Game-Based Cognitive Aging Assessment: Toward a Digital Biomarker of Cognitive Health

Fine structural details of glycans attached to the conserved N-glycosylation site significantly not only affect function of individual immunoglobulin G (IgG) molecules but also mediate inflammation at the systemic level. By analyzing IgG glycosylation in 5,117 individuals from four European populations, we have revealed very complex patterns of changes in IgG glycosylation with age. Several IgG glycans (including FA2B, FA2G2, and FA2BG2) changed considerably with age and the combination of these three glycans can explain up to 58% of variance in chronological age, significantly more than other markers of biological age like telomere lengths. The remaining variance in these glycans strongly correlated with physiological parameters associated with biological age. Thus, IgG glycosylation appears to be closely linked with both chronological and biological ages. Considering the important role of IgG glycans in inflammation, and because the observed changes with age promote inflammation, changes in IgG glycosylation also seem to represent a factor contributing to aging.Significance StatementGlycosylation is the key posttranslational mechanism that regulates function of immunoglobulins, with multiple systemic repercussions to the immune system. Our study of IgG glycosylation in 5,117 individuals from four European populations has revealed very extensive and complex changes in IgG glycosylation with age. The combined index composed of only three glycans explained up to 58% of variance in age, considerably more than other biomarkers of age like telomere lengths. The remaining variance in these glycans strongly correlated with physiological parameters associated with biological age; thus, IgG glycosylation appears to be closely linked with both chronological and biological ages. The ability to measure human biological aging using molecular profiling has practical applications for diverse fields such as disease prevention and treatment, or forensics.

Background. This prospective observational study aimed to evaluate the impact of adjuvant chemotherapy on clinical and biological markers of ageing and frailty. Materials and methods. Eligible patients were females ≥70y with early invasive breast cancer for whom adjuvant chemotherapy (4 x docetaxel-cyclophosphamide +/- trastuzumab and Granulocyte-Colony Stimulating Factor) was planned (ChemoG). The control group consisted of breast cancer patients for whom adjuvant chemotherapy was not indicated (ControlG). Patients were enrolled after surgery, underwent blood sampling and received full geriatric assessment (GA) and Quality of Life, (QoL) evaluation at baseline, at 3 months (3m) and 1 year (1y). GA results were summarized in a single score, LOFS (Leuven Oncology Frailty Score), ranging from 10 (very fit) to 0 (very frail). Chemotherapy administration and toxicity were recorded. An extensive (ageing) biomarker analysis is being performed, but this abstract focuses on mean leukocyte telomere length (TL), and circulating inflammatory cytokines (IL-6, IL-10, IGF-1, TNF-alfa, MCP-1, and RANTES). The primary endpoint was to assess whether adjuvant chemotherapy induces accelerated telomere attrition at 1y. Secondary endpoints were the evolution of other ageing biomarkers, LOFS and QoL during chemotherapy; correlations between ageing biomarkers, chronological age and LOFS at inclusion; and the predictive value of ageing biomarkers for functional decline, QoL decline, and chemotherapy toxicity. Results. 57 patients were included (ChemoG), and 53 (ControlG), with mean age at diagnosis of 73,8y and 76,8y, and mean LOFS of 7,5 (SD 2,3) and 6,8 (SD 1,6). TL was similar in both groups at baseline, and decreased at 3m (p 0,05) and 1y (p 0,0009) in ChemoG, with a similar evolution in ControlG indicating no difference in evolution between both groups (test for interaction p 0,88). RANTES showed a similar decline at 1y in both groups. The other 5 markers remained stable in ControlG while significantly changing in ChemoG (significant time interaction): IL-6 decreased at 3m in the ChemoG (p 0,01) and returned to baseline values at 1y ; MCP-1 strongly decreased at 3m (p <0,0001) but increased above baseline value at 1y (p <0.0001) ; IGF-1 had a similar initial decline at 3m (p <0,0001) yet with only slight recovery at 1y (p 0,006). On the other hand, IL-10 increased at 3m (p 0,04) but decreased at 1y (p <0,0001), and TNF-alfa increased at 3m (p 0,001) and 1y (p <0,0001). LOFS declined in ChemoG at 3m (p 0,0007) but returned to baseline level at 1y (p 0,6) while remaining stable over time in ControlG. Global QoL decreased slightly at 3m in ChemoG and returned to baseline while remaining stable in ControlG. IL-6 correlated most strongly with chronological age (p 0,0008) and LOFS (p 0,03) while associations were less clear for the other biomarkers. In ChemoG, MCP-1 and RANTES were associated with functional decline (IADL ≥1 point decline at 1y) but no biomarkers were associated with QoL decline and grade II-III-IV toxicity. Conclusions. TL does not evolve differently over time in patients treated with or without chemotherapy. Chemotherapy has measurable impact on clinical frailty and other ageing biomarkers at 3 months, but these effects disappear at 1y follow-up. Citation Format: Barbara Brouwers, Sigrid Hatse, Lissandra Dal Lago, Patrick Neven, Peter Vuylsteke, Guy Debrock, Heidi Van den Bulck, Ann Smeets, Oliver Bechter, Evalien Swerts, Jithendra Kini Bailur, Cindy Kenis, Annouschka Laenen, Bruna Dalmasso, Patrick Schöffski, Graham Pawelec, Hans Wildiers. Impact of adjuvant chemotherapy on clinical and biological ageing in older breast cancer patients [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-09-01.

The small RhoGTPase Cdc42 is mechanistically linked to aging of multiple tissues and to rejuvenation of hematopoietic stem cells in mice. However, data validating Cdc42 activity and expression as biomarker for aging in humans are still missing. Here, we hypothesized that Cdc42 might serve as a novel biomarker of aging in older adults and therefore we determined Cdc42 activity and expression levels in peripheral blood cells from a cohort of 196 donors. We investigated the association of these parameters with both chronological and biological aging. We also tested in this cohort of older adults a recently published algorithm determining chronological age based on DNA methylation profiles. A positive correlation with chronological age was found for both the level of Cdc42 mRNA and the level of active Cdc42 protein (the GTP bound form). Notably, the level of Cdc42 mRNA as well as total protein showed a specific strong association to cardiovascular disease and Cdc42 mRNA levels also to a history of myocardial infarction. In summary, these data validate Cdc42 as a blood biomarker of both chronological aging as well as aging-associated diseases like cardiovascular disease and myocardial infarction.

Background: Although there have been cross-sectional and longitudinal studies examining biological age (BA) with chronological age (CA)-related changes in physical, physiological, biochemical, and hormonal variables, few studies have performed echocardiographic evaluation of the cardiovascular system and inflammatory biomarkers. Furthermore, little is known about biomarkers of aging and BA score (BAS) for healthy people in China. Objectives: The purpose of this study was to identify the biomarkers of healthy aging and to establish BAS for healthy people in China. Methods: We examined 2,876 men and women aged 30–98 years old in three Chinese cities, and 852 healthy subjects were assessed with 108 physical, morphological, physiological and biochemical variables. After excluding binary variables, variables that had a correlation coefficient with CA of ≤0.25 and redundant variables, eight variables including CA, arterial pulse pressure (PP), intima-media thickness (IMT), end diastolic velocity (EDV), ratio of peak velocity of early filling to atrial filling (E/A), mitral valve annulus lateral wall of peak velocity of early filling (MVEL), cystatin C (CYSC), and fibrinogen (FIB) were selected as candidate biomarkers of aging based on a factor-weighted BAS composite for predicting BA. Results: The BAS equation was 0.248 (CA) + 0.195 (IMT) – 0.196 (EDV) – 0.167 (E/A) – 0.166 (MVEL) + 0.188 (PP) + 0.182 (FIB) + 0.193 (CYSC). Individual BAS were significantly correlated with CA (r = 0.893, p < 0.001). Biological aging rate predicted by BAS was accelerated with increases in CA, and peaked when healthy men and women reached ≧75 years of age. Conclusions: Our data suggest that BAS is superior to CA in assessing the rate of aging in healthy Chinese people. The cardiovascular variables play a crucial role in the evaluation of biological aging. Biological aging rate appears to be age specific.

BackgroundAge‐related DNA methylation (DNAm) changes occur in specific regions of the genome and have been shown to be correlated with an individual’s chronological age. Multiple “epigenetic clocks” have been developed to estimate an individual’s DNAm age, which reflect different aspects of the multidimensional aging process. Age acceleration, the deviation of the DNAm‐estimated age from the chronological age, has been proposed as a novel biomarker of aging. We investigated the association between multiple measures of age acceleration and cognitive aging phenotypes in diverse Hispanic and Latino adults.MethodsWe estimated epigenetic age acceleration from 5 epigenetic clocks in 2188 Hispanic and Latino adults (mean age 56.7 years; 64.6% women) from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) who had available blood DNA methylation data at the baseline visit and neurocognitive data. These included first generation clocks, Horvath and Hannum clocks; second generation PhenoAge and GrimAge; and third generation DunedinPACE (Pace of Aging). We used mixed models to test the association of each of these measures with a global measure of cognitive function (PC1) at the baseline visit and with mild cognitive impairment at a follow‐up visit approximately 7 years later.ResultsThere were significant cross‐sectional associations between lower global cognitive function and greater age acceleration based on Hannum, Horvath, PhenoAge, and DunedinPACE algorithms. In addition, a greater age acceleration based on DunedinPACE was strongly associated with a higher risk of MCI 7 years later (Table).ConclusionBiological aging is associated with lower cognitive function and risk of MCI in diverse Hispanic and Latino adults. DunedinPACE, a third generation epigenetic clock, may be a more sensitive predictor of cognitive aging outcomes than previous generation clocks.

Biomarkers of ageing (BA) can predict health risks beyond chronological age, but little is known about how marital/living status affects longitudinal changes in BA. We examined the association between marital/living status and BA over time using the-Swedish-Adoption/Twin-Study-of-Aging (SATSA) cohort. Four BAs were analyzed: telomere length (TL) (638 individuals; 1603 measurements), DNAmAge (535 individuals; 1392 measurements), cognition (823 individuals; 3218 measurements), and frailty index (FI) (1828 individuals; 9502 measurements). Individuals were born between 1900 and 1948, and data on marital/living status, BAs, and covariates were collected through nine waves of questionnaires and in-person testing from 1986 to 2014. Mixed linear regression with random effects at twin-pair and individual levels were used to assess BA changes for constant marital/living status. Conditional generalized estimating equation assessed within-individual BA changes for varying marital/living status. Results showed that individuals who were consistently unmarried/non-cohabiting (β = 0.291, 95%CI = 0.189–0.393) or living alone (β = 0.203, 95%CI = 0.090–0.316) were more frail, and experienced accelerated frailty (p-for-interaction with age < 0.001 for marital status; p-for-interaction = 0.002 for living status) and cognitive decline (p-for-interaction < 0.001), compared to those married/cohabiting or living with someone Among individuals whose marital/living status changed, frailty was higher when living alone (β = 0.089, 95%CI = 0.017–0.162) and frailty accelerated when they became unmarried/non-cohabiting or were living alone (p-for-interaction < 0.001). Cognitive decline also accelerated when living alone (p-for-interaction = 0.020). No associations were observed for TL and DNAmAge. In conclusion, being unmarried/non-cohabiting or living alone from mid-to-old age is linked to accelerated cognitive decline and frailty. These findings highlight the potential importance of social support networks and living arrangements for healthy ageing.

BackgroundIndividual differences in the rate of aging and susceptibility to disease are not accounted for by chronological age alone. These individual differences are better explained by biological age, which may be estimated by biomarker prediction models. In the light of the aging demographics of the global population and the increase in lifestyle-related morbidities, it is interesting to invent a new biological age model to be used for health promotion.ObjectiveThis study aims to develop a model that estimates biological age based on physiological biomarkers of healthy aging.MethodsCarefully selected physiological variables from a healthy study population of 100 women and men were used as biomarkers to establish an estimate of biological age. Principal component analysis was applied to the biomarkers and the first principal component was used to define the algorithm estimating biological age.ResultsThe first principal component accounted for 31% in women and 25% in men of the total variance in the biological age model combining mean arterial pressure, glycated hemoglobin, waist circumference, forced expiratory volume in 1 second, maximal oxygen consumption, adiponectin, high-density lipoprotein, total cholesterol, and soluble urokinase-type plasminogen activator receptor. The correlation between the corrected biological age and chronological age was r=0.86 (P<.001) and r=0.81 (P<.001) for women and men, respectively, and the agreement was high and unbiased. No difference was found between mean chronological age and mean biological age, and the slope of the regression line was near 1 for both sexes.ConclusionsEstimating biological age from these 9 biomarkers of aging can be used to assess general health compared with the healthy aging trajectory. This may be useful to evaluate health interventions and as an aid to enhance awareness of individual health risks and behavior when deviating from this trajectory.Trial RegistrationClinicalTrials.gov NCT03680768; https://clinicaltrials.gov/ct2/show/NCT03680768International Registered Report Identifier (IRRID)RR2-10.2196/19209

Background and Aims There appears to be an accelerated ageing process seen among patients with end stage kidney disease. They often exhibit prematurely aged phenotypes which include frailty, sarcopenia and protein energy wasting. These phenotypes are associated with increased morbidity and mortality. The exact reason for premature ageing in this cohort is poorly understood. We hypothesised that biomarkers of cellular senescence and biological age may be associated with phenotypes of ageing observed in dialysis patients; in particular the frailty phenotype. Both telomere length (TL) and DNA methylation (DNAm) status have been recognised as predictors of biological age. The aim of the study was to investigate the relationship between TL and DNAm status with frailty phenotype among patients on dialysis. Method This was a single centre prospective observational study among eligible haemodialysis (HD) and peritoneal dialysis (PD) patients as per the inclusion and exclusion criteria. All recruited patients had their DNA extracted from peripheral leucocytes and frailty was measured by using the Fried Frailty Phenotype criteria. Extracted DNA was used to measure TL by quantitate polymerase chain reaction according to the modified Cawthon protocol. DNAm status was measured by sodium bisulphite conversion with targeted sequencing of 48 CpG sites. All baseline demographic data were obtained from electronic patient record. Results Between the period of December 2015 to July 2018, 239 dialysis (125 HD, 114 PD) patients were recruited. The age range of the study recruits were 23 to 83 years of age with a mean age of 54.3 years. There were 44 and 43 females in the HD and PD group respectively. All patients had TL measured and 228 patients (118 in HD, 110 in PD) had DNAm status measured successfully. Frailty assessments at baseline were completed in 213 patients (110 in HD, 103 in PD). A decrease in mean TL (p&amp;lt;0.001) and increased mean DNAm age (p&amp;lt;0.001) was observed in the frail group. TL and DNAm status were significantly associated with frailty in a univariate analysis, p=0.010 and p=0.014 respectively but only TL remained significant in a multivariate analysis to predict frailty, p=0.018. Increased frailty was observed in dialysis patients with shorter TL which remained significant following multivariate logistic regression analysis. A receiver operating characteristic curve analysis demonstrated that TL was a significant predictor of frailty, p&amp;lt;0.001 with an area under the curve of 0.64. A decrease of TL by one standard deviation was associated with a 52.2% increase risk of frailty when adjusted for age and gender in this dialysis cohort. Conclusion The study supports the hypothesis that TL; a biomarker of ageing is better associated with frailty, an ageing phenotype in comparison to DNAm status in dialysis patients. This is the first study to show a significant association between TL and frailty status in the dialysis patients. DNAm status is derived from an individual’s chronological age and may not be the best surrogate for chronological age. Therefore, to use this measure seems rather counter intuitive as the incorporation of chronological age might mask clinically significant associations that exist when the DNAm status is considered in isolation. These findings provide a preliminary proof of concept validation that TL is associated with frailty and may provide the basis of future research. The use of targeted methylation CpG sites may be a better predictor of frailty in this cohort which is an area that has sparked an interest.

Aging is a natural process defined by the gradual, time-dependent decline of biological and behavioural functions, for which individuals of the same chronological age show variability. The capacity of biological systems to continuously adjust for optimal functioning despite ever changing environments is essential for healthy aging, and variability in these adaptive homeostatic mechanisms may reflect such heterogeneity in the aging process. With an ever-increasing aging population, interest in biomarkers of aging is growing. Although no universally accepted definition of biomarkers of healthy aging exists, mediators of homeostasis are consistently used as measures of the aging process. As important sex differences are known to underlie many of these systems, it is imperative to consider that this may reflect, to some extent, the sex differences observed in aging and age-related disease states. This chapter aims to outline sex differences in key homeostatic domains thought to be associated with the pathophysiology of aging, often proposed as biomarkers of aging and age-related disease states. This includes considering sex-based differences and hormonal status with regards to the gonadal and adrenal endocrine systems and immune function.

Introduction. Glycomic analysis allows investigating on the global glycome within body fluids (as serum/plasma), this could eventually lead to identify new types of disease biomarkers, or as in this study, biomarkers of human aging studying specific aging models. Recent studies demonstrated that the plasma N-glycome is modified during human aging, suggesting that measurements of log-ratio of two serum/plasma N-glycans (NGA2F and NA2F), named GlycoAge test could provide a non-invasive biomarker of aging. Down syndrome (DS) is a genetic disorder in which multiple major aspects of senescent phenotype occur much earlier than in healthy age-matched subjects and has been often defined as an accelerated aging syndrome. The aim of this study was to compare plasma N-glycome of patients affected by DS with age- and sex matched non-affected controls, represented by their siblings (DSS), in order to assess if DS is characterized by a specific N-glycomic pattern. Therefore, in order to investigate if N-glycans changes that occur in DS were able to reveal an accelerated aging in DS patients, we enrolled the mothers (DSM) of the DS and DSS, representing the non-affected control group with a different chronological age respect to DS. We applied two different N-glycomics approaches on the same samples: first, in order to study the complete plasma N-glycome we applied a new high-sensitive protocol based on a MALDI-TOF-MS approach, second, we used DSA-FACE technology. Results: MALDI-TOF/MS analysis detected a specific N-glycomics signature for DS, characterized by an increase of fucosylated and bisecting species. Moreover, in DS the abundance of agalactosylated (as NA2F) species was similar or higher than their mothers. The measurement of GlycoAge test with DSA-FACE, validated also by MALDI-TOF, demonstrated a strongly association with age, moreover in DS, it’s value was similar to their mothers, and significantly higher than their age- and sex matched not-affected siblings

Chronological age is used as a marker for age-associated changes in cognitive function. However, there is great interindividual variability in cognitive ability among people of the same age. Physiological age rather than chronological age should be more closely associated with age-related cognitive changes because these changes are not universal and are likely dependent on several factors in addition to the number of years lived. Cognitive function is associated with successful self-management, and a biological marker that reflects physiological age and is associated with cognitive function could be used to identify risk for failure to self-manage. The purpose of this study was to investigate the association between telomere length, a known biomarker of age; blood pressure; cognitive assessments; and adherence to antihypertensive medication among community-dwelling middle-aged and older adults. The authors administered a battery of cognitive assessments to 42 participants (M = 69 years of age), collected blood samples, and isolated peripheral blood mononuclear leukocytes for genomic DNA. The authors determined relative telomere length using Cawthon's method for real-time quantitative polymerase chain reaction (RT-qPCR) and measured medication adherence using an electronic medication monitoring system (MEMS by Aardex) over 8 weeks. Findings indicate that telomere length was inversely associated with systolic blood pressure (r = -.38, p < .01) and diastolic blood pressure (r = -.42, p < .01) but not with cognitive assessments or adherence. The authors discuss the nonsignificant findings between telomere length and cognitive assessments including the potential modifying role of gender.

ABSTRACTAdvanced age is the most important risk factor for dementia. Measures of biological ageing such as DNA methylation age (DNAmAge) can give more information about the accumulation of age‐related molecular damage in different organs than chronological age alone. Using post‐mortem brain tissue from Swedish Twin Registry participants, we explored the relationship between lifestyle factors, dementia and DNAmAge measures from prefrontal cortex and cerebellum (n = 27 individuals) and paired blood samples (n = 20 individuals). We observed that smoking was associated with a higher DNAmAge deviation (PCBrainAge + 6.4 years in prefrontal cortex, CI [2.5, 10.3], p = 0.004). Conversely, a longer time spent in formal education was associated with a lower DNAmAge deviation (DNAmClockCortical − 4.8 years in prefrontal cortex, CI [−7.9, −1.8], p = 0.007). We found no significant differences between DNAmAge deviation of dementia cases versus controls, though among dementia cases there was a tendency towards higher DNAmClockCortical deviation in prefrontal cortex for those with a more advanced Braak stage on histopathological assessment (+ 3.4 years, CI [−0.68, 7.50], p = 0.13). There were no clear associations between DNAmAge from brain and blood samples collected prior to death. In summary, these data highlight the impact of smoking and education on biomarkers of brain ageing and emphasise the role for organ‐specific biomarkers of ageing.

Allogeneic Hematopoietic Cell Transplantation Causes Accelerated Aging Both of the Hematopoietic and Somatic Systems

Gerontological research reveals considerable interindividual variability in aging phenotypes, which has motivated research efforts to identify “aging biomarkers.” Aging biomarkers are used to calculate biological age, which are better predictors of disease risk and residual lifespan when compared to chronological age alone. Emerging evidence using the epigenetic clock as an aging biomarker supports highly reliable individualized predictions about future health. This study aimed to determine whether an epigenetic aging biomarker was associated with chronic pain in older adults (60–83 years old). A subset of participants (n = 29) in the Neuromodulatory Examination of Pain and Mobility Across the Lifespan study underwent a blood draw, demographic, psychological, cognitive, and pain assessments. We estimated Horvath’s epigenetic clock and calculated the difference between epigenetic age and chronological age that has been previously reported to predict overall mortality risk. Older individuals without chronic pain (n = 9) had significantly “younger” epigenetic age compared to those with chronic pain (n = 20, p < 0.05). Older epigenetic age was associated with greater pain during daily activities (r = 0.494, p = 0.010) and anatomical pain sites (r = 0.741, p < 0.001) but not pain frequency/duration. An older epigenetic age was also associated with higher vibratory detection thresholds (r = 0.490, p = 0.021), heat pain thresholds (r = −0.478, p = 0.028), and pressure pain thresholds at the trapezius (r = −0.571, p = 0.006) but not thermal detection, pressure pain at the quadriceps or pain inhibition (p’s > 0.05). Epigenetic aging was associated with greater emotional stability (r = −0.461, p = 0.027), conscientiousness (r = −0.549, p = 0.007), and lower extraversion (r = 0.414, p = 0.049) but not depression or affect (p’s > 0.05). Epigenetic aging was also associated with lower episodic (r = −0.698, p = 0.001) and working memory (r = −0.760, p < 0.001). Our findings suggest that chronic pain is associated with accelerated epigenetic aging in healthy, community-dwelling older individuals, and future studies with larger samples are needed to confirm our findings. An aging biomarker such as the epigenetic clock may help identify people with chronic pain at greater risk of functional decline and poorer health outcomes.

We identified a "cognitive clock," a novel indicator of brain health that provides person-specific estimates of cognitive age, and tested the hypothesis that cognitive age is a better predictor of brain health than chronological age in two independent datasets. The initial analyses were based on 1057 participants from the Rush Memory and Aging Project and the Religious Orders Study who began without impairment and underwent cognitive assessments up to 24 years. A shape invariant model characterized the latent pattern of cognitive decline, conceptualized here as the "cognitive clock," and yielded person-specific estimates of cognitive age. Survival analyses examined cognitive versus chronological age for predicting Alzheimer's disease dementia, mild cognitive impairment and mortality, and regression analyses examined associations of cognitive versus chronological age with neuropathology and brain atrophy. Finally, we applied the cognitive clock to an independent validation sample of 2592 participants from the Chicago Health and Aging Project, a biracial population-based study, to confirm the predictive utility of cognitive age. The "cognitive clock" showed that cognition remained stable until a cognitive age of about 80, then declined moderately until 90, then declined precipitously. In the initial dataset, cognitive age was a better predictor of dementia, mild cognitive impairment and mortality than chronological age, and was more strongly associated with neuropathology and brain atrophy. Application of the cognitive clock to the independent validation sample provided further support for the utility of cognitive age as a strong prognostic indicator of adverse outcomes. Cognitive age is a robust prognostic indicator of adverse health outcomes and may serve as a useful biomarker in aging research.