Vermeer SE, Prins ND, Den Heijer T, Hofman A, Koudstaal PJ, Breteler MMB. Silent brain infarcts and the risk of dementia and cognitive decline. N Engl J Med. 2003;348(13):1215–1222. doi: 10.1056/NEJMoa022066. PubMed DOI

Neuropathology Group Medical research council cognitive function and aging study. Pathological correlates of late-onset dementia in a multicentre, community-based population in England and Wales. Neuropathology Group of the Medical Research Council Cognitive Function and Ageing Study (MRC CFAS) Lancet. 2001;357(9251):169–75. doi: 10.1016/S0140-6736(00)03589-3. PubMed DOI

Jellinger KA, Mitter-Ferstl E. The impact of cerebrovascular lesions in Alzheimer disease–a comparative autopsy study. J Neurol. 2003;250(9):1050–1055. doi: 10.1007/s00415-003-0142-0. PubMed DOI

Bennett DA, Schneider JA, Bienias JL, Evans DA, Wilson RS. Mild cognitive impairment is related to Alzheimer disease pathology and cerebral infarctions. Neurology. 2005;64(5):834–841. doi: 10.1212/01.WNL.0000152982.47274.9E. PubMed DOI

Makin SDJ, Turpin S, Dennis MS, Wardlaw JM. Cognitive impairment after lacunar stroke: systematic review and meta-analysis of incidence, prevalence and comparison with other stroke subtypes. J Neurol Neurosurg Psychiatry. 2013;84(8):893–900. doi: 10.1136/jnnp-2012-303645. PubMed DOI PMC

Matsui T, Nemoto M, Maruyama M, et al. Plasma homocysteine and risk of coexisting silent brain infarction in Alzheimer’s disease. Neurodegener Dis. 2005;2(6):299–304. doi: 10.1159/000092316. PubMed DOI

Bogousslavsky J, Regli F, Uske A. Thalamic infarcts: clinical syndromes, etiology, and prognosis. Neurology. 1988;38(6):837–837. doi: 10.1212/WNL.38.6.837. PubMed DOI

Tatemichi TK, Steinke W, Duncan C, et al. Paramedian thalamopeduncular infarction: Clinical syndromes and magnetic resonance imaging. Ann Neurol. 1992;32(2):162–171. doi: 10.1002/ana.410320207. PubMed DOI

Gold G, Kövari E, Herrmann FR, et al. Cognitive consequences of thalamic, basal ganglia, and deep white matter lacunes in brain aging and dementia. Stroke. 2005;36(6):1184–1188. doi: 10.1161/01.STR.0000166052.89772.b5. PubMed DOI

Fujikawa T, Yamawaki S, Touhouda Y. Silent cerebral infarctions in patients with late-onset mania. Stroke. 1995;26(6):946–949. doi: 10.1161/01.STR.26.6.946. PubMed DOI

Yamashita H, Fujikawa T, Yanai I, Morinobu S, Yamawaki S. Cognitive dysfunction in recovered depressive patients with silent cerebral infarction. Neuropsychobiology. 2002;45(1):12–18. doi: 10.1159/000048667. PubMed DOI

Hamada T, Murata T, Omori M, et al. Abnormal nocturnal blood pressure fall in senile-onset depression with subcortical silent cerebral infarction. Neuropsychobiology. 2003;47(4):187–191. doi: 10.1159/000071213. PubMed DOI

Antelmi E, Fabbri M, Cretella L, Guarino M, Stracciari A. Late onset bipolar disorder due to a lacunar state. Behav Neurol. 2014;2014:1–5. doi: 10.1155/2014/780742. PubMed DOI PMC

Price TR, Manolio TA, Kronmal RA, et al. Silent brain infarction on magnetic resonance imaging and neurological abnormalities in community-dwelling older adults. The Cardiovascular Health Study. CHS Collaborative Research Group. Stroke. 1997;28(6):1158–64. doi: 10.1161/01.STR.28.6.1158. PubMed DOI

Kruit MC. Migraine as a Risk factor for subclinical brain lesions. JAMA. 2004;291(4):427. doi: 10.1001/jama.291.4.427. PubMed DOI

Tietjen GE, Maly EF. Migraine and ischemic stroke in women. A narrative review. Headache. 2020;60(5):843–863. doi: 10.1111/head.13796. PubMed DOI

Leung DYL, Tham CCY, Li FCH, Kwong YYY, Chi SCC, Lam DSC. Silent cerebral infarct and visual field progression in newly diagnosed normal-tension glaucoma: a cohort study. Ophthalmology. 2009;116(7):1250–1256. doi: 10.1016/j.ophtha.2009.02.003. PubMed DOI

Leung DYL, Tham CC. Normal-tension glaucoma: current concepts and approaches-a review. Clin Experiment Ophthalmol. 2022;50(2):247–259. doi: 10.1111/ceo.14043. PubMed DOI

Konieczka K, Ritch R, Traverso CE, et al. Flammer syndrome. EPMA J. 2014;5(1):11. doi: 10.1186/1878-5085-5-11. PubMed DOI PMC

Golubnitschaja O. Flammer syndrome – from phenotype to associated pathologies, prediction, prevention and personalisation. Springer; 2019.

Golubnitschaja O, Yeghiazaryan K, Flammer J. Key molecular pathways affected by glaucoma pathology: is predictive diagnosis possible? EPMA J. 2010;1(2):237–244. doi: 10.1007/s13167-010-0031-4. PubMed DOI PMC

Golubnitschaja O. Feeling cold and other underestimated symptoms in breast cancer: anecdotes or individual profiles for advanced patient stratification? EPMA J. 2017;8(1):17–22. doi: 10.1007/s13167-017-0086-6. PubMed DOI PMC

Golubnitschaja O, Flammer J. Individualised patient profile: clinical utility of Flammer syndrome phenotype and general lessons for predictive, preventive and personalised medicine. EPMA J. 2018;9(1):15-20. PubMed PMC

Bubnov R, Polivka J, Zubor P, Konieczka K, Golubnitschaja O. “Pre-metastatic niches” in breast cancer: are they created by or prior to the tumour onset? “Flammer Syndrome” relevance to address the question. EPMA J. 2017;8(2):141–157. doi: 10.1007/s13167-017-0092-8. PubMed DOI PMC

Evsevieva M, Sergeeva O, Mazurakova A, et al. Pre-pregnancy check-up of maternal vascular status and associated phenotype is crucial for the health of mother and offspring. EPMA J. 2022;13(3):351–366. doi: 10.1007/s13167-022-00294-1. PubMed DOI PMC

Golubnitschaja-Labudova O, Liu R, Decker C, Zhu P, Haefliger IO, Flammer J. Altered gene expression in lymphocytes of patients with normal-tension glaucoma. Curr Eye Res. 2000;21(5):867–876. doi: 10.1076/ceyr.21.5.867.5534. PubMed DOI

Yeghiazaryan K, Flammer J, Golubnitschaja O. Predictive molecular profiling in blood of healthy vasospastic individuals: clue to targeted prevention as personalised medicine to effective costs. EPMA J. 2010;1(2):263–272. doi: 10.1007/s13167-010-0032-3. PubMed DOI PMC

Koklesova L, Mazurakova A, Samec M, et al. Mitochondrial health quality control: measurements and interpretation in the framework of predictive, preventive, and personalized medicine. EPMA J. 2022;13(2):177–193. doi: 10.1007/s13167-022-00281-6. PubMed DOI PMC

Narayan SM, Wang PJ, Daubert JP. New concepts in sudden cardiac arrest to address an intractable epidemic: JACC state-of-the-art review. J Am Coll Cardiol. 2019;73(1):70–88. doi: 10.1016/j.jacc.2018.09.083. PubMed DOI PMC

Ha ACT, Doumouras BS, Wang CN, Tranmer J, Lee DS. Prediction of sudden cardiac arrest in the general population: review of traditional and emerging risk factors. Can J Cardiol. 2022;38(4):465–478. doi: 10.1016/j.cjca.2022.01.007. PubMed DOI

Kim YG, Han K-D, Roh S-Y, et al. Being Underweight Is Associated with increased risk of sudden cardiac death in people with diabetes mellitus. J Clin Med. 2023;12(3):1045. doi: 10.3390/jcm12031045. PubMed DOI PMC

Chen H, Deng Y, Li S. Relation of body mass index categories with risk of sudden cardiac death. Int Heart J. 2019;60(3):624–630. doi: 10.1536/ihj.18-155. PubMed DOI

Dale CE, Fatemifar G, Palmer TM, et al. Causal Associations of adiposity and body fat distribution with coronary heart disease, stroke subtypes, and type 2 diabetes mellitus: a mendelian randomization analysis. Circulation. 2017;135(24):2373–2388. doi: 10.1161/CIRCULATIONAHA.116.026560. PubMed DOI PMC

Chiu Y-W, Su M-H, Lin Y-F, Chen C-Y, Chen T-T, Wang S-H. Causal influence of sleeping phenotypes on the risk of coronary artery disease and sudden cardiac arrest: a mendelian randomization analysis. Sleep Health. 2023;S2352–7218(23):00097–99. PubMed

Modesto-Lowe V, Brooks D, Petry N. Methadone deaths: risk factors in pain and addicted populations. J Gen Intern Med. 2010;25(4):305–309. doi: 10.1007/s11606-009-1225-0. PubMed DOI PMC

Jacob L, Smith L, Koyanagi A, et al. Chronic low back pain and incident transient ischemic attack and stroke in general practices in Germany. Healthcare (Basel) 2023;11(10):1499. doi: 10.3390/healthcare11101499. PubMed DOI PMC

Wen L-Y, Ni H, Li K-S, et al. Asthma and Risk of stroke: a systematic review and meta-analysis. J Stroke Cerebrovasc Dis. 2016;25(3):497–503. doi: 10.1016/j.jstrokecerebrovasdis.2015.11.030. PubMed DOI

Finocchiaro G, Radaelli D, D’Errico S, et al. Sudden cardiac death among adolescents in the United Kingdom. J Am Coll Cardiol. 2023;81(11):1007–1017. doi: 10.1016/j.jacc.2023.01.041. PubMed DOI

Gullach AJ, Risgaard B, Lynge TH, et al. Sudden death in young persons with uncontrolled asthma- a nationwide cohort study in Denmark. BMC Pulm Med. 2015;15:35. doi: 10.1186/s12890-015-0033-z. PubMed DOI PMC

Hummel EM, Hessas E, Müller S, Beiter T, Fisch M, Eibl A, Wolf OT, Giebel B, Platen P, Kumsta R, Moser DA. Cell-free DNA release under psychosocial and physical stress conditions. Transl Psychiatry. 2018;8(1):236. doi: 10.1038/s41398-018-0264-x. PubMed DOI PMC

3P Medicon your risk reducer. Available from: https://www.3pmedicon.com/en/scientific-evidence/compromised-mitochondrial-health. Accessed 22 Jan 2024.

Crigna AT, Link B, Samec M, Giordano FA, Kubatka P, Golubnitschaja O. Endothelin-1 axes in the framework of predictive, preventive and personalised (3P) medicine. EPMA J. 2021;12(3):265–305. doi: 10.1007/s13167-021-00248-z. PubMed DOI PMC

Bushnell CD, Goldstein LB. Risk of ischemic stroke with tamoxifen treatment for breast cancer: a meta-analysis. Neurology. 2004;63(7):1230–1233. doi: 10.1212/01.WNL.0000140491.54664.50. PubMed DOI

D’Onofrio N, Martino E, Mele L, et al. Colorectal cancer apoptosis induced by dietary δ-valerobetaine involves PINK1/Parkin dependent-mitophagy and SIRT3. Int J Mol Sci. 2021;22(15):8117. doi: 10.3390/ijms22158117. PubMed DOI PMC

Liu J-X, Li J-H, Du C-H, Yan Y. Metabonomic study of biochemical changes in serum of PCPA-induced insomnia rats after treatment with Suanzaoren Decoction. Zhongguo Zhong Yao Za Zhi. 2022;47(6):1632–1641. PubMed

He J, Zheng W, Lu M, Yang X, Xue Y, Yao W. A controlled heat stress during late gestation affects thermoregulation, productive performance, and metabolite profiles of primiparous sow. J Therm Biol. 2019;81:33–40. doi: 10.1016/j.jtherbio.2019.01.011. PubMed DOI

Ahmed H, Leyrolle Q, Koistinen V, et al. Microbiota-derived metabolites as drivers of gut-brain communication. Gut Microbes. 2022;14(1):2102878. doi: 10.1080/19490976.2022.2102878. PubMed DOI PMC

Pochakom A, Mu C, Rho JM, Tompkins TA, Mayengbam S, Shearer J. Selective probiotic treatment positively modulates the microbiota-gut-brain axis in the BTBR mouse model of autism. Brain Sci. 2022;12(6):781. doi: 10.3390/brainsci12060781. PubMed DOI PMC

Gaggini M, Ndreu R, Michelucci E, Rocchiccioli S, Vassalle C. Ceramides as mediators of oxidative stress and inflammation in cardiometabolic disease. Int J Mol Sci. 2022;23(5):2719. doi: 10.3390/ijms23052719. PubMed DOI PMC

Roszczyc-Owsiejczuk K, Zabielski P. Sphingolipids as a culprit of mitochondrial dysfunction in insulin resistance and type 2 diabetes. Front Endocrinol (Lausanne) 2021;12:635175. doi: 10.3389/fendo.2021.635175. PubMed DOI PMC

Liu H, Wang X, Chen L, et al. Microglia modulate stable wakefulness via the thalamic reticular nucleus in mice. Nat Commun. 2021;12(1):4646. doi: 10.1038/s41467-021-24915-x. PubMed DOI PMC

Habibi J, DeMarco VG, Hulse JL, et al. Inhibition of sphingomyelinase attenuates diet - Induced increases in aortic stiffness. J Mol Cell Cardiol. 2022;167:32–39. doi: 10.1016/j.yjmcc.2022.03.006. PubMed DOI PMC

Fan K-Q, Li Y-Y, Wang H-L, et al. Stress-induced metabolic disorder in peripheral CD4+ T cells leads to anxiety-like behavior. Cell. 2019;179(4):864–879.e19. doi: 10.1016/j.cell.2019.10.001. PubMed DOI

Dumor K, Shoemaker-Moyle M, Nistala R, Whaley-Connell A. Arterial stiffness in hypertension: an update. Curr Hypertens Rep. 2018;20(8):72. doi: 10.1007/s11906-018-0867-x. PubMed DOI

Golubnitschaja O. What is the routine mitochondrial health check-up good for? A holistic approach in the framework of 3P medicine. In: Podbielska H, Kapalla M, editors. Predictive, preventive, and personalised medicine: from bench to bedside. Switzerland: Springer International Publishing; 2023. 10.1007/978-3-031-34884-6_3.

Xu K, Gao X, Xia G, et al. Rapid gut dysbiosis induced by stroke exacerbates brain infarction in turn. Gut 2021:gutjnl-2020-323263. PubMed

Spychala MS, Venna VR, Jandzinski M, et al. Age-related changes in the gut microbiota influence systemic inflammation and stroke outcome. Ann Neurol. 2018;84(1):23–36. doi: 10.1002/ana.25250. PubMed DOI PMC

Hill C, Guarner F, Reid G, et al. Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic. Nat Rev Gastroenterol Hepatol. 2014;11(8):506–14. doi: 10.1038/nrgastro.2014.66. PubMed DOI

Wu H, Chiou J. Potential benefits of probiotics and prebiotics for coronary heart disease and stroke. Nutrients. 2021;13(8):2878. doi: 10.3390/nu13082878. PubMed DOI PMC

Fröhlich H, Balling R, Beerenwinkel N, et al. From hype to reality: data science enabling personalized medicine. BMC Med. 2018;16(1):150. doi: 10.1186/s12916-018-1122-7. PubMed DOI PMC

Linden T, De Jong J, Lu C, Kiri V, Haeffs K, Fröhlich H. An explainable multimodal neural network architecture for predicting epilepsy comorbidities based on administrative claims data. Front Artif Intell. 2021;4:610197. doi: 10.3389/frai.2021.610197. PubMed DOI PMC

Jung S, Song M-K, Lee E, et al. Predicting ischemic stroke in patients with atrial fibrillation using machine learning. Front Biosci (Landmark Ed) 2022;27(3):80. doi: 10.31083/j.fbl2703080. PubMed DOI

Fröhlich H, Bontridder N, Petrovska-Delacréta D, et al. Leveraging the potential of digital technology for better individualized treatment of Parkinson’s disease. Front Neurol. 2022;13:788427. doi: 10.3389/fneur.2022.788427. PubMed DOI PMC

Warnat-Herresthal S, Schultze H, Shastry KL, et al. Swarm Learning for decentralized and confidential clinical machine learning. Nature. 2021;594(7862):265–270. doi: 10.1038/s41586-021-03583-3. PubMed DOI PMC

Advances in predictive, preventive and personalised medicine. Book series, Switzerland, Springer. Available from: https://link.springer.com/bookseries/10051. Accessed 22 Jan 2024.

Mitochondria-based holistic 3PM approach as the 'game-changer' for individualised rehabilitation-the proof-of-principle model by treated breast cancer survivors