100-Year Human Aging Study
100-Year Human Aging Study: Prospective Longitudinal Validation of Multi-System Health Measurements Against Mortality and Aging Outcomes
調査の概要
状態
条件
詳細な説明
All currently existing longevity measures are surrogate endpoints that have not been prospectively validated against actual mortality and aging outcomes. The 100-Year Human Aging Study is a prospective, pragmatic, observational trial that addresses this gap by enrolling participants in comprehensive clinical screening and following them longitudinally until death to determine which measurements - alone and in combination - are predictive of mortality, serious disease, and functional disability.
The study prioritizes dynamic measurements: the physiological, cognitive, social, and environmental capacities that change with aging and are most likely to carry predictive signal for mortality and functional outcomes. These include cardiorespiratory fitness (cardiopulmonary exercise testing with ventilatory threshold analysis), strength (grip, explosive power, functional movement), mobility and balance, neurocognitive performance, sensory function (vision, hearing, smell, light touch), and metabolic function (oral glucose tolerance, continuous glucose monitoring), in addition to other testing. Structural and imaging assessments include body composition and bone mineral density by DEXA, echocardiography, resting and stress electrocardiography, spirometry, retinal fundus photography, and vascular ultrasound. Laboratory measures are drawn on-site and processed through a CLIA-certified reference laboratory. Complete medical, surgical, family, social, occupational, and environmental histories are obtained at each visit.
Participation ranges from single-service visits - including standalone DEXA, cardiopulmonary exercise testing, laboratory panel testing, and sleep studies - to the full two-visit comprehensive screening battery. All participation pathways contribute clinical data to the longitudinal mortality and aging outcomes linkage framework regardless of service level. Participants are encouraged to return for repeat testing to build longitudinal health trajectories across the lifespan.
At enrollment and across longitudinal follow-up, the study platform generates individualized investigational constructs including biological age estimate, predicted death age, and predicted cause of death profile. These are explicitly investigational hypotheses, not validated clinical standards. Their predictive validity relative to actual mortality, aging outcomes, and functional disability is a central scientific question this study is designed to answer, both for individual measures and for composite multi-system models.
All data are archived in their highest-dimensional raw form to preserve the ability to apply future analytical methods retroactively. Participants are followed with periodic contact and offered repeat screening throughout the lifespan. Longitudinal outcomes ascertainment includes all-cause mortality, cause-specific mortality, incident serious health events, chronic disease diagnosis, functional independence, disability status, and health behavior change.
Study sites and participation pathways. The 100-Year Human Aging Study is conducted across all Longevity Metrics participation pathways, current and future: the Boulder Human Performance Lab (fixed flagship laboratory); mobile screening units including the Health Ahead Bus; any additional fixed or mobile Longevity Metrics laboratory established during the study period; and an online participation pathway through which participants enroll and contribute structured data without in-person screening. All pathways operate under a single protocol with identical procedures, data management, informed consent, and safety standards.
This study is one of four that compound into one system. The Human Observatory Study (NCT07646782) validates sociodemographic and environmental data against the same outcomes, and receives each model's geographic residuals. The Health Ahead Comparative Effectiveness Study (NCT07669168) moves the screening toward increasing automation and mobility while maintaining quality. The Longevity Metrics AI/ML Development Study (NCT pending approval) builds the models that make automation, prediction, and broad utilization possible. This study supplies the clinical data and validates what it means for health, disease, disability, and death.
研究の種類
入学 (推定)
連絡先と場所
研究連絡先
- 名前：William E Brandenburg, MD
- 電話番号：3035010016
- メール：info@longevitymetrics.org
研究場所
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Colorado
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Boulder、Colorado、アメリカ、80301
- 募集
- Longevity Metrics
-
コンタクト：
- William E Brandenburg, MD
- 電話番号：3035010016
- メール：info@longevitymetrics.org
-
-
参加基準
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
サンプリング方法
調査対象母集団
説明
Inclusion Criteria:
- Age 18 years or older
- Willing and able to provide written informed consent, or enrollment with consent of a legally authorized representative
- Willing to participate in longitudinal follow-up
Exclusion Criteria:
- Age under 18 years
研究計画
研究はどのように設計されていますか？
デザインの詳細
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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All-Cause Mortality
時間枠：From enrollment until death, assessed periodically, up to 100 years
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Vital status ascertained through longitudinal follow-up contact, mortality record linkage, and health data network linkage using probabilistic matching on name, date of birth, and address history.
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From enrollment until death, assessed periodically, up to 100 years
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Cause-Specific Mortality
時間枠：From enrollment until death, assessed periodically, up to 100 years
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Cause of death ascertained via death certificate and mortality record linkage.
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From enrollment until death, assessed periodically, up to 100 years
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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Cause-Specific Mortality Prediction Accuracy
時間枠：From enrollment until death, assessed periodically, up to 100 years
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Concordance between predicted cause of death profile generated at enrollment and actual cause of death ascertained at follow-up.
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From enrollment until death, assessed periodically, up to 100 years
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Incident Serious Adverse Health Events
時間枠：Periodically from enrollment until death, up to 100 years
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New diagnosis of myocardial infarction, stroke, cancer, dementia, heart failure, atrial fibrillation, sepsis, venous thromboembolism, COPD, chronic hypoxia, or major fracture ascertained via periodic follow-up contact and health data network linkage.
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Periodically from enrollment until death, up to 100 years
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Incident Chronic Disease
時間枠：Periodically from enrollment until death, up to 100 years
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New diagnosis of type 2 diabetes, hypertension, COPD, chronic kidney disease, metabolic syndrome, or osteoporosis ascertained via self-report and health data network linkage.
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Periodically from enrollment until death, up to 100 years
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Functional Independence and Disability Status
時間枠：Periodically from enrollment until death, up to 100 years
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Activities of daily living, instrumental activities of daily living, and self-reported disability status ascertained via periodic health survey using validated open-source instruments.
Higher composite scores indicate greater functional independence.
Specific instruments will be selected prior to first follow-up contact and documented in the statistical analysis plan.
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Periodically from enrollment until death, up to 100 years
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Biological Age Estimate Prediction Accuracy
時間枠：Periodically from enrollment until death, up to 100 years
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Concordance between investigational biological age estimate and actual mortality outcomes at longitudinal follow-up.
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Periodically from enrollment until death, up to 100 years
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Health Behavior Change: Composite Self-Report and Repeat Screening Index
時間枠：Periodically from enrollment until death, up to 100 years
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Health behavior change assessed through two complementary measures aggregated into a single index: validated composite self-report survey administered at periodic follow-up, and change in pre-specified clinical measurements at repeat screening.
Improvement in objective clinical measurements (cardiorespiratory fitness, body composition, metabolic biomarkers, and related parameters) serves as the primary behavioral activation signal.
Self-report domains including health behaviors and preventive care utilization provide supporting context.
Both are combined into a single participant-level health activation index.
Higher scores indicate greater engagement with health-promoting behaviors and measurable clinical improvement.
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Periodically from enrollment until death, up to 100 years
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Multi-System Predictor Modeling: Predictive Performance
時間枠：Periodically from enrollment until death, up to 100 years
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Performance of a unified multi-domain measurement framework in predicting all-cause mortality and incident serious disease.
The framework integrates clinical, biological, behavioral, social, occupational, and environmental data into a single composite model.
Performance is reported for the full composite model, with pre-specified secondary reporting for individual predictor domains and domain combinations to identify which inputs are independently predictive, which are redundant, and which combinations provide additive or synergistic predictive value.
Metrics are specified in the statistical analysis plan.
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Periodically from enrollment until death, up to 100 years
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協力者と研究者
スポンサー
捜査官
- 主任研究者：William E Brandenburg, MD、Longevity Metrics, Inc.
出版物と役立つリンク
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
キーワード
追加の関連 MeSH 用語
その他の研究ID番号
- 100Year
- IORG0012336 (その他の識別子：OHRP)
- IRB00014601 (その他の識別子：OHRP)
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
IPD プランの説明
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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