Manika
danae manika (phd, university of texas at austin) is executive dean and professor of marketing at brunel business school. in the past, danae served as acting executive dean and deputy dean of the college of business, arts and social sciences at brunel university of london; and as associate head of brunel business school. before joining brunel, she was professor of marketing at newcastle university business school, where she led its london campus as academic group head and held the deputy director of research role at newcastle university business school. danae in the past has also held academic positions at queen mary university of london, durham university and the university of texas at austin; and is currently visiting professor at newcastle university and queen mary university of london. prior to her academic career, danae worked as an account planning intern in advertising agencies such as latinworks in austin, tx, and ddb in new york. she obtained a ph.d and a m.a. in advertising from the university of texas at austin, and a b.a. honours in marketing from university of stirling. danae’s recent research has been published in journals such as journal of service research, journal of business ethics, tourism management, annals of tourism research, psychology and marketing, european journal of marketing, technological forecasting and social change, journal of business research, european management review, and international business review, amongst others. using an interdisciplinary approach, danae’s research focuses on effective message construction for behaviour change within the contexts of health, well-being and the environment. she is involved in various consultancies (e.g., harrow council, royal borough of kensington and chelsea council, recoup, global action plan, texas comprehensive cancer control coalition), and her research has been supported by £450,000+ of funding (e.g., nerc, cruk, epsrc/innovate uk, red). danae is section editor for the journal of business ethics (section: marketing ethics) and an associate editor (ae) for business and society and the journal of current issues and research in advertising, while in the past she was ae for the journal of marketing management (2017-21). she is also currently on the editorial review boards of: technological forecasting & social change, and journal of marketing management; with guest editor experience across multiple top journals. danae also has experience as: funding reviewer for cancer research uk (2015-19); and track chair for top marketing conferences (ams wmc 2025 and 2023, tcr 2021). using an interdisciplinary approach, blending the lines between marketing, advertising and psychology her research aims to answer a fundamental marketing research question: how to diminish the knowledge-behaviour gap? particularly, her research focuses on effective message construction for behaviour change. it takes an information processing approach, which identifies, classifies and examines cognitive (e.g., knowledge, confidence, trust, values) and affective (e.g., pride, fear, disgust) factors that influence individuals’/consumers’/employees’ decisions and choices after exposure to campaigns/messages/interventions, and translate knowledge acquisition to behaviour change/formation. her research is theory-based but practically applicable research, and often uses health (e.g., weight control, alcohol consumption, vaccination), well-being and environmental (e.g. energy saving, recycling) social issues as the venue for understanding the knowledge-behaviour gap, with direct implications for persuasive communication and behavioural interventions that motivate health and environmental action. the campaigns/messages/interventions often examined involve digital components (e.g., websites, social media, mobile applications, online tracking tools) and technology adoption behaviours (e.g., adoption and usage of technology-based solutions). other projects with information technology and effective message construction focus include: social media service failure apologies, online petitions, and online political engagement. side projects include innovative research methodologies, female-disparaging adverts, and consumer animosity, amongst others. danae’s recent research has been published in journals such as journal of service research, journal of business ethics, tourism management, annals of tourism research, psychology and marketing, european journal of marketing, technological forecasting and social change, journal of business research, european management review, international business review, information technology and people, studies in higher education, journal of marketing management, computers in human behavior, international journal of advertising, journal of health communication, journal of marketing communications, health marketing quarterly, and multivariate behavioral research, amongst others. she often engages in research projects that require collaborations with other disciplines such as medicine, engineering and geography; and her research has been supported by£450,000+ of funding (e.g., nerc, cruk, epsrc/innovate uk, red, and arrow/erdf). she also strongly believes in the interplay and interdependence of academia, government, business and society and hence she is often involved in various consultancies (e.g., harrow council, royal borough of kensington and chelsea council, recoup, global action plan, texas comprehensive cancer control coalition), in line with her research (i.e., effective message construction for behaviour change). danae is section editor for the journal of business ethics (section: marketing ethics; ft50 journal), and associate editor (ae) for business and society and the journal of current issues and research in advertising, while in the past she was ae for the journal of marketing management (2017-21). she is also currently on the editorial review boards of: technological forecasting & social change, and journal of marketing management; with guest editor experience across multiple top journals. danae also has experience as: funding reviewer for cancer research uk (2015-19); and track chair for the academy of marketing science world marketing congress conference in 2023, the transformative consumer research conference in 2021, and the european social marketing association conference in 2016. knowledge-behaviour gap effective message construction for behaviour change information processing & persuasive communication health communication (employee) pro-environmental behaviour technology adoption for behaviour change consumer psychology social marketing advertising
![Professor Danae Manika]()
Professor Danae Manika
Danae Manika (PhD, University of Texas at Austin) is Executive Dean and Professor of Marketing at Brunel Business School. In the past, Danae served as Acting Executive Dean and Deputy Dean of the College of Business, Arts and Social Sciences at Brunel University of London; and as Associate Head of Brunel Business School. Before joining Brunel, she was Professor of Marketing at Newcastle University Business School, where she led its London Campus as Academic Group Head and held the Deputy Director of Research role at Newcastle University Business School. Danae in the past has also held academic positions at Queen Mary University of London, Durham University and the University of Texas at Austin; and is currently Visiting Professor at Newcastle University and Queen Mary University of London. Prior to her academic career, Danae worked as an Account Planning Intern in advertising agencies such as Latinworks in Austin, TX, and DDB in New York. She obtained a Ph.D and a M.A. in Advertising from the University of Texas at Austin, and a B.A. Honours in Marketing from University of Stirling. Danae’s recent research has been published in journals such as Journal of Service Research, Journal of Business Ethics, Tourism Management, Annals of Tourism Research, Psychology and Marketing, European Journal of Marketing, Technological Forecasting and Social Change, Journal of Business Research, European Management Review, and International Business Review, amongst others. Using an interdisciplinary approach, Danae’s research focuses on effective message construction for behaviour change within the contexts of health, well-being and the environment. She is involved in various consultancies (e.g., Harrow Council, Royal Borough of Kensington and Chelsea Council, RECOUP, Global Action Plan, Texas Comprehensive Cancer Control Coalition), and her research has been supported by £450,000+ of funding (e.g., NERC, CRUK, EPSRC/Innovate UK, RED). Danae is Section Editor for the Journal of Business Ethics (section: Marketing Ethics) and an Associate Editor (AE) for Business and Society and the Journal of Current Issues and Research in Advertising, while in the past she was AE for the Journal of Marketing Management (2017-21). She is also currently on the Editorial Review Boards of: Technological Forecasting & Social Change, and Journal of Marketing Management; with guest editor experience across multiple top journals. Danae also has experience as: funding reviewer for Cancer Research UK (2015-19); and track chair for top marketing conferences (AMS WMC 2025 and 2023, TCR 2021). Using an interdisciplinary approach, blending the lines between marketing, advertising and psychology her research aims to answer a fundamental marketing research question: How to diminish the knowledge-behaviour gap? Particularly, her research focuses on effective message construction for behaviour change. It takes an information processing approach, which identifies, classifies and examines cognitive (e.g., knowledge, confidence, trust, values) and affective (e.g., pride, fear, disgust) factors that influence individuals’/consumers’/employees’ decisions and choices after exposure to campaigns/messages/interventions, and translate knowledge acquisition to behaviour change/formation. Her research is theory-based but practically applicable research, and often uses health (e.g., weight control, alcohol consumption, vaccination), well-being and environmental (e.g. energy saving, recycling) social issues as the venue for understanding the knowledge-behaviour gap, with direct implications for persuasive communication and behavioural interventions that motivate health and environmental action. The campaigns/messages/interventions often examined involve digital components (e.g., websites, social media, mobile applications, online tracking tools) and technology adoption behaviours (e.g., adoption and usage of technology-based solutions). Other projects with information technology and effective message construction focus include: social media service failure apologies, online petitions, and online political engagement. Side projects include innovative research methodologies, female-disparaging adverts, and consumer animosity, amongst others. Danae’s recent research has been published in journals such as Journal of Service Research, Journal of Business Ethics, Tourism Management, Annals of Tourism Research, Psychology and Marketing, European Journal of Marketing, Technological Forecasting and Social Change, Journal of Business Research, European Management Review, International Business Review, Information Technology and People, Studies in Higher Education, Journal of Marketing Management, Computers in Human Behavior, International Journal of Advertising, Journal of Health Communication, Journal of Marketing Communications, Health Marketing Quarterly, and Multivariate Behavioral Research, amongst others. She often engages in research projects that require collaborations with other disciplines such as medicine, engineering and geography; and her research has been supported by£450,000+ of funding (e.g., NERC, CRUK, EPSRC/Innovate UK, RED, and Arrow/ERDF). She also strongly believes in the interplay and interdependence of academia, government, business and society and hence she is often involved in various consultancies (e.g., Harrow Council, Royal Borough of Kensington and Chelsea Council, RECOUP, Global Action Plan, Texas Comprehensive Cancer Control Coalition), in line with her research (i.e., effective message construction for behaviour change). Danae is Section Editor for the Journal of Business Ethics (section: Marketing Ethics; FT50 journal), and Associate Editor (AE) for Business and Society and the Journal of Current Issues and Research in Advertising, while in the past she was AE for the Journal of Marketing Management (2017-21). She is also currently on the Editorial Review Boards of: Technological Forecasting & Social Change, and Journal of Marketing Management; with guest editor experience across multiple top journals. Danae also has experience as: funding reviewer for Cancer Research UK (2015-19); and track chair for the Academy of Marketing Science World Marketing Congress Conference in 2023, the Transformative Consumer Research Conference in 2021, and the European Social Marketing Association Conference in 2016. Knowledge-Behaviour Gap Effective Message Construction for Behaviour Change Information Processing & Persuasive Communication Health Communication (Employee) Pro-environmental Behaviour Technology Adoption for Behaviour Change Consumer Psychology Social Marketing Advertising
Pazoki
raha pazok md phd fhea is a medical doctor and an epidemiologist. she studied epidemiology at the netherlands institute for health sciences (nihes) and in the university of amsterdam. she worked with various cohort and case control studies such as the arrhythmia genetics in the netherlands (agnes), the rotterdam study, the airwave health monitoring study and the uk bio bank. in 2016, she joined the department of epidemiology and bio-statistics at imperial college london as a research associate. in 2020, she started a teaching & research academic position at brunel university london. dr pazoki specializes in the field of health data research, with a primary focus on the epidemiology of cardiometabolic diseases. she holds a particular interest in exploring causal inference and precision medicine by leveraging genomics and extensive health data sets with sample sizes exceeding 500,000 individuals. her expertise spans various domains, including precision medicine, global health, interventions, and the application of artificial intelligence for predicting health outcomes. she harbors a keen interest in identification of the relationship between circulating molecules and biomarkers, nutrition, lifestyle choices, genetic factors, and their collective contribution to the modulation of health risk factors and outcomes. she was the first to identify 517 novel genetic loci associated with liver enzymes and the first to show the causal effect of liver dysfunction on cardiovascular diseases. in addition, she is the first to show the effect of the alcohol consumption wdpcp gene in lipid metabolism, and liver cirrhosis. (genetic) epidemiology of cardiovascular diseases big data genome-wide association studies genetic risk scores mendelian randomization machine learning dr paozki is a founder and director of the cardiovascular and metabolic research group hosting researchers and academics across brunel university with direct or indirect research interest involving cardiometabolic aetiology, prevention, and health. we work in various areas to identify causes of cardiometabolic diseases (environmental, lifestyle, molecular, and clinical) and provide insight into how they interplay. we use the information for better prevention of cardiometabolic diseases in the community. if you are a msc graduates (with upper second class degree or higher) in the relevant field to the above research area, please contact dr raha pazoki (raha.pazoki@brunel.ac.uk). postgraduate fees and funding | brunel university london or scholarships and bursaries | brunel university london and other funding | brunel university london selected publications karkia, r., maccarthy, g., payne, a., karteris, e., pazoki, r., & chatterjee, j. (n.d.). the association between metabolic syndrome and the risk of endometrial cancer in pre- and post-menopausal women: a uk biobank study. journal of clinical medicine, 14(3), 751. doi:10.3390/jcm14030751 hezekiah, c., & pazoki, r. (2024). physical activity and favourable adiposity genetic liability reduce the risk of hypertension among high body mass individuals. doi:10.1101/2024.12.18.24319295 maccarthy, g., & pazoki, r. (2024). using machine learning to evaluate the value of genetic liabilities in the classification of hypertension within the uk biobank. journal of clinical medicine, 13(10), 1-20. doi:10.3390/jcm13102955 hezekiah, c., blakemore, a. i., bailey, d. p., & pazoki, r. (2024). physical activity alters the effect of genetic determinants of adiposity on hypertension among individuals of european ancestry in the ukb. scandinavian journal of medicine and science in sports, 34(5), 1-13. doi:10.1111/sms.14636 o’farrell, f., aleyakpo, b., mustafa, r., jiang, x., pinto, r. c., elliott, p., . . . pazoki, r. (2023). evidence for involvement of the alcohol consumption wdpcp gene in lipid metabolism, and liver cirrhosis. scientific reports, 13(1), 1-13. doi:10.1038/s41598-023-47371-7 hezekiah, c., blakemore, a. i., bailey, d. p., & pazoki, r. (2023). physical activity reduces the effect of adiposity genetic liability on hypertension risk in the uk biobank cohort. doi:10.1101/2023.09.22.23295992 roa-díaz, z. m., teuscher, j., gamba, m., bundo, m., grisotto, g., wehrli, f., . . . muka, t. (2022). gene-diet interactions and cardiovascular diseases: a systematic review of observational and clinical trials. bmc cardiovascular disorders, 22(1), 1-22. doi:10.1186/s12872-022-02808-1 o'farrell, f., jiang, x., aljifri, s., & pazoki, r. (2022). molecular alterations caused by alcohol consumption in the uk biobank: a mendelian randomisation study. nutrients, 14(14), 1-14. doi:10.3390/nu14142943 jiang, x., anasanti, m. d., drenos, f., blakemore, a. i., & pazoki, r. (2022). urinary sodium excretion enhances the effect of alcohol on blood pressure. healthcare, 10(7), 1-13. doi:10.3390/healthcare10071296 jiang, x., anasanti, m., drenos, f., blakemore, a., & pazoki, r. (2022). urinary sodium excretion enhances the effect of alcohol on blood pressure. doi:10.20944/preprints202205.0385.v1 said, s., pazoki, r., karhunen, v., võsa, u., ligthart, s., bodinier, b., . . . dehghan, a. (2022). genetic analysis of over half a million people characterises c-reactive protein loci. nature communications, 13(1), 1-10. doi:10.1038/s41467-022-29650-5 roa-díaz, z. m., asllanaj, e., amin, h. a., rojas, l. z., nano, j., ikram, m. a., . . . muka, t. (2021). age at natural menopause and blood pressure traits: mendelian randomization study. journal of clinical medicine, 10(19), 1-13. doi:10.3390/jcm10194299 jiang, x., gao, h., elliott, p., & pazoki, r. (2022). percentage of explained variance in alcohol consumption by genetic risk score in the uk biobank. in european journal of human genetics vol. 30 (pp. 528-529). online. doi:10.1038/s41431-021-01026-1 evangelou, e., suzuki, h., bai, w., pazoki, r., gao, h., matthews, p. m., & elliott, p. (2021). alcohol consumption in the general population is associated with structural changes in multiple organ systems. elife, 10. doi:10.7554/elife.65325 pazoki, r., vujkovic, m., elliott, j., evangelou, e., gill, d., mohsen, g., . . . elliott, p. (2021). genetic analysis in european ancestry individuals identifies 517 loci associated with liver enzymes. nature communications, 12, 1-12. doi:10.1038/s41467-021-22338-2 pazoki, r., lin, b. d., van eijk, k. r., schijven, d., de zwarte, s., guloksuz, s., & luykx, j. j. (2020). phenome-wide and genome-wide analyses of quality of life in schizophrenia. bjpsych open, 7(1), 1-7. doi:10.1192/bjo.2020.140 cabrera, c. p., pazoki, r., giri, a., hellwege, j. n., evangelou, e., ramirez, j., . . . warren, h. r. (2020). multi-trait genome-wide association analysis of blood pressure identifies 45 additional loci. in european journal of human genetics vol. 28 (pp. 105). virtual conference. doi:10.1038/s41431-020-00740-6 elliott, p., muller, d. c., schneider-luftman, d., pazoki, r., evangelou, e., dehghan, a., . . . tzoulaki, i. (2020). estimated 24-hour urinary sodium excretion and incident cardiovascular disease and mortality among 398628 individuals in uk biobank. hypertension, 76(3), 683-691. doi:10.1161/hypertensionaha.119.14302 robinson, o., chadeau hyam, m., karaman, i., climaco pinto, r., ala-korpela, m., handakas, e., . . . vineis, p. (2020). determinants of accelerated metabolomic and epigenetic aging in a uk cohort. aging cell, 19(6), 1-13. doi:10.1111/acel.13149 schmidt, a. f., holmes, m. v., preiss, d., swerdlow, d. i., denaxas, s., fatemifar, g., . . . dehghan, a. (2019). phenome-wide association analysis of ldl-cholesterol lowering genetic variants in pcsk9. bmc cardiovascular disorders, 19(1). doi:10.1186/s12872-019-1187-z pazoki, r., lin, b. d., van eijk, k. r., schijven, d., guloksuz, s., & luykx, j. j. (2019). phenome-wide and genome-wide analyses of quality of life in schizophrenia. biorxiv, preprint. doi:10.1101/744045 pazoki, r., evangelou, e., mosen-ansorena, d., pinto, r., karaman, i., blakeley, p., . . . dehghan, a. (2019). pathways underlying urinary sodium and potassium excretion and the link to blood pressure and cardiovascular disease. in journal of hypertension vol. 37 (pp. e74). ovid technologies (wolters kluwer health). doi:10.1097/01.hjh.0000571108.82708.c0 pazoki, r., evangelou, e., mosen-ansorena, d., pinto, r. c., karaman, i., blakeley, p., . . . dehghan, a. (2019). gwas for urinary sodium and potassium excretion highlights pathways shared with cardiovascular traits. nature communications, 10(1), 1-11. doi:10.1038/s41467-019-11451-y evangelou, e., gao, h., chu, c., ntritsos, g., blakeley, p., butts, a. r., . . . elliott, p. (2019). new alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders. nature human behaviour, 3(9), 950-961. doi:10.1038/s41562-019-0653-z luykx, j., pazoki, r., lin, b., guloksuz, s., schijven, d., van eijk, k., & group collaborators. (2019). t168. phenome-wide and genome-wide analyses of quality of life in patients with psychosis. in biological psychiatry vol. 85 (pp. s194). elsevier bv. doi:10.1016/j.biopsych.2019.03.491 pazoki, r. (2019). cardiovascular disease, abo locus, and markers of platelet functionality. international journal of cardiology, 286(1 july 2019), 162-163. doi:10.1016/j.ijcard.2019.03.061 de vries, p. s., brown, m. r., bentley, a. r., sung, y. j., winkler, t. w., ntalla, i., . . . giulianini, f. (2019). multiancestry genome-wide association study of lipid levels incorporating gene-alcohol interactions. american journal of epidemiology, 188(6), 1033-1054. doi:10.1093/aje/kwz005 robinson, o., hyam, m. c., karaman, i., pinto, r. c., fiorito, g., gao, h., . . . vineis, p. (2018). determinants of accelerated metabolomic and epigenetic ageing in a uk cohort. biorxiv, preprint. doi:10.1101/411603 kilpeläinen, t. o., bentley, a. r., noordam, r., sung, y. j., schwander, k., winkler, t. w., . . . krieger, j. e. (2019). multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. nature communications, 10(1). doi:10.1038/s41467-018-08008-w ashar, f. n., mitchell, r. n., albert, c. m., newton-cheh, c., brody, j. a., müller-nurasyid, m., . . . sotoodehnia, n. (2018). a comprehensive evaluation of the genetic architecture of sudden cardiac arrest. european heart journal, 39(44), 3961-3969. doi:10.1093/eurheartj/ehy474 evangelou, e., warren, h. r., mosen-ansorena, d., mifsud, b., pazoki, r., gao, h., . . . gandin, i. (2018). genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. nature genetics, 50(10), 1412-1425. doi:10.1038/s41588-018-0205-x davies, g., lam, m., harris, s. e., trampush, j. w., luciano, m., hill, w. d., . . . kleineidam, l. (2018). study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. nature communications, 9(1). doi:10.1038/s41467-018-04362-x pazoki, r., dehghan, a., evangelou, e., warren, h., gao, h., caulfield, m., . . . tzoulaki, i. (2018). genetic predisposition to high blood pressure and lifestyle factors: associations with midlife blood pressure levels and cardiovascular events. in circulation vol. 137 (pp. 653-661). doi:10.1161/circulationaha.117.030898 pazoki, r. (2018). methods for polygenic traits. international journal of cardiology, 1793, 145-156. doi:10.1007/978-1-4939-7868-7_10 dr. raha pazoki's research is centered around health data science, with a strong emphasis on cardiometabolic diseases. 🔬 key research themes cardiometabolic epidemiology investigating the genetic and environmental determinants of cardiovascular and metabolic disorders. studying conditions like hypertension, diabetes, liver dysfunction, and lipid metabolism. genomics and precision medicine utilizing large-scale genomic data (e.g., uk biobank) to identify genetic loci associated with disease. she was the first to identify 517 novel genetic loci linked to liver enzymes and demonstrated their causal role in cardiovascular disease. causal inference in epidemiology applying mendelian randomization and other causal inference techniques to understand the relationships between biomarkers, lifestyle factors, and disease outcomes. lifestyle, nutrition, and biomarkers exploring how diet, alcohol consumption, and other lifestyle factors interact with genetic predispositions to influence health. artificial intelligence in health prediction leveraging ai and machine learning to predict health outcomes using large datasets. global health and interventions engaging in research that informs public health interventions and policies, especially in the context of global health disparities. dr. raha pazoki is addressing several critical problems in public health and biomedical science, particularly in the context of cardiometabolic diseases. here's a breakdown of the problems she's tackling and why they matter: 🧩 problems she’s solving understanding genetic and environmental risk factors problem: cardiovascular and metabolic diseases (like heart disease, diabetes, and liver dysfunction) are influenced by a complex interplay of genetic and lifestyle factors. her work: she identifies both genetic variants and non-genetic contributors (e.g., diet, alcohol, physical activity) that increase disease risk. causal inference in epidemiology problem: observational studies often show associations, but not causation. her work: she uses mendelian randomization to determine whether certain biomarkers or behaviors cause disease, rather than just correlate with it. improving disease prediction and prevention problem: current risk prediction models often lack precision, especially across diverse populations. her work: by integrating genomic data with clinical and lifestyle information, she helps build more accurate, personalized prediction tools. bridging the gap between big data and clinical practice problem: despite the explosion of health data, translating it into actionable insights remains a challenge. her work: she applies ai and machine learning to large datasets (e.g., uk biobank) to uncover patterns that can inform public health interventions and clinical guidelines. 🌍 why it matters public health impact: cardiometabolic diseases are leading causes of death globally. understanding their root causes can lead to better prevention strategies and reduced healthcare costs. equity in healthcare: her work helps ensure that genetic research benefits diverse populations. scientific rigor: by focusing on causal relationships, her research improves the reliability of health recommendations. policy and practice: her findings can inform national health policies, especially around lifestyle interventions and early screening. dr. raha pazoki’s research has significant clinical and societal applications, particularly in the prevention, early detection, and personalized treatment of cardiometabolic diseases. here's how her work translates into real-world impact: 🏥 clinical applications personalized risk prediction by integrating genetic data with lifestyle factors, her research helps develop precision medicine tools that can predict an individual’s risk for conditions like hypertension, liver disease, and cardiovascular disease. example: her work on genetic liabilities and hypertension using machine learning improves how clinicians classify and manage high blood pressure. causal insights for treatment using mendelian randomization, she identifies causal relationships between biomarkers (like liver enzymes or alcohol-related genes) and diseases. this helps clinicians target the right pathways for intervention. improved screening and diagnostics her findings on gene-diet interactions and biomarker profiles can inform screening guidelines, especially for at-risk populations, enabling earlier and more accurate diagnoses . 🌍 societal applications public health policy her research supports evidence-based policies on alcohol consumption, nutrition, and physical activity by showing how these factors interact with genetics to influence disease risk. health equity by analyzing large, diverse datasets like the uk biobank, she contributes to more inclusive health research, ensuring that findings are applicable across different ethnic and socioeconomic groups. ai in healthcare her use of artificial intelligence to analyze complex health data helps automate and scale health risk assessments, making them more accessible in both high- and low-resource settings . education and capacity building as a senior lecturer and research leader, she trains the next generation of scientists in data-driven, ethical, and impactful health research. dr. raha pazoki’s research is already showing real-world outcomes and holds strong near-future potential in both clinical and public health domains. ✅ real-world outcomes stroke risk prediction using genetics and ai in a recent study, dr. pazoki and her team demonstrated that incorporating genetic liability scores into machine learning models significantly improves the prediction of stroke risk. this model, using uk biobank data, showed that individuals with higher genetic risk had a 14% increased risk of stroke. the best-performing model achieved an auc of 69.5, indicating strong predictive power. discovery of genetic loci for liver enzymes she was the first to identify 517 novel genetic loci associated with liver enzymes, and showed their causal role in cardiovascular disease .this discovery is already influencing how researchers and clinicians understand liver function as a predictive biomarker for heart disease. alcohol-related genetic insights her work on the wdpcp gene revealed its role in alcohol metabolism and its link to liver cirrhosis and lipid disorders, which could inform personalized lifestyle recommendations and early intervention. 🔮 near-future potential precision medicine tools her research is paving the way for genetically-informed clinical decision-making, where a patient’s genetic profile could guide personalized prevention and treatment plans for cardiometabolic diseases. ai-driven health risk platforms by combining ai with genomics, her models could be integrated into clinical software to help gps and specialists identify high-risk patients earlier, especially for stroke, liver disease, and hypertension. public health interventions her findings on the interaction between lifestyle and genetic risk can inform targeted public health campaigns, especially in populations with high genetic susceptibility to certain diseases. global health equity her use of large, diverse datasets ensures that these tools and insights are applicable across ethnicities, helping reduce health disparities in genomic medicine. dr. raha pazoki’s work significantly advances our understanding of health, ageing, and wellbeing, particularly through the lens of genomics, lifestyle, and precision medicine. here's how her research contributes to these areas: 🧠 improving understanding genetic and lifestyle interactions her studies reveal how genetic predispositions interact with lifestyle factors like physical activity, diet, and alcohol consumption to influence ageing-related conditions such as hypertension, liver dysfunction, and cardiovascular disease . causal pathways in ageing diseases by applying mendelian randomization, she identifies causal relationships between biomarkers (e.g., liver enzymes, lipid levels) and age-related diseases, helping to clarify which factors are true drivers of decline in health . 🩺 enhancing treatment and prevention precision medicine for ageing populations her work supports the development of personalized treatment strategies by integrating genetic risk scores with clinical and lifestyle data. this is especially valuable for older adults, who often have complex, multi-factorial health profiles. early detection of age-related conditions her research on biomarkers and genetic loci enables earlier identification of individuals at risk for diseases like stroke, liver cirrhosis, and metabolic syndrome—conditions that become more prevalent with age . lifestyle-based interventions she has shown that physical activity can mitigate genetic risk for conditions like hypertension, offering actionable insights for public health and individual prevention strategies . 🌍 promoting wellbeing and healthy ageing data-driven public health her findings inform public health campaigns that promote healthy behaviours tailored to genetic risk, supporting longer, healthier lives. reducing health inequities by using large, diverse datasets, her work ensures that genomic insights are inclusive, helping to close gaps in health outcomes across different populations. ai for ageing research she applies machine learning to predict health outcomes in ageing populations, enabling scalable, cost-effective tools for monitoring and intervention code and academic year title level credits core/option (c/o) module leader (y/n) % teaching contribution bb3711-2022/3 introduction to epidemiology and disease prevention (block leading and delivery) 6 20 o y 95 bb3711-2023/4 introduction to epidemiology and disease prevention (block leading and delivery) 6 20 o y 100 bb3711-2024/5 introduction to epidemiology and disease prevention (block leading and delivery) 6 20 o y 100 bb3804-2023/4 synoptic examinations 3 (leading and marking) 6 20 c y 75 bb3804-2024/5 synoptic examinations 3 (leading and marking) 6 20 c y 75 bb3804-2021/22 synoptic examination 3 (marking, cross moderating) 6 20 c n 5 bb1719-2021/22 introduction to data analysis (leading, delivering, marking) 4 20 c y 90 bb3091-2021/22 final year project (leading, delivering, marking) 6 40 c y 50 bb3091-2022/23 final year project (support of leading, marking, delivering, supervision) 6 40 c n 20 bb3091-2023/24 final year project (marking, delivering, supervision) 6 40 c n 6 bb3091-2024/25 final year project (marking, delivering, supervision) 6 40 c n 6 bb3803-2022/23 biomedical sciences examinations 3 (marking, question design) 6 20 c n 20 bb3803-2023/24 biomedical sciences examinations 3 (marking, question design) 6 20 c n 20 bb3803-2024/25 biomedical sciences examinations 3 (marking, question design) 6 20 c n 20 bb1804-2023/24 practical skills 3: molecular analysis (marking) 4 20 c n 20 bb1804-2022/23 practical skills 3: molecular analysis (marking) 4 20 c n 20 bb2710-2021/22 analytical biochemistry (moderation) 5 20 c n 3 bb2709-2021/22 genetics, genomics and human health 5 20 c n 15 bb2709-2024/5 genetics, genomics and human health 5 20 c n 15 bb3801-2022/3 scientific communication -essay (coursework design & delivery, marking) 6 20 c n 20 bb3801-2023/4 scientific communication -essay (coursework design & delivery, marking) 6 20 c n 20 bb3801-2024/5 scientific communication -essay (coursework design & delivery, marking) 6 20 c n 20 bb2801-2021/22 career skills 5 20 c n 5 bb2555-2022/23 placement 5 20 c n 5 bb2555-2023/24 placement 5 20 c n 5 bb2555-2021/22 placement 5 20 c n 5 bb1801a-2023/24 research and communication skills - presentation 4 20 c n 3 bb1801a-2024/25 research and communication skills - presentation 4 20 c n 3 bb1801c-2023/24 research and communication skills - portfolio 4 20 c n 3 bb1806-2023/24 synoptic examination 1 (marking) 4 20 c n 3 bb1806-2022/23 synoptic examination 1 (marking) 4 20 c n 3 bb2802-2021/22 primary literature interrogation and synthesis (supervision, marking) 5 20 c n 3 bb2802-2022/23 primary literature interrogation and synthesis (supervision, marking) 5 20 c n 3 bb2802-2023/24 primary literature interrogation and synthesis (supervision, marking) 5 20 c n 3 bb2804-2023/24 data analysis, interpretation and presentation (poster, marking) 5 20 c n 3 bb2804-2021/22 data analysis, interpretation and presentation (poster, marking) 5 20 c n 3 bb2805-2021/22 biomedical sciences examinations 2 (moderation) 5 20 c n 3 bb2805-2022/23 biomedical sciences examinations 2 (moderation) 5 20 c n 3 bb2805-2023/24 biomedical sciences examinations 2 (moderation) 5 20 c n 3 bb3801-2021/22 scientific communication – presentation (marking) 6 20 c n 3 bb3801b (term 1)-2022/23 scientific communication – presentation (marking) 6 20 c n 3 bb3801b (term 1)-2023/24 scientific communication – presentation (marking) 6 20 c n 3 bb3802b (term 2)-2023/24 problem solving and data analysis – reflection (marking) 6 20 c n 3 bb3802b (term 2)-2022/23 problem solving and data analysis – reflection (marking) 6 20 c n 3 bb1801a-2022/23 research and communication skills - presentation 4 20 c n 3 bb1801-2021/22 research and communication skills - presentation 4 20 c n 3 pgt modules: code and academic year title credits core/option (c/o) module leader (y/n) % teaching contribution (excluding pgt dissertation supervision) bb5716-2024/2025 vaccines and treatment for infection and inflammation 7 20 n 10 bb5716-2023/2024 vaccines and treatment for infection and inflammation 7 20 n 10 bb5713-2022/2023 radiation, toxicology and pollution 7 20 n 10 bb5713-2021/2022 radiation, toxicology and pollution 7 20 n 10 bb5804-2024/25 scientific communication 7 20 n 10 bb5804-2021/22 scientific communication 7 20 n 10 pgt dissertation supervision: code and academic year title number primary supervisions number of secondary supervisions 2024/25-bb5604 mendelian randomisation study of lipid levels on alcohol consumption using mr-base 1 0 2022/23-bb5604 genetic risk score of alcohol consumption and risk of type 2 diabetes 1 0
![Dr Raha Pazoki]()
Dr Raha Pazoki
Raha Pazok MD PhD FHEA is a medical doctor and an epidemiologist. She studied Epidemiology at the Netherlands Institute for Health Sciences (NIHES) and in the University of Amsterdam. She worked with various cohort and case control studies such as the Arrhythmia Genetics in the Netherlands (AGNES), the Rotterdam Study, the Airwave Health Monitoring Study and the UK Bio bank. In 2016, she joined the Department of Epidemiology and Bio-statistics at Imperial College London as a Research Associate. In 2020, she started a Teaching & Research academic position at Brunel University London. Dr Pazoki specializes in the field of health data research, with a primary focus on the epidemiology of cardiometabolic diseases. She holds a particular interest in exploring causal inference and precision medicine by leveraging genomics and extensive health data sets with sample sizes exceeding 500,000 individuals. Her expertise spans various domains, including precision medicine, global health, interventions, and the application of artificial intelligence for predicting health outcomes. She harbors a keen interest in identification of the relationship between circulating molecules and biomarkers, nutrition, lifestyle choices, genetic factors, and their collective contribution to the modulation of health risk factors and outcomes. She was the first to identify 517 novel genetic loci associated with liver enzymes and the first to show the causal effect of liver dysfunction on cardiovascular diseases. In addition, she is the first to show the effect of the alcohol consumption WDPCP gene in lipid metabolism, and liver cirrhosis. (Genetic) Epidemiology of Cardiovascular Diseases Big Data Genome-wide Association Studies Genetic risk scores Mendelian Randomization Machine Learning Dr Paozki is a founder and director of the Cardiovascular and Metabolic Research Group hosting researchers and academics across Brunel university with direct or indirect research interest involving cardiometabolic aetiology, prevention, and health. We work in various areas to identify causes of cardiometabolic diseases (environmental, lifestyle, molecular, and clinical) and provide insight into how they interplay. We use the information for better prevention of cardiometabolic diseases in the community. If you are a MSc graduates (with upper second class degree or higher) in the relevant field to the above research area, please contact Dr Raha Pazoki (raha.pazoki@brunel.ac.uk). Postgraduate fees and funding | Brunel University London or Scholarships and Bursaries | Brunel University London and Other funding | Brunel University London Selected publications Karkia, R., Maccarthy, G., Payne, A., Karteris, E., Pazoki, R., & Chatterjee, J. (n.d.). The Association Between Metabolic Syndrome and the Risk of Endometrial Cancer in Pre- and Post-Menopausal Women: A UK Biobank Study. Journal of Clinical Medicine, 14(3), 751. doi:10.3390/jcm14030751 Hezekiah, C., & Pazoki, R. (2024). Physical activity and favourable adiposity genetic liability reduce the risk of hypertension among high body mass individuals. doi:10.1101/2024.12.18.24319295 MacCarthy, G., & Pazoki, R. (2024). Using Machine Learning to Evaluate the Value of Genetic Liabilities in the Classification of Hypertension within the UK Biobank. Journal of Clinical Medicine, 13(10), 1-20. doi:10.3390/jcm13102955 Hezekiah, C., Blakemore, A. I., Bailey, D. P., & Pazoki, R. (2024). Physical activity alters the effect of genetic determinants of adiposity on hypertension among individuals of European ancestry in the UKB. Scandinavian Journal of Medicine and Science in Sports, 34(5), 1-13. doi:10.1111/sms.14636 O’Farrell, F., Aleyakpo, B., Mustafa, R., Jiang, X., Pinto, R. C., Elliott, P., . . . Pazoki, R. (2023). Evidence for involvement of the alcohol consumption WDPCP gene in lipid metabolism, and liver cirrhosis. Scientific Reports, 13(1), 1-13. doi:10.1038/s41598-023-47371-7 Hezekiah, C., Blakemore, A. I., Bailey, D. P., & Pazoki, R. (2023). Physical activity reduces the effect of adiposity genetic liability on hypertension risk in the UK Biobank cohort. doi:10.1101/2023.09.22.23295992 Roa-Díaz, Z. M., Teuscher, J., Gamba, M., Bundo, M., Grisotto, G., Wehrli, F., . . . Muka, T. (2022). Gene-diet interactions and cardiovascular diseases: a systematic review of observational and clinical trials. BMC Cardiovascular Disorders, 22(1), 1-22. doi:10.1186/s12872-022-02808-1 O'Farrell, F., Jiang, X., Aljifri, S., & Pazoki, R. (2022). Molecular Alterations Caused by Alcohol Consumption in the UK Biobank: A Mendelian Randomisation Study. Nutrients, 14(14), 1-14. doi:10.3390/nu14142943 Jiang, X., Anasanti, M. D., Drenos, F., Blakemore, A. I., & Pazoki, R. (2022). Urinary Sodium Excretion Enhances the Effect of Alcohol on Blood Pressure. Healthcare, 10(7), 1-13. doi:10.3390/healthcare10071296 Jiang, X., Anasanti, M., Drenos, F., Blakemore, A., & Pazoki, R. (2022). Urinary Sodium Excretion Enhances the Effect of Alcohol on Blood Pressure. doi:10.20944/preprints202205.0385.v1 Said, S., Pazoki, R., Karhunen, V., Võsa, U., Ligthart, S., Bodinier, B., . . . Dehghan, A. (2022). Genetic analysis of over half a million people characterises C-reactive protein loci. Nature Communications, 13(1), 1-10. doi:10.1038/s41467-022-29650-5 Roa-Díaz, Z. M., Asllanaj, E., Amin, H. A., Rojas, L. Z., Nano, J., Ikram, M. A., . . . Muka, T. (2021). Age at natural menopause and blood pressure traits: Mendelian randomization study. Journal of Clinical Medicine, 10(19), 1-13. doi:10.3390/jcm10194299 Jiang, X., Gao, H., Elliott, P., & Pazoki, R. (2022). Percentage of explained variance in alcohol consumption by genetic risk score in the UK Biobank. In EUROPEAN JOURNAL OF HUMAN GENETICS Vol. 30 (pp. 528-529). Online. doi:10.1038/s41431-021-01026-1 Evangelou, E., Suzuki, H., Bai, W., Pazoki, R., Gao, H., Matthews, P. M., & Elliott, P. (2021). Alcohol consumption in the general population is associated with structural changes in multiple organ systems. eLife, 10. doi:10.7554/eLife.65325 Pazoki, R., Vujkovic, M., Elliott, J., Evangelou, E., Gill, D., Mohsen, G., . . . elliott, P. (2021). Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes. Nature Communications, 12, 1-12. doi:10.1038/s41467-021-22338-2 Pazoki, R., Lin, B. D., van Eijk, K. R., Schijven, D., de Zwarte, S., Guloksuz, S., & Luykx, J. J. (2020). Phenome-wide and genome-wide analyses of quality of life in schizophrenia. BJPsych Open, 7(1), 1-7. doi:10.1192/bjo.2020.140 Cabrera, C. P., Pazoki, R., Giri, A., Hellwege, J. N., Evangelou, E., Ramirez, J., . . . Warren, H. R. (2020). Multi-trait genome-wide association analysis of blood pressure identifies 45 additional loci. In EUROPEAN JOURNAL OF HUMAN GENETICS Vol. 28 (pp. 105). Virtual Conference. doi:10.1038/s41431-020-00740-6 Elliott, P., Muller, D. C., Schneider-Luftman, D., Pazoki, R., Evangelou, E., Dehghan, A., . . . Tzoulaki, I. (2020). Estimated 24-Hour Urinary Sodium Excretion and Incident Cardiovascular Disease and Mortality among 398628 Individuals in UK Biobank. Hypertension, 76(3), 683-691. doi:10.1161/HYPERTENSIONAHA.119.14302 Robinson, O., Chadeau Hyam, M., Karaman, I., Climaco Pinto, R., Ala-Korpela, M., Handakas, E., . . . Vineis, P. (2020). Determinants of accelerated metabolomic and epigenetic aging in a UK cohort. Aging Cell, 19(6), 1-13. doi:10.1111/acel.13149 Schmidt, A. F., Holmes, M. V., Preiss, D., Swerdlow, D. I., Denaxas, S., Fatemifar, G., . . . Dehghan, A. (2019). Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9. BMC Cardiovascular Disorders, 19(1). doi:10.1186/s12872-019-1187-z Pazoki, R., Lin, B. D., van Eijk, K. R., Schijven, D., Guloksuz, S., & Luykx, J. J. (2019). Phenome-wide and Genome-wide Analyses of Quality of Life in Schizophrenia. bioRxiv, preprint. doi:10.1101/744045 Pazoki, R., Evangelou, E., Mosen-Ansorena, D., Pinto, R., Karaman, I., Blakeley, P., . . . Dehghan, A. (2019). PATHWAYS UNDERLYING URINARY SODIUM AND POTASSIUM EXCRETION AND THE LINK TO BLOOD PRESSURE AND CARDIOVASCULAR DISEASE. In Journal of Hypertension Vol. 37 (pp. e74). Ovid Technologies (Wolters Kluwer Health). doi:10.1097/01.hjh.0000571108.82708.c0 Pazoki, R., Evangelou, E., Mosen-Ansorena, D., Pinto, R. C., Karaman, I., Blakeley, P., . . . Dehghan, A. (2019). GWAS for urinary sodium and potassium excretion highlights pathways shared with cardiovascular traits. Nature Communications, 10(1), 1-11. doi:10.1038/s41467-019-11451-y Evangelou, E., Gao, H., Chu, C., Ntritsos, G., Blakeley, P., Butts, A. R., . . . Elliott, P. (2019). New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders. Nature Human Behaviour, 3(9), 950-961. doi:10.1038/s41562-019-0653-z Luykx, J., Pazoki, R., Lin, B., Guloksuz, S., Schijven, D., van Eijk, K., & GROUP collaborators. (2019). T168. Phenome-Wide and Genome-Wide Analyses of Quality of Life in Patients With Psychosis. In Biological Psychiatry Vol. 85 (pp. S194). Elsevier BV. doi:10.1016/j.biopsych.2019.03.491 Pazoki, R. (2019). Cardiovascular disease, ABO locus, and markers of platelet functionality. International Journal of Cardiology, 286(1 July 2019), 162-163. doi:10.1016/j.ijcard.2019.03.061 De Vries, P. S., Brown, M. R., Bentley, A. R., Sung, Y. J., Winkler, T. W., Ntalla, I., . . . Giulianini, F. (2019). Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. American Journal of Epidemiology, 188(6), 1033-1054. doi:10.1093/aje/kwz005 Robinson, O., Hyam, M. C., Karaman, I., Pinto, R. C., Fiorito, G., Gao, H., . . . Vineis, P. (2018). Determinants of accelerated metabolomic and epigenetic ageing in a UK cohort. bioRxiv, preprint. doi:10.1101/411603 Kilpeläinen, T. O., Bentley, A. R., Noordam, R., Sung, Y. J., Schwander, K., Winkler, T. W., . . . Krieger, J. E. (2019). Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nature Communications, 10(1). doi:10.1038/s41467-018-08008-w Ashar, F. N., Mitchell, R. N., Albert, C. M., Newton-Cheh, C., Brody, J. A., Müller-Nurasyid, M., . . . Sotoodehnia, N. (2018). A comprehensive evaluation of the genetic architecture of sudden cardiac arrest. European Heart Journal, 39(44), 3961-3969. doi:10.1093/eurheartj/ehy474 Evangelou, E., Warren, H. R., Mosen-Ansorena, D., Mifsud, B., Pazoki, R., Gao, H., . . . Gandin, I. (2018). Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nature Genetics, 50(10), 1412-1425. doi:10.1038/s41588-018-0205-x Davies, G., Lam, M., Harris, S. E., Trampush, J. W., Luciano, M., Hill, W. D., . . . Kleineidam, L. (2018). Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nature Communications, 9(1). doi:10.1038/s41467-018-04362-x Pazoki, R., Dehghan, A., Evangelou, E., Warren, H., Gao, H., Caulfield, M., . . . Tzoulaki, I. (2018). Genetic predisposition to high blood pressure and lifestyle factors: Associations with midlife blood pressure levels and cardiovascular events. In Circulation Vol. 137 (pp. 653-661). doi:10.1161/CIRCULATIONAHA.117.030898 Pazoki, R. (2018). Methods for polygenic traits. International journal of cardiology, 1793, 145-156. doi:10.1007/978-1-4939-7868-7_10 Dr. Raha Pazoki's research is centered around health data science, with a strong emphasis on cardiometabolic diseases. 🔬 Key Research Themes Cardiometabolic Epidemiology Investigating the genetic and environmental determinants of cardiovascular and metabolic disorders. Studying conditions like hypertension, diabetes, liver dysfunction, and lipid metabolism. Genomics and Precision Medicine Utilizing large-scale genomic data (e.g., UK Biobank) to identify genetic loci associated with disease. She was the first to identify 517 novel genetic loci linked to liver enzymes and demonstrated their causal role in cardiovascular disease. Causal Inference in Epidemiology Applying Mendelian randomization and other causal inference techniques to understand the relationships between biomarkers, lifestyle factors, and disease outcomes. Lifestyle, Nutrition, and Biomarkers Exploring how diet, alcohol consumption, and other lifestyle factors interact with genetic predispositions to influence health. Artificial Intelligence in Health Prediction Leveraging AI and machine learning to predict health outcomes using large datasets. Global Health and Interventions Engaging in research that informs public health interventions and policies, especially in the context of global health disparities. Dr. Raha Pazoki is addressing several critical problems in public health and biomedical science, particularly in the context of cardiometabolic diseases. Here's a breakdown of the problems she's tackling and why they matter: 🧩 Problems She’s Solving Understanding Genetic and Environmental Risk Factors Problem: Cardiovascular and metabolic diseases (like heart disease, diabetes, and liver dysfunction) are influenced by a complex interplay of genetic and lifestyle factors. Her Work: She identifies both genetic variants and non-genetic contributors (e.g., diet, alcohol, physical activity) that increase disease risk. Causal Inference in Epidemiology Problem: Observational studies often show associations, but not causation. Her Work: She uses Mendelian randomization to determine whether certain biomarkers or behaviors cause disease, rather than just correlate with it. Improving Disease Prediction and Prevention Problem: Current risk prediction models often lack precision, especially across diverse populations. Her Work: By integrating genomic data with clinical and lifestyle information, she helps build more accurate, personalized prediction tools. Bridging the Gap Between Big Data and Clinical Practice Problem: Despite the explosion of health data, translating it into actionable insights remains a challenge. Her Work: She applies AI and machine learning to large datasets (e.g., UK Biobank) to uncover patterns that can inform public health interventions and clinical guidelines. 🌍 Why It Matters Public Health Impact: Cardiometabolic diseases are leading causes of death globally. Understanding their root causes can lead to better prevention strategies and reduced healthcare costs. Equity in Healthcare: Her work helps ensure that genetic research benefits diverse populations. Scientific Rigor: By focusing on causal relationships, her research improves the reliability of health recommendations. Policy and Practice: Her findings can inform national health policies, especially around lifestyle interventions and early screening. Dr. Raha Pazoki’s research has significant clinical and societal applications, particularly in the prevention, early detection, and personalized treatment of cardiometabolic diseases. Here's how her work translates into real-world impact: 🏥 Clinical Applications Personalized Risk Prediction By integrating genetic data with lifestyle factors, her research helps develop precision medicine tools that can predict an individual’s risk for conditions like hypertension, liver disease, and cardiovascular disease. Example: Her work on genetic liabilities and hypertension using machine learning improves how clinicians classify and manage high blood pressure. Causal Insights for Treatment Using Mendelian randomization, she identifies causal relationships between biomarkers (like liver enzymes or alcohol-related genes) and diseases. This helps clinicians target the right pathways for intervention. Improved Screening and Diagnostics Her findings on gene-diet interactions and biomarker profiles can inform screening guidelines, especially for at-risk populations, enabling earlier and more accurate diagnoses . 🌍 Societal Applications Public Health Policy Her research supports evidence-based policies on alcohol consumption, nutrition, and physical activity by showing how these factors interact with genetics to influence disease risk. Health Equity By analyzing large, diverse datasets like the UK Biobank, she contributes to more inclusive health research, ensuring that findings are applicable across different ethnic and socioeconomic groups. AI in Healthcare Her use of artificial intelligence to analyze complex health data helps automate and scale health risk assessments, making them more accessible in both high- and low-resource settings . Education and Capacity Building As a senior lecturer and research leader, she trains the next generation of scientists in data-driven, ethical, and impactful health research. Dr. Raha Pazoki’s research is already showing real-world outcomes and holds strong near-future potential in both clinical and public health domains. ✅ Real-World Outcomes Stroke Risk Prediction Using Genetics and AI In a recent study, Dr. Pazoki and her team demonstrated that incorporating genetic liability scores into machine learning models significantly improves the prediction of stroke risk. This model, using UK Biobank data, showed that individuals with higher genetic risk had a 14% increased risk of stroke. The best-performing model achieved an AUC of 69.5, indicating strong predictive power. Discovery of Genetic Loci for Liver Enzymes She was the first to identify 517 novel genetic loci associated with liver enzymes, and showed their causal role in cardiovascular disease .This discovery is already influencing how researchers and clinicians understand liver function as a predictive biomarker for heart disease. Alcohol-Related Genetic Insights Her work on the WDPCP gene revealed its role in alcohol metabolism and its link to liver cirrhosis and lipid disorders, which could inform personalized lifestyle recommendations and early intervention. 🔮 Near-Future Potential Precision Medicine Tools Her research is paving the way for genetically-informed clinical decision-making, where a patient’s genetic profile could guide personalized prevention and treatment plans for cardiometabolic diseases. AI-Driven Health Risk Platforms By combining AI with genomics, her models could be integrated into clinical software to help GPs and specialists identify high-risk patients earlier, especially for stroke, liver disease, and hypertension. Public Health Interventions Her findings on the interaction between lifestyle and genetic risk can inform targeted public health campaigns, especially in populations with high genetic susceptibility to certain diseases. Global Health Equity Her use of large, diverse datasets ensures that these tools and insights are applicable across ethnicities, helping reduce health disparities in genomic medicine. Dr. Raha Pazoki’s work significantly advances our understanding of health, ageing, and wellbeing, particularly through the lens of genomics, lifestyle, and precision medicine. Here's how her research contributes to these areas: 🧠 Improving Understanding Genetic and Lifestyle Interactions Her studies reveal how genetic predispositions interact with lifestyle factors like physical activity, diet, and alcohol consumption to influence ageing-related conditions such as hypertension, liver dysfunction, and cardiovascular disease . Causal Pathways in Ageing Diseases By applying Mendelian randomization, she identifies causal relationships between biomarkers (e.g., liver enzymes, lipid levels) and age-related diseases, helping to clarify which factors are true drivers of decline in health . 🩺 Enhancing Treatment and Prevention Precision Medicine for Ageing Populations Her work supports the development of personalized treatment strategies by integrating genetic risk scores with clinical and lifestyle data. This is especially valuable for older adults, who often have complex, multi-factorial health profiles. Early Detection of Age-Related Conditions Her research on biomarkers and genetic loci enables earlier identification of individuals at risk for diseases like stroke, liver cirrhosis, and metabolic syndrome—conditions that become more prevalent with age . Lifestyle-Based Interventions She has shown that physical activity can mitigate genetic risk for conditions like hypertension, offering actionable insights for public health and individual prevention strategies . 🌍 Promoting Wellbeing and Healthy Ageing Data-Driven Public Health Her findings inform public health campaigns that promote healthy behaviours tailored to genetic risk, supporting longer, healthier lives. Reducing Health Inequities By using large, diverse datasets, her work ensures that genomic insights are inclusive, helping to close gaps in health outcomes across different populations. AI for Ageing Research She applies machine learning to predict health outcomes in ageing populations, enabling scalable, cost-effective tools for monitoring and intervention Code and Academic Year Title Level Credits Core/Option (C/O) Module leader (Y/N) % teaching contribution BB3711-2022/3 Introduction to Epidemiology and Disease Prevention (Block leading and delivery) 6 20 O Y 95 BB3711-2023/4 Introduction to Epidemiology and Disease Prevention (Block leading and delivery) 6 20 O Y 100 BB3711-2024/5 Introduction to Epidemiology and Disease Prevention (Block leading and delivery) 6 20 O Y 100 BB3804-2023/4 Synoptic Examinations 3 (Leading and marking) 6 20 C Y 75 BB3804-2024/5 Synoptic Examinations 3 (Leading and marking) 6 20 C Y 75 BB3804-2021/22 Synoptic Examination 3 (marking, cross moderating) 6 20 C N 5 BB1719-2021/22 Introduction to Data Analysis (Leading, delivering, marking) 4 20 C Y 90 BB3091-2021/22 Final Year Project (Leading, delivering, marking) 6 40 C Y 50 BB3091-2022/23 Final Year Project (support of leading, marking, delivering, supervision) 6 40 C N 20 BB3091-2023/24 Final Year Project (marking, delivering, supervision) 6 40 C N 6 BB3091-2024/25 Final Year Project (marking, delivering, supervision) 6 40 C N 6 BB3803-2022/23 Biomedical Sciences Examinations 3 (marking, question design) 6 20 C N 20 BB3803-2023/24 Biomedical Sciences Examinations 3 (marking, question design) 6 20 C N 20 BB3803-2024/25 Biomedical Sciences Examinations 3 (marking, question design) 6 20 C N 20 BB1804-2023/24 Practical Skills 3: Molecular Analysis (marking) 4 20 C N 20 BB1804-2022/23 Practical Skills 3: Molecular Analysis (marking) 4 20 C N 20 BB2710-2021/22 Analytical Biochemistry (moderation) 5 20 C N 3 BB2709-2021/22 Genetics, Genomics and Human Health 5 20 C N 15 BB2709-2024/5 Genetics, Genomics and Human Health 5 20 C N 15 BB3801-2022/3 Scientific Communication -Essay (Coursework design & delivery, marking) 6 20 C N 20 BB3801-2023/4 Scientific Communication -Essay (Coursework design & delivery, marking) 6 20 C N 20 BB3801-2024/5 Scientific Communication -Essay (Coursework design & delivery, marking) 6 20 C N 20 BB2801-2021/22 Career Skills 5 20 C N 5 BB2555-2022/23 Placement 5 20 C N 5 BB2555-2023/24 Placement 5 20 C N 5 BB2555-2021/22 Placement 5 20 C N 5 BB1801a-2023/24 Research and Communication Skills - Presentation 4 20 C N 3 BB1801a-2024/25 Research and Communication Skills - Presentation 4 20 C N 3 BB1801c-2023/24 Research and Communication Skills - Portfolio 4 20 C N 3 BB1806-2023/24 Synoptic Examination 1 (marking) 4 20 C N 3 BB1806-2022/23 Synoptic Examination 1 (marking) 4 20 C N 3 BB2802-2021/22 Primary Literature Interrogation and Synthesis (supervision, marking) 5 20 C N 3 BB2802-2022/23 Primary Literature Interrogation and Synthesis (supervision, marking) 5 20 C N 3 BB2802-2023/24 Primary Literature Interrogation and Synthesis (supervision, marking) 5 20 C N 3 BB2804-2023/24 Data Analysis, Interpretation and Presentation (poster, marking) 5 20 C N 3 BB2804-2021/22 Data Analysis, Interpretation and Presentation (poster, marking) 5 20 C N 3 BB2805-2021/22 Biomedical Sciences Examinations 2 (moderation) 5 20 C N 3 BB2805-2022/23 Biomedical Sciences Examinations 2 (moderation) 5 20 C N 3 BB2805-2023/24 Biomedical Sciences Examinations 2 (moderation) 5 20 C N 3 BB3801-2021/22 Scientific Communication – Presentation (marking) 6 20 C N 3 BB3801b (term 1)-2022/23 Scientific Communication – Presentation (marking) 6 20 C N 3 BB3801b (term 1)-2023/24 Scientific Communication – Presentation (marking) 6 20 C N 3 BB3802b (term 2)-2023/24 Problem Solving and Data Analysis – Reflection (marking) 6 20 C N 3 BB3802b (term 2)-2022/23 Problem Solving and Data Analysis – Reflection (marking) 6 20 C N 3 BB1801a-2022/23 Research and Communication Skills - Presentation 4 20 C N 3 BB1801-2021/22 Research and Communication Skills - Presentation 4 20 C N 3 PGT Modules: Code and Academic Year Title Credits Core/Option (C/O) Module leader (Y/N) % teaching Contribution (excluding PGT dissertation supervision) BB5716-2024/2025 Vaccines and Treatment for Infection and Inflammation 7 20 N 10 BB5716-2023/2024 Vaccines and Treatment for Infection and Inflammation 7 20 N 10 BB5713-2022/2023 Radiation, Toxicology and Pollution 7 20 N 10 BB5713-2021/2022 Radiation, Toxicology and Pollution 7 20 N 10 BB5804-2024/25 Scientific Communication 7 20 N 10 BB5804-2021/22 Scientific Communication 7 20 N 10 PGT Dissertation Supervision: Code and Academic Year Title Number Primary supervisions Number of Secondary supervisions 2024/25-BB5604 Mendelian Randomisation study of lipid levels on alcohol consumption using MR-Base 1 0 2022/23-BB5604 Genetic Risk score of Alcohol Consumption and Risk of Type 2 Diabetes 1 0