Lifestyle-related factors in late midlife as predictors of frailty from late midlife into old age: a longitudinal birth cohort study.

BACKGROUND: Few studies have examined longitudinal changes in lifestyle-related factors and frailty. METHODS: We examined the association between individual lifestyle factors (exercise, diet, sleep, alcohol, smoking and body composition), their sum at baseline, their change over the 17-year follow-up and the rate of change in frailty index values using linear mixed models in a cohort of 2,000 participants aged 57-69 years at baseline. RESULTS: A higher number of healthy lifestyle-related factors at baseline was associated with lower levels of frailty but not with its rate of change from late midlife into old age. Participants who stopped exercising regularly (adjusted ß × Time = 0.19, 95%CI = 0.10, 0.27) and who began experiencing sleeping difficulties (adjusted ß × Time = 0.20, 95%CI = 0.10, 0.31) experienced more rapid increases in frailty from late midlife into old age. Conversely, those whose sleep improved (adjusted ß × Time = -0.10, 95%CI = -0.23, -0.01) showed a slower increase in frailty from late midlife onwards. Participants letting go of lifestyle-related factors (decline by 3+ factors vs. no change) became more frail faster from late midlife into old age (adjusted ß × Time = 0.16, 95% CI = 0.01, 0.30). CONCLUSIONS: Lifestyle-related differences in frailty were already evident in late midlife and persisted into old age. Adopting one new healthy lifestyle-related factor had a small impact on a slightly less steeply increasing level of frailty. Maintaining regular exercise and sleeping habits may help prevent more rapid increases in frailty.

Frailty in Midlife as a Predictor of Changes in Body Composition from Midlife into Old Age: A Longitudinal Birth Cohort Study.

INTRODUCTION: Few studies have investigated the association between frailty and subsequent body composition. METHODS: We performed separate linear mixed model analyses to study the associations between changes in the participant frailty status assessed by a frailty index (FI) and subsequent body mass index (BMI), lean mass index (LMI), fat mass index (FMI), and FMI to LMI ratio values assessed on three occasions over 17 years. The analyses were carried out among 996 participants spanning from age 57 to 84 years. RESULTS: With advancing age, LMI and BMI decreased, whereas FMI and FMI to LMI ratio increased. Participants with "stable frailty," followed by those with "increasing frailty" experienced faster decreases in LMI and faster increases in FMI and FMI to LMI ratio values from midlife into old age relative to those in the group "stable not frail." Contrastingly, those in the highest third of absolute annual increase in FMI and FMI to LMI ratio became more frail faster from midlife into old age relative to those in the lowest third. CONCLUSIONS: We found evidence of an adverse health outcome of frailty where lean indices declined faster and fat indices and fat-to-lean ratios increased faster from midlife into old age. The changes resembled those that occurred with aging, but at a faster pace. The relationship between body composition and frailty is likely bidirectional, where high or increasing levels of fat are associated with the risk of becoming more frail earlier, but where a longer duration of frailty may increase the risk of faster age-related changes to body composition.

Association of cancer with functional decline at old age: a longitudinal study in Danish twins.

INTRODUCTION: There is evidence that older adults with cancer have a higher risk of functional decline than cancer-free older adults. However, few studies are longitudinal, and none are twin studies. Thus, we aimed to investigate the relationship between cancer and functional decline in older adult (aged 70+ years) twins. MATERIALS AND METHODS: Cancer cases in the Longitudinal Study of Aging Danish Twins were identified through the Danish Cancer Registry. Functional status was assessed using hand grip strength (6 years follow-up), and self-reported questions on mobility (10 years follow-up), and cut-offs were defined to assess functional decline. Cox regression models were performed for all the individual twins. In addition, we extended the analysis to discordant twin pairs (twin pairs with one having cancer and the other being cancer-free), to control to a certain extent for (unmeasured) shared confounders (genetic and environmental factors). RESULTS: The analysis based on individual twins showed that individual twins with cancer are at increased hazard of worsening hand grip strength (hazard ratio (HR) 1.37, 95% confidence interval (CI) 1.04, 1.80) than cancer-free twins. Among the discordant twin pairs, twins with cancer had a higher hazard of worsening hand grip strength (HR 3.50, 95% CI 1.15, 10.63) than cancer-free cotwins. In contrast, there was no evidence of a difference between the hazard of experiencing mobility decline for twins with cancer compared with cancer-free twins, in both individual twins and discordant twin pairs analyses. DISCUSSION: Cancer was associated with hand grip strength functional decline in old individual twins and discordant pairs. Our results strengthen the importance of comprehensive geriatric assessment in older adults with cancer, as well as the importance of routine assessment of functional status. Promoting physical activity through exercise training programmes could enable the prevention of functional decline in older adults with cancer.

Clinical biomarker-based biological aging and risk of cancer in the UK Biobank.

BACKGROUND: Despite a clear link between aging and cancer, there has been inconclusive evidence on how biological age (BA) may be associated with cancer incidence. METHODS: We studied 308,156 UK Biobank participants with no history of cancer at enrolment. Using 18 age-associated clinical biomarkers, we computed three BA measures (Klemera-Doubal method [KDM], PhenoAge, homeostatic dysregulation [HD]) and assessed their associations with incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, and melanoma) using Cox proportional-hazards models. RESULTS: A total of 35,426 incident cancers were documented during a median follow-up of 10.9 years. Adjusting for common cancer risk factors, 1-standard deviation (SD) increment in the age-adjusted KDM (hazard ratio = 1.04, 95% confidence interval = 1.03-1.05), age-adjusted PhenoAge (1.09, 1.07-1.10), and HD (1.02, 1.01-1.03) was significantly associated with a higher risk of any cancer. All BA measures were also associated with increased risks of lung and colorectal cancers, but only PhenoAge was associated with breast cancer risk. Furthermore, we observed an inverse association between BA measures and prostate cancer, although it was attenuated after removing glycated hemoglobin and serum glucose from the BA algorithms. CONCLUSIONS: Advanced BA quantified by clinical biomarkers is associated with increased risks of any cancer, lung cancer, and colorectal cancer.

Is Frailty Different in Younger Adults Compared to Old? Prevalence, Characteristics, and Risk Factors of Early-Life and Late-Life Frailty in Samples from Sweden and UK.

INTRODUCTION: Although frailty is commonly considered as a syndrome of old individuals, recent studies show that it can affect younger adults, too. Whether and how frailty differs in younger adults compared to old is however unknown. To this end, we analyzed the prevalence, characteristics, and risk factors of early-life (aged <65) and late-life (aged ≥65) frailty. METHODS: We analyzed individuals in the UK Biobank (N = 405,123) and Swedish Screening Across the Lifespan Twin (SALT; N = 43,641) study. Frailty index (FI) scores ≥0.21 were used to demarcate frailty. Characteristics of early-life versus late-life frailty were analyzed by collating the FI items (deficits) into domains and comparing the domain scores between younger and older frail individuals. Logistic regression was used to assess the risk factors of frailty. RESULTS: The pooled prevalence rates of frailty were 10.3% (95% confidence interval [CI]: 2.7-32.7), 14.4% (95% CI: 4.5-37.2), 19.2% (95% CI: 2.5-68.5) in individuals aged ≤55, 55-64, 65-74, respectively. Younger frail adults (aged <65) had higher scores in immunological, mental wellbeing, and pain-related domains, whereas older frail adults (aged ≥65) had higher scores in cardiometabolic, cancer, musculoskeletal, and sensory-related domains. Higher age, female sex, smoking, lower alcohol consumption, lower education, obesity, overweight, low income, and maternal smoking were similarly associated with the risk of early-life and late-life frailty. CONCLUSION: Frailty is prevalent also in younger age groups (aged <65) but differs in some of its characteristics from the old. The risk factors of frailty are nevertheless largely similar for early-life and late-life frailty.

Two Years with COVID-19: The Electronic Frailty Index Identifies High-Risk Patients in the Stockholm GeroCovid Study.

INTRODUCTION: Frailty, a measure of biological aging, has been linked to worse COVID-19 outcomes. However, as the mortality differs across the COVID-19 waves, it is less clear whether a medical record-based electronic frailty index (eFI) that we have previously developed for older adults could be used for risk stratification in hospitalized COVID-19 patients. OBJECTIVES: The aim of the study was to examine the association of frailty with mortality, readmission, and length of stay in older COVID-19 patients and to compare the predictive accuracy of the eFI to other frailty and comorbidity measures. METHODS: This was a retrospective cohort study using electronic health records (EHRs) from nine geriatric clinics in Stockholm, Sweden, comprising 3,980 COVID-19 patients (mean age 81.6 years) admitted between March 2020 and March 2022. Frailty was assessed using a 48-item eFI developed for Swedish geriatric patients, the Clinical Frailty Scale, and the Hospital Frailty Risk Score. Comorbidity was measured using the Charlson Comorbidity Index. We analyzed in-hospital mortality and 30-day readmission using logistic regression, 30-day and 6-month mortality using Cox regression, and the length of stay using linear regression. Predictive accuracy of the logistic regression and Cox models was evaluated by area under the receiver operating characteristic curve (AUC) and Harrell's C-statistic, respectively. RESULTS: Across the study period, the in-hospital mortality rate decreased from 13.9% in the first wave to 3.6% in the latest (Omicron) wave. Controlling for age and sex, a 10% increment in the eFI was significantly associated with higher risks of in-hospital mortality (odds ratio = 2.95; 95% confidence interval = 2.42-3.62), 30-day mortality (hazard ratio [HR] = 2.39; 2.08-2.74), 6-month mortality (HR = 2.29; 2.04-2.56), and a longer length of stay (ß-coefficient = 2.00; 1.65-2.34) but not with 30-day readmission. The association between the eFI and in-hospital mortality remained robust across the waves, even after the vaccination rollout. Among all measures, the eFI had the best discrimination for in-hospital (AUC = 0.780), 30-day (Harrell's C = 0.733), and 6-month mortality (Harrell's C = 0.719). CONCLUSION: An eFI based on routinely collected EHRs can be applied in identifying high-risk older COVID-19 patients during the continuing pandemic.

Comparison of two different frailty scales in the longitudinal Swedish Adoption/Twin Study of Aging (SATSA).

AIMS: Although up to 25% of older adults are frail, assessing frailty can be difficult, especially in registry data. This study evaluated the utility of a code-based frailty score in registry data by comparing it to a gold-standard frailty score to understand how frailty can be quantified in population data and perhaps better addressed in healthcare. METHODS: We compared the Hospital Frailty Risk Score (HFRS), a frailty measure based on 109 ICD codes, to a modified version of the Frailty Index (FI) Frailty Index (FI), a self-report frailty measure, and their associations with all-cause mortality both cross-sectionally and longitudinally (follow-up = 36 years) in a Swedish cohort study (n = 1368). RESULTS: The FI and HFRS were weakly correlated (rho = 0.11, p < 0.001). Twenty-two percent (n = 297) of participants were considered frail based on published cut-offs of either measure. Only 3% (n = 35) of participants were classified as frail by both measures; 4% (n = 60) of participants were considered frail by only the HFRS; and 15% (n = 202) of participants were considered frail based only on the FI. Frailty as measured by the HFRS showed greater variance and no clear increase or decrease with age, while frailty as measured by the FI increased steadily with age. In adjusted Cox proportional hazard models, baseline HFRS frailty (HR = 1.17, 95% CI 0.92, 1.49) was not statistically significantly associated with mortality, while FI frailty was (HR = 2.89, 95% CI 1.61, 2.23). These associations were modified by age and sex. CONCLUSIONS: The HFRS may not capture the full spectrum of frailty among community-dwelling individuals, particularly at younger ages, in Swedish registry data.

Prevalence and Implications of Frailty in Older Adults With Incident Inflammatory Bowel Diseases: A Nationwide Cohort Study.

BACKGROUND AND AIMS: We aimed to compare the risk of frailty in older adults with incident inflammatory bowel disease (IBD) and matched non-IBD comparators and assess the association between frailty and future hospitalizations and mortality. METHODS: In a cohort of patients with incident IBD ≥60 years of age from 2007 to 2016 in Sweden identified using nationwide registers, we defined frailty using Hospital Frailty Risk Score. We compared prevalence of frailty in patients with IBD with age, sex, place of residency- and calendar year-matched population comparators. In the IBD cohort, we used Cox proportional hazards modeling to examine the associations between frailty risk and hospitalizations or mortality. RESULTS: We identified 10,590 patients with IBD, 52% female with a mean age of 71 years of age, matched to 103,398 population-based comparators. Among patients with IBD, 39% had no risk for frailty, 49% had low risk for frailty, and 12% had higher risk for frailty. Mean Hospital Frailty Risk Score was 1.9 in IBD and 0.9 in matched comparators (P < .01). Older adults with IBD at higher risk for frailty had a 20% greater risk for mortality at 3 years compared with those who were not frail. Compared with nonfrail older patients with IBD, patients at higher risk for frailty had increased mortality (hazard ratio [HR], 3.22, 95% confidence interval [CI], 2.86-3.61), all-cause hospitalization (HR, 2.42; 95% CI, 2.24-2.61), and IBD-related hospitalization (HR, 1.50; 95% CI, 1.35-1.66). These associations were not attenuated after adjusting for comorbidities. CONCLUSIONS: Frailty is more prevalent in older adults with IBD than in matched comparators. Among older patients with IBD, frailty is associated with increased risk for hospitalizations and mortality.

Protein Nutritional Status and Frailty: A Mendelian Randomization Study.

BACKGROUND: Observational studies have suggested that better protein nutritional status may contribute to prevention of frailty. OBJECTIVE: We sought to examine this hypothesis using a Mendelian randomization (MR) analysis. METHODS: We conducted a two-sample MR study using GWAS summary statistics data of the UK Biobank. We applied genetically predicted serum albumin as a primary exposure measure and serum total protein as a secondary exposure measure. The outcome measure was the Rockwood frailty index (FI) based on 49 deficits from 356,432 individuals (53.3% of them were women, with a mean ± SD age of 56.7 ± 8.0 y. The association between serum protein measures and FI was mainly analyzed by use of the inverse variance weighted method. RESULTS: A genetically predicted serum albumin concentration was not statistically significantly associated with FI in the full sample. However, in women, we observed a preventive association between genetically predicted serum albumin and FI (ß = -0.172 per g/L; 95% CI: -0.336, -0.007; P = 0.041). In the full sample, genetically predicted serum total protein was inversely associated with FI (ß: -0.153 per g/L; 95% CI: -0.251, -0.056; P = 0.002). In both women and men, higher serum total protein was significantly inversely associated with FI; regression coefficients were -0.148 per g/L (95% CI: -0.287, -0.009; P = 0.037) for women, -0.154 per g/L (95% CI: -0.290, -0.018; P = 0.027) for men. CONCLUSIONS: The present MR study implies that better protein nutritional status modestly contributes to reducing the risk of frailty.

DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan.

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10-7; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.

COVID-19 prevalence and mortality in longer-term care facilities.

This essay considers the factors that have contributed to very high COVID-19 mortality in longer-term care facilities (LTCFs). We compare the demographic characteristics of LTCF residents with those of community-dwelling older adults, and then we review the evidence regarding prevalence and infection fatality rates (IFRs), including links to frailty and some comorbidities. Finally, we discuss policy measures that could foster the physical and mental health and well-being of LTCF residents in the present context and in potential future pandemics.

Adiposity and the risk of dementia: mediating effects from inflammation and lipid levels.

While midlife adiposity is a risk factor for dementia, adiposity in late-life appears to be associated with lower risk. What drives the associations is poorly understood, especially the inverse association in late-life. Using results from genome-wide association studies, we identified inflammation and lipid metabolism as biological pathways involved in both adiposity and dementia. To test if these factors mediate the effect of midlife and/or late-life adiposity on dementia, we then used cohort data from the Swedish Twin Registry, with measures of adiposity and potential mediators taken in midlife (age 40-64, n = 5999) or late-life (age 65-90, n = 7257). Associations between body-mass index (BMI), waist-hip ratio (WHR), C-reactive protein (CRP), lipid levels, and dementia were tested in survival and mediation analyses. Age was used as the underlying time scale, and sex and education included as covariates in all models. Fasting status was included as a covariate in models of lipids. One standard deviation (SD) higher WHR in midlife was associated with 25% (95% CI 2-52%) higher dementia risk, with slight attenuation when adjusting for BMI. No evidence of mediation through CRP or lipid levels was present. After age 65, one SD higher BMI, but not WHR, was associated with 8% (95% CI 1-14%) lower dementia risk. The association was partly mediated by higher CRP, and suppressed when high-density lipoprotein levels were low. In conclusion, the negative effects of midlife adiposity on dementia risk were driven directly by factors associated with body fat distribution, with no evidence of mediation through inflammation or lipid levels. There was an inverse association between late-life adiposity and dementia risk, especially where the body's inflammatory response and lipid homeostasis is intact.

Deciphering the genetic and epidemiological landscape of mitochondrial DNA abundance.

Mitochondrial (MT) dysfunction is a hallmark of aging and has been associated with most aging-related diseases as well as immunological processes. However, little is known about aging, lifestyle and genetic factors influencing mitochondrial DNA (mtDNA) abundance. In this study, mtDNA abundance was estimated from the weighted intensities of probes mapping to the MT genome in 295,150 participants from the UK Biobank. We found that the abundance of mtDNA was significantly elevated in women compared to men, was negatively correlated with advanced age, higher smoking exposure, greater body-mass index, higher frailty index as well as elevated red and white blood cell count and lower mortality. In addition, several biochemistry markers in blood-related to cholesterol metabolism, ion homeostasis and kidney function were found to be significantly associated with mtDNA abundance. By performing a genome-wide association study, we identified 50 independent regions genome-wide significantly associated with mtDNA abundance which harbour multiple genes involved in the immune system, cancer as well as mitochondrial function. Using mixed effects models, we estimated the SNP-heritability of mtDNA abundance to be around 8%. To investigate the consequence of altered mtDNA abundance, we performed a phenome-wide association study and found that mtDNA abundance is involved in risk for leukaemia, hematologic diseases as well as hypertension. Thus, estimating mtDNA abundance from genotyping arrays has the potential to provide novel insights into age- and disease-relevant processes, particularly those related to immunity and established mitochondrial functions.

Frailty and the risk of dementia: is the association explained by shared environmental and genetic factors?

BACKGROUND: Frailty has been identified as a risk factor for cognitive impairment and dementia. However, it is not known whether familial factors, such as genetics and shared environmental factors, underlie this association. We analyzed the association between frailty and the risk of dementia in a large twin cohort and examined the role of familial factors in the association. METHODS: The Rockwood frailty index (FI) based on 44 health deficits was used to assess frailty. The population-level association between FI and the risk of all-cause dementia was analyzed in 41,550 participants of the Screening Across the Lifespan Twin (SALT) study (full sample, aged 41-97 years at baseline), using Cox and competing risk models. A subsample of 10,487 SALT participants aged 65 and older who received a cognitive assessment (cognitive sample) was used in a sensitivity analysis to assess the effect of baseline cognitive level on the FI-dementia association. To analyze the influence of familial effects on the FI-dementia association, a within-pair analysis was performed. The within-pair model was also used to assess whether the risk conferred by frailty varies by age at FI assessment. RESULTS: A total of 3183 individuals were diagnosed with dementia during the 19-year follow-up. A 10% increase in FI was associated with an increased risk of dementia (hazard ratio [HR] 1.17 (95% confidence interval [CI] 1.07, 1.18)) in the full sample adjusted for age, sex, education, and tobacco use. A significant association was likewise found in the cognitive sample, with an HR of 1.13 (95% CI 1.09, 1.20), adjusted for age, sex, and cognitive level at baseline. The associations were not attenuated when adjusted for APOE ɛ4 carrier status or considering the competing risk of death. After adjusting for familial effects, we found no evidence for statistically significant attenuation of the effect. The risk conferred by higher FI on dementia was constant after age 50 until very old age. CONCLUSIONS: A higher level of frailty predicts the risk of dementia and the association appears independent of familial factors. Targeting frailty might thus contribute to preventing or delaying dementia.

Frailty trajectories in three longitudinal studies of aging: Is the level or the rate of change more predictive of mortality?

BACKGROUND: frailty shows an upward trajectory with age, and higher levels increase the risk of mortality. However, it is less known whether the shape of frailty trajectories differs by age at death or whether the rate of change in frailty is associated with mortality. OBJECTIVES: to assess population frailty trajectories by age at death and to analyse whether the current level of the frailty index (FI) i.e. the most recent measurement or the person-specific rate of change is more predictive of mortality. METHODS: 3,689 individuals from three population-based cohorts with up to 15 repeated measurements of the Rockwood frailty index were analysed. The FI trajectories were assessed by stratifying the sample into four age-at-death groups: <70, 70-80, 80-90 and >90 years. Generalised survival models were used in the survival analysis. RESULTS: the FI trajectories by age at death showed that those who died at <70 years had a steadily increasing trajectory throughout the 40 years before death, whereas those who died at the oldest ages only accrued deficits from age ~75 onwards. Higher level of FI was independently associated with increased risk of mortality (hazard ratio 1.68, 95% confidence interval 1.47-1.91), whereas the rate of change was no longer significant after accounting for the current FI level. The effect of the FI level did not weaken with time elapsed since the last measurement. CONCLUSIONS: Frailty trajectories differ as a function of age-at-death category. The current level of FI is a stronger marker for risk stratification than the rate of change.

Replicating associations between DNA methylation and body mass index in a longitudinal sample of older twins.

BACKGROUND: There is an important interplay between epigenetic factors and body weight, and previous work has identified ten sites where DNA methylation is robustly associated with body mass index (BMI) cross-sectionally. However, interpretation of the associations is complicated by the substantial changes in BMI often occurring in late-life, and the fact that methylation is often driven by genetic variation. This study therefore investigated the longitudinal association between these ten sites and BMI from midlife to late-life, and whether associations persist after controlling for genetic factors. METHODS: We used data from 535 individuals (mean age 68) in the Swedish Adoption/Twin Study of Aging (SATSA) with longitudinal measures of both DNA methylation from blood samples and BMI, spanning up to 20 years. Methylation levels were measured with the Infinium Human Methylation 450K or Infinium MethylationEpic array, with seven of the ten sites passing quality control. Latent growth curve models were applied to investigate longitudinal associations between methylation and BMI, and between-within models to study associations within twin pairs, thus adjusting for genetic factors. RESULTS: Baseline DNA methylation levels at five of the seven sites were associated with BMI level at age 65 (cg00574958 [CPT1A]; cg11024682 [SREBF1]), and/or change (cg06192883 [MYO5C]; cg06946797 [RMI2]; cg08857797 [VPS25]). For four of the five sites, the associations remained comparable within twin pairs. However, the effects of cg06192883 were substantially attenuated within pairs. No change in DNA methylation was detected for any of the seven evaluated sites. CONCLUSION: Five of the seven sites investigated were associated with late-life level and/or change in BMI. The effects for four of the sites remained similar when examined within twin pairs, indicating that the associations are mainly environmentally driven. However, the substantial attenuation in the association between cg06192883 and late-life BMI within pairs points to the importance of genetic factors in this association.

Lung-protective ventilation suppresses systemic and hepatic vein levels of cell-free DNA in porcine experimental post-operative sepsis.

BACKGROUND: Plasma levels of cell-free DNA (cf-DNA) are known to be elevated in sepsis and high levels are associated with a poor prognosis. Mechanical ventilation affects systemic inflammation in which lung-protective ventilation attenuates the inflammatory response. The aim was to study the effect of a lung protective ventilator regime on arterial and organ-specific venous blood as well as on trans-organ differences in cf-DNA levels in a porcine post-operative sepsis model. METHOD: One group of anaesthetised, domestic-breed, 9-12 weeks old, pigs were ventilated with protective ventilation (VT 6 mL x kg- 1, PEEP 10 cmH2O) n = 20. Another group, ventilated with a medium high tidal volume and lower PEEP, served as a control group (VT 10 mL x kg- 1, PEEP 5 cm H2O) n = 10. Blood samples were taken from four sources: artery, hepatic vein, portal vein and, jugular bulb. A continuous endotoxin infusion at 0.25 µg x kg- 1 x h- 1 for 5 h was started following 2 h of laparotomy, which simulated a surgical procedure. Inflammatory cytokines and cf-DNA in plasma were analysed and trans-organ differences calculated. RESULTS: The protective ventilation group had lower levels of cf-DNA in arterial (p = 0.02) and hepatic venous blood (p = 0.03) compared with the controls. Transhepatic differences in cf-DNA were lower in the protective group, compared with the controls (p = 0.03). No differences between the groups were noted as regards the transcerebral, transsplanchnic or the transpulmonary cf-DNA differences. CONCLUSIONS: Protective ventilation suppresses arterial levels of cf-DNA. The liver seems to be a net contributor to the systemic cf-DNA levels, but this effect is attenuated by protective ventilation.

The frailty index is a predictor of cause-specific mortality independent of familial effects from midlife onwards: a large cohort study.

BACKGROUND: Frailty index (FI) is a well-established predictor of all-cause mortality, but less is known for cause-specific mortality and whether familial effects influence the associations. Middle-aged individuals are also understudied for the association between FI and mortality. Furthermore, the population mortality impact of frailty remains understudied. METHODS: We estimated the predictive value of FI for all-cause and cause-specific mortality, taking into account familial factors, and tested whether the associations are time-dependent. We also assessed the proportion of all-cause and cause-specific deaths that are attributable to increased levels of frailty. We analyzed 42,953 participants from the Screening Across the Lifespan Twin Study (aged 41-95 years at baseline) with up to 20 years' mortality follow-up. The FI was constructed using 44 health-related items. Deaths due to cardiovascular disease (CVD), respiratory-related causes, and cancer were considered in the cause-specific analysis. Generalized survival models were used in the analysis. RESULTS: Increased FI was associated with higher risks of all-cause, CVD, and respiratory-related mortality, with the corresponding hazard ratios of 1.28 (1.24, 1.32), 1.31 (1.23, 1.40), and 1.23 (1.11, 1.38) associated with a 10% increase in FI in male single responders, and 1.21 (1.18, 1.25), 1.27 (1.15, 1.34), and 1.26 (1.15, 1.39) in female single responders. No significant associations were observed for cancer mortality. No attenuation of the mortality associations in unrelated individuals was observed when adjusting for familial effects in twin pairs. The associations were time-dependent with relatively greater effects observed in younger ages. Before the age of 80, the proportions of deaths attributable to FI levels > 0.21 were 18.4% of all-cause deaths, 25.4% of CVD deaths, and 20.4% of respiratory-related deaths in men and 19.2% of all-cause deaths, 27.8% of CVD deaths, and 28.5% of respiratory-related deaths in women. After the age of 80, the attributable proportions decreased, most notably for all-cause and CVD mortality. CONCLUSIONS: Increased FI predicts higher risks of all-cause, CVD, and respiratory-related mortality independent of familial effects. Increased FI presents a relatively greater risk factor at midlife than in old age. Increased FI has a significant population mortality impact that is greatest through midlife until the age of 80.

Neuroticism as a Predictor of Frailty in Old Age: A Genetically Informative Approach.

OBJECTIVE: Neuroticism is associated with poor health outcomes, but its contribution to the accumulation of health deficits in old age, that is, the frailty index, is largely unknown. We aimed to explore associations between neuroticism and frailty cross-sectionally and longitudinally, and to investigate the contribution of shared genetic influences. METHODS: Data were derived from the UK Biobank (UKB; n = 274,951), the Australian Over 50's Study (AO50; n = 2849), and the Swedish Twin Registry (Screening Across the Lifespan of Twins Study [SALT], n = 18,960; The Swedish Adoption/Twin Study of Aging [SATSA], n = 1365). Associations between neuroticism and the frailty index were investigated using regression analysis cross-sectionally in UKB, AO50, and SATSA and longitudinally in SALT (25-29 years of follow-up) and SATSA (6 and 23 years of follow-up). The co-twin control method was applied to explore the contribution of underlying shared familial factors (SALT, SATSA, AO50). Genome-wide polygenic risk scores for neuroticism were used in all samples to further assess whether common genetic variants associated with neuroticism predict frailty. RESULTS: High neuroticism was consistently associated with greater frailty cross-sectionally (adjusted ß [95% confidence intervals] in UKB = 0.32 [0.32-0.33]; AO50 = 0.35 [0.31-0.39]; SATSA = 0.33 [0.27-0.39]) and longitudinally up to 29 years (SALT = 0.24 [0.22-0.25]; SATSA 6 years = 0.31 [0.24-0.38]; SATSA 23 years = 0.16 [0.07-0.25]). When adjusting for underlying shared genetic and environmental factors, the neuroticism-frailty association remained significant, although decreased. Polygenic risk scores for neuroticism significantly predicted frailty in the two larger samples (meta-analyzed total ß = 0.059 [0.055-0.062]). CONCLUSIONS: Neuroticism in midlife predicts frailty in late life. Neuroticism may have a causal influence on frailty, whereas both environmental and genetic influences, including neuroticism-associated common genetic variants, contribute to this relationship.

Can markers of biological age predict dependency in old age?

Recent research has shown that markers of biological age, such as leukocyte telomere length (LTL), epigenetic clocks and the frailty index (FI) are predictive of mortality and age-related diseases. However, whether these markers associate with the need for care in old age, thereby having utility in reflecting dependency, is unclear. This study was undertaken to analyze whether LTL, two epigenetic clocks-the DNA methylation age (DNAmAge) and DNAm PhenoAge-and the FI are associated with the need for regular care in up to 604 individuals (aged 48-94 years) participating in the Swedish Adoption/Twin Study of Aging. Need for regular care was defined as receiving formal or informal help in daily routines at least once per week. Logistic regression adjusted for age, sex and education was used in the analysis. The predictive accuracies, assessed as the area under the curve (AUC) for the significant biological age measures were further compared to the accuracies of the limitations in activities of daily living (ADL) and instrumental ADL (IADL). Neither LTL nor the epigenetic clocks were associated with the need for care, whereas the FI was; odds ratio for 10% increase in FI 3.54 (95% confidence interval 2.32-5.41). The FI also demonstrated higher predictive accuracy than the ADL score (FI AUC 0.80 vs. ADL score AUC 0.62; p < 0.001 for equality of the AUCs), whereas the difference between FI AUC (0.80) and IADL score AUC (0.75) was not significant (p = 0.238). The FI might thus be a useful marker for the need for care.