The SOMAscan-based proteomic measurements of 1301 plasma proteins in a population of 240 healthy men and women (22-93 years old) identified growth differentiation factor 15 (GDF15) as the strongest biomarker positively associated with age. The proteomic age predictor was developed based on relative concentrations of 76 proteins that highly correlated with chronological age using elastic net regression models (Table S1, Supporting Information). Continually improving technologies should lead to better age predictors as more proteins become identifiable. The newest study on 2925 plasma proteins from 4263 young adults to nonagenarians (18-95 years old) revealed specific waves of changes in the proteome in the fourth, seventh, and eighth decades of life, and identified a highly accurate plasma proteomic clock consisting of 373 proteins (Table S1, Supporting Information). Besides the blood proteome, other clinical samples can be analyzed. The first broad application of SOMAscan technology to CSF from 90 cognitively healthy donors of different ages revealed 82 age-associated proteins. Most of them were novel biomarkers of aging that are prominently associated with immune system activation or response to injury. Despite the fact that the subjects included in this study were judged to be cognitively normal, the probability remains that some elderly patients could have had undetected, preclinical neurodegenerative disease, suggesting that some of the identified age-correlated biomarkers are instead disease-correlated biomarkers.data using algorithms, which can be used as indicators of normal or pathological biological processes or responses to therapeutic interventions.[141] Examples of digital biomarkers include heart rate variability, sleep duration and quality, physical activity, and social behavior, which can be monitored using wearable devices such as smartwatches or smartphone applications.[142] Digital biomarkers have the potential to provide continuous and objective measurements of health-related parameters, enabling early detection and intervention of age-related diseases. Moreover, they can be used to monitor the efficacy of interventions in real-time and to personalize treatment regimens based on individual needs and responses.[143] However, the validity and reliability of digital biomarkers are still being evaluated, and their integration into clinical practice requires further standardization and validation.[144] Overall, digital biomarkers represent a promising approach for improving the management of age-related diseases and promoting healthy aging.number of corrections to the text:

Data using the device's software and hardware. Depending on the method of signal detection, sensors can be classified into two main groups: physical and biochemical. Physical sensors can measure a number of clinically relevant physiological characteristics, including the temperature of human skin (by digital thermometer), blood pressure (by digital sphygmomanometer), body motion (by gyroscope, accelerometer, and magnetometer), heart rhythms (by wearable electrocardiograph), heart rate (by photoplethysmography device), and blood oxygen levels (by noninvasive pulse oximeter). These measurements complement and can even replace traditional physiological tests. [141]

Biochemical sensors require body fluids for analysis and can be noninvasive in the case of collecting secreted fluids (saliva, tears, sweat, skin interstitial fluids, urine, or stools), or invasive (blood, biopsies), when sampling is performed by penetrating the body through injection or incision. [142] Biochemical sensors provide measurements of pH, blood oxygen saturation, protein concentration, amino acids, lipids, electrolytes and metabolites, hormones, and pathogenic bacteria. The incorporation of automated dosing systems allows not only monitoring biomarker concentration in the body but also automatically controlled drug release, such as in the artificial pancreas device system where a glucose sensor placed under the skin is linked to an insulin infusion pump. [143]

Substantial progress in omics approaches provides an opportunity for more multilayer assessment of aging in humans. [90] Omics-based biomarkers can be equally applicable throughout the human lifespan at all levels of biological organization from single-cell profiling to systemic phenotyping (Figure 2). The advantage of omics approaches over systemic biomarkers is that they help to reveal underlying degenerative processes at the earliest stages when no strong correlation between single molecular biomarkers and associated degenerative processes exists.

Wearable devices with wireless modules are particularly valuable in remote patient monitoring, allowing real-time consultation and immediate medical interventions in life-threatening conditions. They offer advantages over standard functional tests in the clinical setting as they generate continuous data, providing a determination of an individual's behavior in normal settings and longitudinally.