Biological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood-DNA-methylation measure that is sensitive to variation in pace of biological aging among individuals born the same year. We first modeled change-over-time in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in n = 954 members of the Dunedin Study born in 1972–1973. Rates of change in each biomarker over ages 26–38 years were composited to form a measure of aging-related decline, termed Pace-of-Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace-of-Aging, called DunedinPoAm for Dunedin(P)ace(o)f(A)ging(m)ethylation. Validation analysis in cohort studies and the CALERIE trial provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person’s pace of biological aging.

IMPORTANCE Mental health professionals typically encounter patients at 1 point in patients' lives.This cross-sectional window understandably fosters focus on the current presenting diagnosis.Research programs, treatment protocols, specialist clinics, and specialist journals are oriented to presenting diagnoses, on the assumption that diagnosis informs about causes and prognosis. This study tests an alternative hypothesis: people with mental disorders experience many different kinds of disorders across diagnostic families, when followed for 4 decades. OBJECTIVETo describe mental disorder life histories across the first half of the life course. DESIGN, SETTING, AND PARTICIPANTS This cohort study involved participants born in New Zealand from 1972 to 1973 who were enrolled in the population-representative Dunedin Study. Participants were observed from birth to age 45 years (until April 2019). Data were analyzed from May 2019 to January 2020. MAIN OUTCOMES AND MEASURES Diagnosed impairing disorders were assessed 9 times from ages 11 to 45 years. Brain function was assessed through neurocognitive examinations conducted at age 3 years, neuropsychological testing during childhood and adulthood, and midlife neuroimaging-based brain age. RESULTSOf 1037 original participants (535 male [51.6%]), 1013 had mental health data available.The proportions of participants meeting the criteria for a mental disorder were as follows: 35% (346 of 975) at ages 11 to 15 years, 50% (473 of 941) at age 18 years, 51% (489 of 961) at age 21 years, 48% (472 of 977) at age 26 years, 46% (444 of 969) at age 32 years, 45% (429 of 955) at age 38 years, and 44% (407 of 927) at age 45 years. The onset of the disorder occurred by adolescence for 59% of participants (600 of 1013), eventually affecting 86% of the cohort (869 of 1013) by midlife. By age 45 years, 85% of participants (737 of 869) with a disorder had accumulated comorbid diagnoses.

DM2 is present in a large number of families of northern European ancestry. Clinically, DM2 resembles adult-onset DM1, with myotonia, muscular dystrophy, cataracts, diabetes, testicular failure, hypogammaglobulinemia, and cardiac conduction defects. An important distinction is the lack of a congenital form of DM2. The clinical and molecular parallels between DM1 and DM2 indicate that the multisystemic features common to both diseases are caused by CUG or CCUG expansions expressed at the RNA level.

ABSTRACTBiological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed to serve as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood DNA-methylation measure that is sensitive to variation in the pace of biological aging among individuals born the same year. We first modeled longitudinal change in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in the Dunedin birth cohort. Rates of change in each biomarker were composited to form a measure of aging-related decline, termed Pace of Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace of Aging, called DunedinPoAm for Dunedin (P)ace (o)f (A)ging (m)ethylation. Validation analyses showed DunedinPoAm was associated with functional decline in the Dunedin Study and more advanced biological age in the Understanding Society Study, predicted chronic disease and mortality in the Normative Aging Study, was accelerated by early-life adversity in the E-risk Study, and DunedinPoAm prediction was disrupted by caloric restriction in the CALERIE trial. DunedinPoAm generally outperformed epigenetic clocks. Findings provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person’s pace of biological aging.

SUMMARY DNA methylation plays an important role in both normal human development and risk of disease. The most utilized method of assessing DNA methylation uses BeadChips, generating an epigenome-wide “snapshot” of >450,000 observations (probe measurements) per assay. However, the reliability of each of these measurements is not equal, and little consideration is paid to consequences for research. We correlated repeat measurements of the same DNA samples using the Illumina HumanMethylation450K and the Infinium MethylationEPIC BeadChips in 350 blood DNA samples. Probes that were reliably measured were more heritable and showed consistent associations with environmental exposures, gene expression, and greater cross-tissue concordance. Unreliable probes were less replicable and generated an unknown volume of false negatives. This serves as a lesson for working with DNA methylation data, but the lessons are equally applicable to working with other data: as we advance toward generating increasingly greater volumes of data, failure to document reliability risks harming reproducibility.

ObjectiveSoluble urokinase plasminogen activator receptor (suPAR) is an inflammatory biomarker associated with presence and progression of disease and with increased risk of mortality. We aimed to evaluate the unspecific biomarker suPAR as a prognostic marker in patients admitted to acute care.MethodsThis registry-based retrospective cohort study included 4343 consecutively admitted patients from the Acute Medical Unit at a large Danish university hospital. Time to readmission and death were analysed by multiple Cox regression. Results were reported as HRs for 30-day and 90-day follow-up.ResultsDuring 30-day follow-up, 782 patients (18.0%) were readmitted and 224 patients (5.2%) died. Comparing 30-day readmission and mortality between patients in the highest and lowest suPAR quartiles yielded HRs of 2.11 (95% CI 1.70 to 2.62) and 4.11 (95% CI 2.46 to 6.85), respectively, when adjusting for age, sex, Charlson score and C reactive protein. Area under the curve for receiver operating characteristics curve analysis of suPAR for 30-day mortality was 0.84 (95% CI 0.81 to 0.86). Furthermore, in the entire cohort, women had slightly higher suPAR compared with men, and suPAR was associated with age, admission time, admission to intensive care unit and Charlson score.ConclusionsIn this large unselected population of acute medical patients, suPAR is strongly associated with disease severity, readmission and mortality after adjusting for all other risk factors, indicating that suPAR adds information to established prognostic indicators. While patients with low suPAR levels have low risk of readmission and mortality, patients with high suPAR levels have a high risk of adverse events.

IMPORTANCE Gait speed is a well-known indicator of risk of functional decline and mortality in older adults, but little is known about the factors associated with gait speed earlier in life. OBJECTIVES To test the hypothesis that slow gait speed reflects accelerated biological aging at midlife, as well as poor neurocognitive functioning in childhood and cognitive decline from childhood to midlife. DESIGN, SETTING, AND PARTICIPANTS This cohort study uses data from the Dunedin Multidisciplinary Health and Development Study, a population-based study of a representative 1972 to 1973 birth cohort in New Zealand that observed participants to age 45 years (until April 2019). Data analysis was performed from April to June 2019. EXPOSURES Childhood neurocognitive functions and accelerated aging, brain structure, and concurrent physical and cognitive functions in adulthood. MAIN OUTCOMES AND MEASURES Gait speed at age 45 years, measured under 3 walking conditions: usual, dual task, and maximum gait speeds. RESULTS Of the 1037 original participants (91% of eligible births; 535 [51.6%] male), 997 were alive at age 45 years, of whom 904 (90.7%) had gait speed measured (455 [50.3%] male; 93% white). The mean (SD) gait speeds were 1.30 (0.17) m/s for usual gait, 1.16 (0.23) m/s for dual task gait, and 1.99 (0.29) m/s for maximum gait. Adults with more physical limitations (standardized regression

Systemic chronic inflammation (SCI) is persistent, health-damaging, low-grade inflammation that plays a major role in immunosenescence and in development and progression of many diseases. But currently, there are no recognized standard biomarkers to assess SCI levels alone, and SCI is typically measured by combining biomarkers of acute inflammation and infection, e.g., CRP, IL-6, and TNFα. In this review, we highlight 10 properties and characteristics that are shared by the blood protein soluble urokinase plasminogen activator receptor (suPAR) and SCI, supporting the argument that suPAR is a biomarker of SCI: (1) Expression and release of suPAR is upregulated by immune activation; (2) uPAR and suPAR exert pro-inflammatory functions; (3) suPAR is associated with the amount of circulating immune cells; (4) Blood suPAR levels correlate with the levels of established inflammatory biomarkers; (5) suPAR is minimally affected by acute changes and short-term influences, in contrast to many currently used markers of systemic inflammation; (6) Like SCI, suPAR is non-specifically associated with multiple diseases; (7) suPAR and SCI both predict morbidity and mortality; (8) suPAR and SCI share the same risk factors; (9) suPAR is associated with risk factors and outcomes of inflammation above and beyond other inflammatory biomarkers; (10) The suPAR level can be reduced by anti-inflammatory interventions and treatment of disease. Assessing SCI has the potential to inform risk for morbidity and mortality. Blood suPAR is a newer biomarker which may, in fact, be a biomarker of SCI since it is stably associated with inflammation and immune activation; shares the same risk factors as many age-related diseases; is both elevated by and predicts age-related diseases. There is strong evidence that suPAR is a prognostic marker of adverse events, morbidity, and mortality. It is associated with immune activity and prognosis across diverse conditions, including kidney disease, cardiovascular disease, cancer, diabetes, and inflammatory disorders. Thus, we think it likely represents a common underlying disease-process shared by many diseases; that is, SCI. We review the supporting literature and propose a research agenda that can help test the hypothesis that suPAR indexes SCI, with the potential of becoming the new gold standard for measuring SCI.