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 ), WNT1-inducible-signaling pathway protein 2 (WISP-2; β[SE] = 0.0189 [0.0009]; p = 4.60 × 10 ), chordin-like protein 1 (CRDL1; β[SE] = 0.0203[0.0010]; p = 1.45 × 10 ), transgelin (TAGL; β[SE] = 0.0215 [0.0011]; p = 9.70 × 10 ), and R-spondin-1(RSPO1; β[SE] = 0.0208 [0.0011]; p = 1.09 × 10 ), 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.