[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100639408":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":12,"locations":18,"responsibleParty":31,"collaborators":10,"id":33,"slug":34,"hasResults":35,"nctId":36,"briefTitle":37,"officialTitle":38,"acronym":39,"eligibilityCriteria":40,"healthyVolunteers":41,"sex":42,"minAge":43,"maxAge":10,"enrollmentInfo":44,"targetDuration":47,"studyType":48,"phases":10,"briefSummary":49,"conditions":50,"keywords":53,"overallStatus":20,"whyStopped":10,"lastUpdateSubmitDate":62,"lastUpdatePostDateStruct":63,"startDateStruct":66,"completionDateStruct":68,"leadSponsor":70,"locationsCount":71},{"fullName":5,"class":6},"Pirogov Russian National Research Medical University","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"A representative Russian adult cohort",null,"A representative Russian adult cohort aged 18+ both men and women",[13],{"name":14,"role":15,"phone":16,"phoneExt":10,"email":17},"Liubov Machekhina, MD, PhD","CONTACT","+79037488543","machehina_lv@rgnkc.ru",[19],{"facility":5,"status":20,"city":21,"state":10,"zip":22,"country":23,"countryCode":24,"cosmosGeoPoint":25,"geoPoint":30,"contacts":10},"RECRUITING","Moscow","129226","Russia","RU",{"type":26,"coordinates":27},"Point",[28,29],37.61781,55.75204,{"lat":29,"lon":28},{"type":32,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100639408","russ-age-creating-of-a-biological-age-calculator-and-study-of-aging-phenotypes-in-the-russian-population-100639408",false,"NCT07574359","RUSS-AGE: Creating of a Biological Age Calculator and Study of Aging Phenotypes in the Russian Population","RUSS-AGE, CREATING OF A BIOLOGICAL AGE CALCULATOR AND STUDY OF AGING PHENOTYPES IN THE RUSSIAN POPULATION","RUSS-AGE","Inclusion Criteria: Signing the informed consent form to participate in the study.\n\nParticipant's age was 18 years or older at the time of inclusion in the study.\n\n\\-\n\nExclusion Criteria:\n\n1. Refusal to participate in the study or to provide informed consent.\n2. History or medical records indicating the presence of infectious diseases (Hepatitis C, Hepatitis B, including HBsAg carrier status, HIV infection).\n3. Presence of an acute illness\u002Fcondition, exacerbation of a chronic disease, or surgical intervention within the last month prior to study inclusion.\n4. Lack of remission from an oncological disease or ongoing anti-tumor therapy initiated less than three years prior to study inclusion.\n5. Severe cognitive or sensory impairments and mental disorders that, in the investigator's opinion, preclude adequate communication with the subject.\n6. Severe forms of chronic non-communicable diseases: life-threatening cardiac arrhythmias, chronic heart failure NYHA Class III-IV, left ventricular ejection fraction \\\u003C40%, ischemic heart disease CCS Class III-IV, chronic kidney disease Stages 4-5, type 1 diabetes mellitus, type 2 diabetes mellitus with terminal stages of complications, systemic connective tissue diseases, chronic obstructive pulmonary disease with respiratory failure of Grade 1 or higher, bronchial asthma requiring glucocorticosteroid therapy, osteoarthritis Kellgren-Lawrence Grade IV, body mass index (BMI) ≥40 kg\u002Fm², as well as documented history of myocardial infarction (MI) or acute cerebrovascular accident (stroke).\n7. Pregnancy or lactation (breastfeeding).\n8. Any other factors that, in the investigator's opinion, may preclude the participant's inclusion in the study.\n\n   Additional exclusion criteria for participants undergoing stool sample collection:\n9. Use of systemic antibiotics for 3 or more days within the 3 months prior to the study start.\n10. Any invasive procedures on the large intestine within the last 3 weeks prior to the study start.",true,"ALL","18 Years",{"count":45,"type":46},3500,"ESTIMATED","2 Years","OBSERVATIONAL","This is a multi-center, cross-sectional, observational study aimed at developing biological age calculators specifically for the Russian population investigating various aging phenotypes.\n\nAging is a complex process that varies greatly between individuals, meaning that chronological age does not always reflect one's biological health status. The primary goal of this study is to identify and analyze a comprehensive set of markers (including socioeconomic factors, lifestyle, physical parameters, cognitive function, and laboratory biomarkers) that best reflect the aging process. Using this data, researchers will create a mathematical model to estimate a person's \"biological age.\"\n\nThe study plans to enroll at least 3,500 male and female volunteers aged 18 years and older from across Russia. Participants will be divided into 5-year age groups (e.g., 18-24, 25-29, up to 90+ years) to ensure broad representation.\n\nParticipation involves a single visit to a clinical center. During this visit, participants will undergo:\n\nInterview and questionnaires (assessing health history, lifestyle, socioeconomic status, diet, sleep, and quality of life).\n\nPhysical examination and anthropometric measurements (height, weight, blood pressure, grip strength).\n\nFunctional and cognitive tests (e.g., walking speed, balance tests, memory and attention tasks tailored to age).\n\nCollection of biomaterials: blood (50 ml), urine, and stool samples for extensive laboratory analysis, including routine tests and specialized aging biomarkers. Part of the biomaterials will be biobanked for future scientific research.\n\nInstrumental examinations for a subset of participants: Depending on the center's capabilities and the study protocol, some participants may also undergo additional assessments such as densitometry (bone density scan), bioimpedance analysis (body composition), and brain MRI.\n\nThe results are expected to lead to the creation of a validated biological age calculator for the Russian population. This tool could help identify targets for interventions to promote healthy aging and, in the future, potentially predict the risk of developing age-related chronic diseases.",[51,52],"Healthy Aging","Biomarkers",[54,55,56,57,58,59,60,61],"biological age","aging biomarkers","aging clock","biological age calculator","phenotypic age","aging phenotype","healthy aging","machine learning in aging","2026-05-04",{"date":64,"type":65},"2026-05-07","ACTUAL",{"date":67,"type":65},"2023-01-12",{"date":69,"type":46},"2030-09",{"name":5,"class":6},1]