Kidney Function Measures and Mortality: A Mendelian Randomization Study.

RATIONALE & OBJECTIVE: Individuals with a low estimated glomerular filtration rate (eGFR) are at a high risk of death. However, the causes underpinning this association are largely uncertain. This study aimed to assess the causal relationship of low eGFR with all-cause and cause-specific mortality. STUDY DESIGN: Retrospective cohort study incorporating Mendelian randomization (MR). SETTING & PARTICIPANTS: Individual-level data from 436,214 White participants (54.3% female; aged 56.8±8.0 years) included in the UK Biobank. EXPOSURES: eGFR estimated using cystatin C (eGFRcyst). OUTCOMES: The outcomes of interest included all-cause mortality, cardiovascular mortality, cancer mortality, infection mortality, and other-cause mortality. ANALYTICAL APPROACH: Cox proportional hazards analysis for the conventional observational analyses; linear and nonlinear MR analyses implemented using genetic allele scores as instrumental variables representing kidney function to estimate the effect of kidney function on the survival outcomes. RESULTS: During a median follow-up of 12.1 years, there were 30,489 deaths, 6,098 of which were attributed to cardiovascular events, 15,538 to cancer, 1,516 to infection, and 7,227 to other events. In the conventional observational analysis, eGFRcyst exhibited a nonlinear association with all the outcomes. MR analysis suggested that a genetically predicted lower eGFRcyst was linearly associated with a higher rate of cardiovascular mortality (HR, 1.43; 95% CI, 1.18-1.75) across the entire measurement range (every 10-mL/min/1.73m2 decrement). Nonetheless, no causal associations between eGFRcyst and all-cause mortality (HR, 1.07; 95% CI, 0.98-1.17) or any types of noncardiovascular mortality were detected. LIMITATIONS: Potential misclassification of the actual cause of death, a nonrepresentative sample, and potential error in the interpretation of the magnitude of associations generated in MR analyses. CONCLUSIONS: These findings suggest a potential causal association between low eGFR and cardiovascular mortality in the general population, but no causal relationship with all-cause mortality or noncardiovascular mortality was observed. Further studies in other populations are warranted to confirm these findings. PLAIN-LANGUAGE SUMMARY: This study investigated the existence of a causal relationship between lower kidney function and death of different causes. Using data from 436,214 people in the United Kingdom, we applied conventional statistical analyses and those incorporating genetic data to implement Mendelian randomization, an approach that estimates causal associations. The observational analysis showed a nonlinear association between kidney function and various types of mortality outcomes. However, Mendelian randomization analysis suggested a linear increase in the risk of cardiovascular mortality with lower kidney function, but no causal link between the level of kidney function and all-cause or noncardiovascular mortality was identified. Managing kidney health may help reduce cardiovascular mortality, but caution is needed in interpreting the magnitudes of these results. Further validation in other populations and in those with advanced kidney failure is needed.

Clinical biomarker-based biological ageing and future risk of neurological disorders in the UK Biobank.

BACKGROUND: Many common neurological disorders are associated with advancing chronological age, but their association with biological age (BA) remains poorly understood. METHODS: We studied 325 870 participants in the UK Biobank without a diagnosed neurological condition at baseline and generated three previously-described measures of BA based on 18 routinely measured clinical biomarkers (PhenoAge, Klemera-Doubal method age (KDMAge), homeostatic dysregulation age). Using survival models, we assessed the effect of advanced BA on incident neurological diagnoses, including all-cause and cause-specific dementia, ischaemic stroke, Parkinson's disease and motor neuron disease. RESULTS: During a mean follow-up of 9.0 years, there were 1397 incident cases of dementia and 2515 of ischaemic stroke, with smaller case numbers of other diagnoses. The strongest associations with a 1 SD in BA residual were seen for all-cause dementia (KDMAge HR=1.19, 95% CI=1.11 to 1.26), vascular dementia (1.41, 1.25 to 1.60) and ischaemic stroke (1.39, 1.34 to 1.46). Weaker associations were seen for Alzheimer's disease and motor neuron disease, while, in contrast, HRs for Parkinson's disease tended to be <1. Results were largely consistent after adjustment for disease-specific covariates including common cardiometabolic risk factors. CONCLUSIONS: Advanced BA calculated from routine clinical biomarker results increases the risk of subsequent neurological diagnoses including all-cause dementia and ischaemic stroke.

Associations between Sleep Disorders and Impulsive-Compulsive Behaviors in Parkinson's Disease: A Prospective Cohort Study.

OBJECTIVE: To examine the associations of excessive daytime sleepiness (EDS) and probable rapid eye movement sleep behavior disorder (pRBD), respectively, with impulsive-compulsive behaviors (ICB) over a 5-year follow-up in patients with early Parkinson's disease (PD). METHODS: The Parkinson's Progression Markers Initiative is a multicenter cohort study based on an ongoing and open-ended registry. Longitudinal associations of sleep disorders with ICB over 5-year follow-up visits were estimated using generalized linear mixed-effects models among PD participants. RESULTS: A total of 825 PD participants were enrolled at baseline. The study sample had a median baseline age of 63.1 (interquartile range [IQR]: 55.6-69.3) years and comprised 496 (61.5%) men. Among them, 201 (24.9%) had ICB at baseline. In the generalized mixed-effects models, EDS (odds ratio [OR] =1.09, 95% confidence interval [CI] 1.05, 1.12) and RBD (OR=1.07, 95% CI 1.03, 1.12) were substantially associated with higher odds of developing ICB over time in PD patients, after multivariate adjustment including age, gender, family history, GDS score, STAI-Y score, MDS-UPDRS part III score, LEDD, and disease duration. Consistent results were observed when stratifying by age at baseline, gender, and PD family history. CONCLUSIONS: The study findings suggest a longitudinal association between EDS and pRBD with an increased risk of developing ICB in patients with Parkinson's disease. The findings emphasize the significance of evaluating and addressing sleep disorders in PD patients as a potential approach to managing ICB.

Combining Mendelian randomization with the sibling comparison design.

Mendelian randomization (MR) is a popular epidemiologic study design that uses genetic variants as instrumental variables (IVs) to estimate causal effects, while accounting for unmeasured confounding. The validity of the MR design hinges on certain IV assumptions, which may sometimes be violated due to dynastic effects, population stratification, or assortative mating. Since these mechanisms act through parental factors it was recently suggested that the bias resulting from violations of the IV assumptions can be reduced by combing the MR design with the sibling comparison design, which implicitly controls for all factors that are constant within families. In this article, we provide a formal discussion of this combined MR-sibling design. We derive conditions under which the MR-sibling design is unbiased, and we relate these to the corresponding conditions for the standard MR and sibling comparison designs. We proceed by considering scenarios where all three designs are biased to some extent, and discuss under which conditions the MR-sibling design can be expected to have less bias than the other two designs. We finally illustrate the theoretical results and conclusions with an application to real data, in a study of low-density lipoprotein and diastolic blood pressure using data from the Swedish Twin Registry.

Advanced biological ageing predicts future risk for neurological diagnoses and clinical examination findings.

Age is a dominant risk factor for some of the most common neurological diseases. Biological ageing encompasses interindividual variation in the rate of ageing and can be calculated from clinical biomarkers or DNA methylation data amongst other approaches. Here, we tested the hypothesis that a biological age greater than one's chronological age affects the risk of future neurological diagnosis and the development of abnormal signs on clinical examination. We analysed data from the Swedish Adoption/Twin Study of Aging (SATSA): a cohort with 3175 assessments of 802 individuals followed-up over several decades. Six measures of biological ageing were generated: two physiological ages (created from bedside clinical measurements and standard blood tests) and four blood methylation age measures. Their effects on future stroke, dementia or Parkinson's disease diagnosis, or development of abnormal clinical signs, were determined using survival analysis, with and without stratification by twin pairs. Older physiological ages were associated with ischaemic stroke risk; for example one standard deviation advancement in baseline PhenoAgePhys or KDMAgePhys residual increased future ischaemic stroke risk by 29.2% [hazard ratio (HR): 1.29, 95% confidence interval (CI) 1.06-1.58, P = 0.012] and 42.9% (HR 1.43, CI 1.18-1.73, P = 3.1 × 10-4), respectively. In contrast, older methylation ages were more predictive of future dementia risk, which was increased by 29.7% (HR 1.30, CI 1.07-1.57, P = 0.007) per standard deviation advancement in HorvathAgeMeth. Older physiological ages were also positively associated with future development of abnormal patellar or pupillary reflexes, and the loss of normal gait. Measures of biological ageing can predict clinically relevant pathology of the nervous system independent of chronological age. This may help to explain variability in disease risk between individuals of the same age and strengthens the case for trials of geroprotective interventions for people with neurological disorders.

Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility.

BACKGROUND: Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance. METHODS: In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI). FINDINGS: The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92). INTERPRETATION: The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.

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.

Occupational inhalable agents constitute major risk factors for rheumatoid arthritis, particularly in the context of genetic predisposition and smoking.

OBJECTIVES: To assess the effects of occupational inhalable exposures on rheumatoid arthritis (RA) development and their interactions with smoking and RA-risk genes, stratifying by presence of anticitrullinated protein antibodies (ACPA). METHODS: Data came from the Swedish Epidemiological Investigation of RA, consisting of 4033 incident RA cases and 6485 matched controls. Occupational histories were retrieved, combining with a Swedish national job-exposure matrix, to estimate exposure to 32 inhalable agents. Genetic data were used to define Genetic Risk Score (GRS) or carrying any copy of human leucocyte antigen class II shared epitope (HLA-SE) alleles. Associations were identified with unconditional logistical regression models. Attributable proportion due to interaction was estimated to evaluate presence of interaction. RESULTS: Exposure to any occupational inhalable agents was associated with increased risk for ACPA-positive RA (OR 1.25, 95% CI 1.12 to 1.38). The risk increased as number of exposed agents increased (Ptrend<0.001) or duration of exposure elongated (Ptrend<0.001). When jointly considering exposure to any occupational inhalable agents, smoking and high GRS, a markedly elevated risk for ACPA-positive RA was observed among the triple-exposed group compared with those not exposed to any (OR 18.22, 95% CI 11.77 to 28.19). Significant interactions were found between occupational inhalable agents and smoking/genetic factors (high GRS or HLA-SE) in ACPA-positive RA. CONCLUSIONS: Occupational inhalable agents could act as important environmental triggers in RA development and interact with smoking and RA-risk genes leading to excessive risk for ACPA-positive RA. Future studies are warranted to assess preventive strategies aimed at reducing occupational hazards and smoking, especially among those who are genetically vulnerable.

Genetic heterogeneity and subtypes of major depression.

Major depression (MD) is a heterogeneous disorder; however, the extent to which genetic factors distinguish MD patient subgroups (genetic heterogeneity) remains uncertain. This study sought evidence for genetic heterogeneity in MD. Using UK Biobank cohort, the authors defined 16 MD subtypes within eight comparison groups (vegetative symptoms, symptom severity, comorbid anxiety disorder, age at onset, recurrence, suicidality, impairment, and postpartum depression; N ~ 3000-47000). To compare genetic component of these subtypes, subtype-specific genome-wide association studies were performed to estimate SNP-heritability, and genetic correlations within subtype comparison and with other related disorders/traits. The findings indicated that MD subtypes were divergent in their SNP-heritability, and genetic correlations both within subtype comparisons and with other related disorders/traits. Three subtype comparisons (vegetative symptoms, age at onset, and impairment) showed significant differences in SNP-heritability; while genetic correlations within subtype comparisons ranged from 0.55 to 0.86, suggesting genetic profiles are only partially shared among MD subtypes. Furthermore, subtypes that are more clinically challenging, e.g., early-onset, recurrent, suicidal, more severely impaired, had stronger genetic correlations with other psychiatric disorders. MD with atypical-like features showed a positive genetic correlation (+0.40) with BMI while a negative correlation (-0.09) was found in those without atypical-like features. Novel genomic loci with subtype-specific effects were identified. These results provide the most comprehensive evidence to date for genetic heterogeneity within MD, and suggest that the phenotypic complexity of MD can be effectively reduced by studying the subtypes which share partially distinct etiologies.

Repurposing antidiabetic drugs for rheumatoid arthritis: results from a two-sample Mendelian randomization study.

Despite increasing therapeutic options to treat rheumatoid arthritis (RA), many patients fail to reach treatment targets. The use of antidiabetic drugs like thiazolidinediones has been associated with lower RA risk. We aimed to explore the repurposing potential of antidiabetic drugs in RA prevention by assessing associations between genetic variation in antidiabetic drug target genes and RA using Mendelian randomization (MR). A two-sample MR design was used to estimate the association between the antidiabetic drug and RA risk using summary statistics from genome-wide association studies (GWAS). We selected independent genetic variants from the gene(s) that encode the target protein(s) of the investigated antidiabetic drug as instruments. We extracted the associations of instruments with blood glucose concentration and RA from the UK Biobank and a GWAS meta-analysis of clinically diagnosed RA, respectively. The effect of genetic variation in the drug target(s) on RA risk was estimated by the Wald ratio test or inverse-variance weighted method. Insulin and its analogues, thiazolidinediones, and sulfonylureas had valid genetic instruments (n = 1, 1, and 2, respectively). Genetic variation in thiazolidinedione target (gene: PPARG) was inversely associated with RA risk (odds ratio [OR] 0.38 per 0.1mmol/L glucose lowering, 95% confidence interval [CI] 0.20-0.73). Corresponding ORs (95%CIs) were 0.83 (0.44-1.55) for genetic variation in the targets of insulin and its analogues (gene: INSR), and 1.12 (0.83, 1.49) 1.25 (0.78-2.00) for genetic variation in the sulfonylurea targets (gene: ABCC8 and KCNJ11). In conclusion, genetic variation in the thiazolidinedione target is associated with a lower RA risk. The underlying mechanisms warrant further exploration.

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.

Assessment of the bi-directional relationship between blood mitochondrial DNA copy number and type 2 diabetes mellitus: a multivariable-adjusted regression and Mendelian randomisation study.

AIMS/HYPOTHESIS: Mitochondrial dysfunction, which can be approximated by blood mitochondrial DNA copy number (mtDNA-CN), has been implicated in the pathogenesis of type 2 diabetes mellitus. Thus far, however, insights from prospective cohort studies and Mendelian randomisation (MR) analyses on this relationship are limited. We assessed the association between blood mtDNA-CN and incident type 2 diabetes using multivariable-adjusted regression analyses, and the associations between blood mtDNA-CN and type 2 diabetes and BMI using bi-directional MR. METHODS: Multivariable-adjusted Cox proportional hazard models were used to estimate the association between blood mtDNA-CN and incident type 2 diabetes in 285,967 unrelated European individuals from UK Biobank free of type 2 diabetes at baseline. Additionally, a cross-sectional analysis was performed to investigate the association between blood mtDNA-CN and BMI. We also assessed the potentially causal relationship between blood mtDNA-CN and type 2 diabetes (N=898,130 from DIAGRAM, N=215,654 from FinnGen) and BMI (N=681,275 from GIANT) using bi-directional two-sample MR. RESULTS: During a median follow-up of 11.87 years, 15,111 participants developed type 2 diabetes. Participants with a higher level of blood mtDNA-CN are at lower risk of developing type 2 diabetes (HR 0.90 [95% CI 0.89, 0.92]). After additional adjustment for BMI and other confounders, these results attenuated moderately and remained present. The multivariable-adjusted cross-sectional analyses showed that higher blood mtDNA-CN was associated with lower BMI (-0.12 [95% CI -0.14, -0.10]) kg/m2. In the bi-directional MR analyses, we found no evidence for causal associations between blood mtDNA-CN and type 2 diabetes, and blood mtDNA-CN and BMI in either direction. CONCLUSIONS/INTERPRETATION: The results from the present study indicate that the observed association between low blood mtDNA-CN and higher risk of type 2 diabetes is likely not causal.

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.

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.

A genome-wide association study of IgM antibody against phosphorylcholine: shared genetics and phenotypic relationship to chronic lymphocytic leukemia.

Phosphorylcholine (PC) is an epitope on oxidized low-density lipoprotein (oxLDL), apoptotic cells and several pathogens like Streptococcus pneumoniae. Immunoglobulin M against PC (IgM anti-PC) has the ability to inhibit uptake of oxLDL by macrophages and increase clearance of apoptotic cells. From our genome-wide association studies (GWASs) in four European-ancestry cohorts, six single nucleotide polymorphisms (SNPs) in 11q24.1 were discovered (in 3002 individuals) and replicated (in 646 individuals) to be associated with serum level of IgM anti-PC (the leading SNP rs35923643-G, combined ß = 0.19, 95% confidence interval 0.13-0.24, P = 4.3 × 10-11). The haplotype tagged by rs35923643-G (or its proxy SNP rs735665-A) is also known as the top risk allele for chronic lymphocytic leukemia (CLL), and a main increasing allele for general IgM. By using summary GWAS results of IgM anti-PC and CLL in the polygenic risk score (PRS) analysis, PRS on the basis of IgM anti-PC risk alleles positively associated with CLL risk (explained 0.6% of CLL variance, P = 1.2 × 10-15). Functional prediction suggested that rs35923643-G might impede the binding of Runt-related transcription factor 3, a tumor suppressor playing a central role in the immune regulation of cancers. Contrary to the expectations from the shared genetics between IgM anti-PC and CLL, an inverse relationship at the phenotypic level was found in a nested case-control study (30 CLL cases with 90 age- and sex-matched controls), potentially reflecting reverse causation. The suggested function of the top variant as well as the phenotypic association between IgM anti-PC and CLL risk needs replication and motivates further studies.