Aging is a complex trait characterized by a diverse spectrum of endophenotypes. By utilizing the SomaScan^® proteomic platform in 1,025 participants of the LonGenity cohort (age range: 65–95, 55.7% females), we found that 754 of 4,265 proteins were associated with chronological age. Pleiotrophin (PTN; β[SE] = 0.0262 [0.0012]; p = 3.21 × 10⁻⁸⁶), WNT1‐inducible‐signaling pathway protein 2 (WISP‐2; β[SE] = 0.0189 [0.0009]; p = 4.60 × 10⁻⁸²), chordin‐like protein 1 (CRDL1; β[SE] = 0.0203[0.0010]; p = 1.45 × 10⁻⁷⁷), transgelin (TAGL; β[SE] = 0.0215 [0.0011]; p = 9.70 × 10⁻⁷¹), and R‐spondin‐1(RSPO1; β[SE] = 0.0208 [0.0011]; p = 1.09 × 10⁻⁷⁰), were the proteins most significantly associated with age. Weighted gene co‐expression network analysis identified two of nine modules (clusters of highly correlated proteins) to be significantly associated with chronological age and demonstrated that the biology of aging overlapped with complex age‐associated diseases and other age‐related traits. The correlation between proteomic age prediction based on elastic net regression and chronological age was 0.8 (p < 2.2E−16). Pathway analysis showed that inflammatory response, organismal injury and abnormalities, cell and organismal survival, and death pathways were associated with aging. The present study made novel associations between a number of proteins and aging, constructed a proteomic age model that predicted mortality, and suggested possible proteomic signatures possessed by a cohort enriched for familial exceptional longevity.

Frailty is a state of decreased physiological reserve and increased vulnerability to adverse outcomes in aging, and is characterized by dysregulation across various biological pathways. Frailty may manifest biologically as alteration in protein expression, possibly regulated at genetic, transcriptional and epigenetic levels. In this study, we examined the proteomic profile associated with frailty defined by an established cumulative frailty index (FI). Using the SomaScan^® assay, 4265 proteins were measured in plasma, of which 55 were positively associated and 88 were negatively associated with the FI. The proteins most strongly associated with frailty were fatty acid‐binding proteins, including fatty acid‐binding protein (FABP) (p = 1.96 × 10⁻¹⁹) and FABPA (p = 8.10 × 10⁻¹⁶), leptin (p = 1.43 × 10⁻¹⁴), and ANTR2 (p = 7.95 × 10⁻²⁰). Pathway analysis with the top 143 frailty‐associated proteins revealed enrichment for proteins in pathways related to lipid metabolism, musculoskeletal development and function, cell‐to‐cell signaling and interaction, cellular assembly, and organization. Frailty prediction model constructed with elastic net regression utilizing 110 proteins demonstrated a correlation between predicted frailty and observed frailty (r = 0.57, p < 2.2 × 10⁻¹⁶). Predicted frailty was also more strongly correlated with chronological age (r = 0.54, p < 2.2 × 10⁻¹⁶) than observed frailty (r = 0.37, p = 1.2 × 10⁻¹⁵). This study identified novel proteins and pathways related to frailty that may offer improved frailty phenotyping and prediction.

Background: The southern India state of Kerala has among the highest proportion of older adults in its population in the country. An increase in chronic age-related diseases such as dementia is expected in the older Kerala population. Identifying older individuals early in the course of cognitive decline offers the best hope of introducing preventive measures early and planning management. However, the epidemiology and pathogenesis of predementia syndromes at the early stages of cognitive decline in older adults are not well established in India. Objective: The Kerala Einstein Study (KES) is a community-based cohort study that was established in 2008 and is based in the Kozhikode district in Kerala state. KES aims to establish risk factors and brain substrates of motoric cognitive risk syndrome (MCR), a predementia syndrome characterized by the presence of slow gait and subjective cognitive concerns in individuals without dementia or disability. This protocol describes the study design and procedures for this KES project. Methods: KES is proposing to enroll a sample of 1000 adults ≥60 years old from urban and rural areas in the Kozhikode district of Kerala state: 200 recruited in the previous phase of KES and 800 new participants to be recruited in this project. MCR is the cognitive phenotype of primary interest. The associations between previously established risk factors for dementia as well as novel risk factors (apathy and traumatic brain injury) and MCR will be examined in KES. Risk factor profiles for MCR will be compared between urban and rural residents as well as with individuals who meet the criteria for mild cognitive impairment (MCI). Cognitive and physical function, medical history and medications, sociodemographic characteristics, lifestyle patterns, and activities of daily living will be evaluated. Participants will also undergo magnetic resonance imaging and electrocardiogram investigations. Longitudinal follow-up is planned in a subset of participants as a prelude to future longitudinal studies. Results: KES (2R01AG039330-07) was funded by the US National Institutes of Health in September 2019 and received approval from the Indian Medical Council of Research to start the study in June 2021. We had recruited 433 new participants from urban and rural sites in Kozhikode as of May 2023: 41.1% (178/433) women, 67.7% (293/433) rural residents, and 13.4% (58/433) MCR cases. Enrollment is actively ongoing at all the KES recruitment sites. Conclusions: KES will provide new insights into risk factors and brain substrates associated with MCR in India and will help guide future development of regionally specific preventive interventions for dementia. International Registered Report Identifier (IRRID): DERR1-10.2196/49933

Objective: This study examines the plasma proteomic profile of abdominal obesity in older adults.Methods: The association of abdominal obesity (waist circumference [WC]) with 4265 plasma proteins identified using the SomaScan Assay was examined in 969 Ashkenazi Jewish participants (LonGenity cohort), aged 65 years and older (mean [SD] age 75.7 [6.7] years, 55.4% women), using regression models. Pathway analysis, as well as weighted correlation network analysis, was performed. WC was determined from the proteome using elastic net regression.Results: A total of 480 out of 4265 proteins were associated with WC in the linear regression model. Leptin (β [SE] = 12.363 [0.490]), inhibin β C chain (INHBC; β [SE] = 24.324 [1.448]), insulin‐like growth factor‐binding protein 2 (IGFBP‐2; β [SE] = −12.782 [0.841]), heparan‐sulfate 6‐O‐sulfotransferase 3 (H6ST3; β [SE] = −39.995 [2.729]), and matrix‐remodeling‐associated protein 8 (MXRA8; β [SE] = −27.101 [1.850]) were the top proteins associated with WC. Cell adhesion, extracellular matrix remodeling, and IGF transport pathways were the top enriched pathways associated with WC. WC signature determined from plasma proteins was highly correlated with measured WC (r = 0.80) and was associated with various metabolic and physical traits.Conclusions: The study unveiled a multifaceted plasma proteomic profile of abdominal obesity in older adults, offering insights into its wide‐ranging impact on the proteome. It also elucidated novel proteins, clusters of correlated proteins, and pathways that are intricately associated with abdominal obesity.

Frailty is an age‐related syndrome characterized by an increased vulnerability to adverse health outcomes in the face of stressors. By deriving a blood‐based proteomic signature for frailty, the current study aimed to enhance the understanding of frailty biology and created a person‐specific predictor for the risk of frailty and other adverse age‐related health outcomes. A 25‐protein signature (proteomic frailty index [pFI]) predictive of the cumulative frailty index (FI) in the LonGenity cohort was derived using a penalized regression method. The pFI was significantly correlated with the FI at baseline (Pearson r = 0.58) and showed significant associations with age‐related chronic conditions, incident mortality, and clinical measures. In an independent cohort of 5195 participants in the Atherosclerosis Risk in Communities study, pFI was successfully validated with measured FI ( r = 0.61, p < 0.001) and was associated with physical frailty at baseline ( p < 0.001). The pFI was significantly associated with physical, clinical, and cognitive measures, as well as incident mortality (HR [95% CI] = 1.13 [1.12–1.14]) and dementia (HR [95% CI] = 1.07 [1.05–1.09]) after accounting for demographic factors. The pFI was further validated against FI ( r = 0.45, p < 0.001) in a second independent study in 654 participants from the Baltimore Longitudinal Study of Aging. In conclusion, we identified and validated a 25‐protein signature as an index of frailty that also captures overall well‐being, health, and risk for key age‐related diseases.

Background: Although gait speed typically declines with age, some individuals manage to maintain higher walking speeds well into older age. To better understand healthy longevity, we propose a novel exceptional aging phenotype of super movers, individuals 80 years or older with walking speeds comparable to individuals 3 decades younger. Methods: We conducted a retrospective cohort study to examine the epidemiology and determinants of super mover status as well as mortality, biological aging and gait speed trajectories of super movers compared to age peers identified from 15 aging cohort studies across 24 countries. Results: In a pooled cohort of data from multicountry population-based surveys, prevalence of super movers ranged from 4.9% to 11.1% in individuals 80 and older, with an average overall prevalence of 7.3%. Compared to age peers, super movers exhibited lower disease prevalence, healthier lifestyles and had lower mortality rates (hazard ratios: 0.38, 95% CI: 0.09–0.66). In 2 smaller samples with gait and biological aging data and longitudinal gait assessments, compared to age-matched peers, super movers had younger biological age and showed faster gait speed from their seventh to tenth decades, respectively. Conclusions: Super movers are an exceptional aging phenotype enriched with unique biological and clinical profiles that can provide valuable insights into healthy longevity.