Linking Brain Age Gap to Mental and Physical Health in the Berlin Aging Study II.

From a biological perspective, humans differ in the speed they age, and this may manifest in both mental and physical health disparities. The discrepancy between an individual's biological and chronological age of the brain ("brain age gap") can be assessed by applying machine learning techniques to Magnetic Resonance Imaging (MRI) data. Here, we examined the links between brain age gap and a broad range of cognitive, affective, socioeconomic, lifestyle, and physical health variables in up to 335 adults of the Berlin Aging Study II. Brain age gap was assessed using a validated prediction model that we previously trained on MRI scans of 32,634 UK Biobank individuals. Our statistical analyses revealed overall stronger evidence for a link between higher brain age gap and less favorable health characteristics than expected under the null hypothesis of no effect, with 80% of the tested associations showing hypothesis-consistent effect directions and 23% reaching nominal significance. The most compelling support was observed for a cluster covering both cognitive performance variables (episodic memory, working memory, fluid intelligence, digit symbol substitution test) and socioeconomic variables (years of education and household income). Furthermore, we observed higher brain age gap to be associated with heavy episodic drinking, higher blood pressure, and higher blood glucose. In sum, our results point toward multifaceted links between brain age gap and human health. Understanding differences in biological brain aging may therefore have broad implications for future informed interventions to preserve mental and physical health in old age.

Association of sex-specific differences in lipoprotein(a) concentrations with cardiovascular mortality in individuals with type 2 diabetes mellitus.

BACKGROUND: Compared to individuals without type 2 diabetes mellitus, the relative increase in cardiovascular mortality is much higher in women than in men in individuals with type 2 diabetes mellitus. METHODS: We evaluated data from 7443 individuals (3792 women, 50.9%), aged 20 to 81 years, from two independent population-based investigations, SHIP-0 and MONICA/KORA S3. We analyzed the longitudinal sex-specific associations of lipoprotein(a) with cardiovascular mortality in individuals with and without type 2 diabetes mellitus using Cox regression. RESULTS: During a median follow-up of 20.5 years (136,802 person-years), 657 participants (404 men and 253 women) died of cardiovascular causes. Among individuals without type 2 diabetes mellitus, men had a significantly higher risk for cardiovascular mortality compared to women in unadjusted model and after adjustment. On the other hand, in participants with type 2 diabetes mellitus, the risk for cardiovascular mortality was not different between men and women in the unadjusted model and after adjustment for age, body mass index, low-density lipoprotein-cholesterol, fasting status and study sample (SHIP-0, MONICA/KORA S3). Further adjustment for lipoprotein(a) concentrations had no impact on the hazard ratio (HR) for cardiovascular mortality comparing men versus women in individuals without type 2 diabetes mellitus [HR: 1.94; 95% confidence interval (CI) 1.63 to 2.32; p < 0.001]. In individuals with type 2 diabetes mellitus, however, further adjustment for lipoprotein(a) led to an increased risk for cardiovascular mortality in men and a decreased risk in women resulting in a statistically significant difference between men and women (HR: 1.53; 95% CI 1.04 to 2.24; p = 0.029). CONCLUSIONS: Women are described to have a stronger relative increase in cardiovascular mortality than men when comparing individuals with and without type 2 diabetes mellitus. Higher lipoprotein(a) concentrations in women with type 2 diabetes mellitus than in men with type 2 diabetes mellitus might partially explain this finding.

Cohort differences in adult-life trajectories of internal and external control beliefs: A tale of more and better maintained internal control and fewer external constraints.

Life Span theory posits that sociohistorical contexts shape individual development. In line with this proposition, cohort differences favoring later-born cohorts have been widely documented for cognition and health. However, little is known about historical change in how key resources of psychosocial functioning such as control beliefs develop in old age. We pooled data from 3 independent samples: Berlin Aging Study (6 waves, N = 414); Interdisciplinary Longitudinal Study of Adult Development (4 waves, N = 925); and Berlin Aging Study II (4 waves, N = 1,111) to construct overlapping multiyear longitudinal data from ages 61 through 85 years for cohorts born 1905 to 1953 and examine historical changes in within-person trajectories of internal and external control beliefs. Results revealed that earlier-born cohorts exhibit age-related declines in internal control beliefs regarding both desirable and undesirable outcomes, whereas later-born cohorts perceive higher internal control and maintain this advantage into old age. Earlier-born cohorts also experience steep age-related increases in external control beliefs regarding both powerful others and chance, whereas later-born cohorts perceive lower external control and were stable across old age. Education and gender disparities in control beliefs narrowed over historical time. Sociodemographic, physical health, cognitive, and social factors explained some of the differences in control beliefs, and accounted for sizable portions of cohort effects. Our results indicate that current generations of older adults perceive more and better maintained internal control and fewer external constraints. We discuss potential underlying mechanisms and consider conceptual and societal implications of our findings. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Different treatment forms of type II diabetes and the risk of dementia in German health claims data.

AIMS: The association between type II diabetes (T2D) and increased all-cause dementia risk is well established. However, to date, there is no definite proof that a specific therapy for diabetes can halt a progress of cognitive decline. Therefore, we analyzed a large longitudinal random sample of German health claims data to focus on associations between T2D and dementia and to elucidate the role of different treatment forms of T2D on the risk for dementia. METHODS: We used a longitudinal random sample (n = 250,000) of claims data of the largest public sickness fund in Germany, the Allgemeine Ortskrankenkasse (AOK). Dementia was defined as ICD-10 codes G31.0, G31.82, G23.1, F00, F01, F02, F03, and F05, and T2D was defined as E11-E14. We performed Cox proportional hazard models to explore the transition into dementia and to calculate the relative risk of dementia dependent on T2D and different T2D treatment forms. RESULTS: All models were adjusted for sex, age, and each patient's history of depression, renal insufficiency, and cardiovascular comorbidities. Non-pharmacologic-treated diabetics showed a 23% increased dementia risk (p < 0.001) and oral ADM-treated diabetics showed a 16% increased risk (p < 0.001). Insulin-dependent diabetics is still the highest dementia risk (40%; p < 0.001) and obesity additionally attenuated this risk (75%; p < 0.001) increased risk. CONCLUSIONS: We found that diabetes is an independent risk factor for all-cause dementia. An increased risk for dementia in insulin-dependent and obese subjects with diabetes was evident. Longitudinal studies on the effect of different forms of therapy and weight reduction are needed to verify the results of this study.

Implementation of integrated geriatric care at a German hospital: a case study to understand when and why beneficial outcomes can be achieved.

BACKGROUND: Many health systems have implemented integrated care as an alternative approach to health care delivery that is more appropriate for patients with complex, long-term needs. The objective of this article was to analyse the implementation of integrated care at a German geriatric hospital and explore whether the use of a "context-mechanisms-outcomes"-based model provides insights into when and why beneficial outcomes can be achieved. METHODS: We conducted 15 semi-structured interviews with health professionals employed at the hospital. The data were qualitatively analysed using a "context-mechanisms-outcomes"-based model. Specifically, mechanisms were defined as the different components of the integrated care intervention and categorised according to Wagner's Chronic Care Model (CCM). Context was understood as the setting in which the mechanisms are brought into practice and described by the barriers and facilitators encountered in the implementation process. These were categorised according to the six levels of Grol and Wensing's Implementation Model (IM): innovation, individual professional, patient, social context, organisational context and economic and political context. Outcomes were defined as the effects triggered by mechanisms and context, and categorised according to the six dimensions of quality of care as defined by the World Health Organization, namely effectiveness, efficiency, accessibility, patient-centeredness, equity and safety. RESULTS: The integrated care intervention consisted of three main components: a specific reimbursement system ("early complex geriatric rehabilitation"), multidisciplinary cooperation, and comprehensive geriatric assessments. The inflexibility of the reimbursement system regarding the obligatory number of treatment sessions contributed to over-, under- and misuse of services. Multidisciplinary cooperation was impeded by a high workload, which contributed to waste in workflows. The comprehensive geriatric assessments were complemented with information provided by family members, which contributed to decreased likelihood of adverse events. CONCLUSIONS: We recommend an increased focus on trying to understand how intervention components interact with context factors and, combined, lead to positive and/or negative outcomes.

Familial hypercholesterolaemia in children and adolescents: gaining decades of life by optimizing detection and treatment.

Familial hypercholesterolaemia (FH) is a common genetic cause of premature coronary heart disease (CHD). Globally, one baby is born with FH every minute. If diagnosed and treated early in childhood, individuals with FH can have normal life expectancy. This consensus paper aims to improve awareness of the need for early detection and management of FH children. Familial hypercholesterolaemia is diagnosed either on phenotypic criteria, i.e. an elevated low-density lipoprotein cholesterol (LDL-C) level plus a family history of elevated LDL-C, premature coronary artery disease and/or genetic diagnosis, or positive genetic testing. Childhood is the optimal period for discrimination between FH and non-FH using LDL-C screening. An LDL-C ≥5 mmol/L (190 mg/dL), or an LDL-C ≥4 mmol/L (160 mg/dL) with family history of premature CHD and/or high baseline cholesterol in one parent, make the phenotypic diagnosis. If a parent has a genetic defect, the LDL-C cut-off for the child is ≥3.5 mmol/L (130 mg/dL). We recommend cascade screening of families using a combined phenotypic and genotypic strategy. In children, testing is recommended from age 5 years, or earlier if homozygous FH is suspected. A healthy lifestyle and statin treatment (from age 8 to 10 years) are the cornerstones of management of heterozygous FH. Target LDL-C is <3.5 mmol/L (130 mg/dL) if >10 years, or ideally 50% reduction from baseline if 8-10 years, especially with very high LDL-C, elevated lipoprotein(a), a family history of premature CHD or other cardiovascular risk factors, balanced against the long-term risk of treatment side effects. Identifying FH early and optimally lowering LDL-C over the lifespan reduces cumulative LDL-C burden and offers health and socioeconomic benefits. To drive policy change for timely detection and management, we call for further studies in the young. Increased awareness, early identification, and optimal treatment from childhood are critical to adding decades of healthy life for children and adolescents with FH.

Assessment of microRNA-related SNP effects in the 3' untranslated region of the IL22RA2 risk locus in multiple sclerosis.

Recent large-scale association studies have identified over 100 MS risk loci. One of these MS risk variants is single-nucleotide polymorphism (SNP) rs17066096, located ~14 kb downstream of IL22RA2. IL22RA2 represents a compelling MS candidate gene due to the role of IL-22 in autoimmunity; however, rs17066096 does not map into any known functional element. We assessed whether rs17066096 or a nearby proxy SNP may exert pathogenic effects by affecting microRNA-to-mRNA binding and thus IL22RA2 expression using comprehensive in silico predictions, in vitro reporter assays, and genotyping experiments in 6,722 individuals. In silico screening identified two predicted microRNA binding sites in the 3'UTR of IL22RA2 (for hsa-miR-2278 and hsa-miR-411-5p) encompassing a SNP (rs28366) in moderate linkage disequilibrium with rs17066096 (r (2) = 0.4). The binding of both microRNAs to the IL22RA2 3'UTR was confirmed in vitro, but their binding affinities were not significantly affected by rs28366. Association analyses revealed significant association of rs17066096 and MS risk in our independent German dataset (odds ratio = 1.15, P = 3.48 × 10(-4)), but did not indicate rs28366 to be the cause of this signal. While our study provides independent validation of the association between rs17066096 and MS risk, this signal does not appear to be caused by sequence variants affecting microRNA function.

Cohort profile: The Berlin Aging Study II (BASE-II).

Similar to other industrialized countries, Germany's population is ageing. Whereas some people enjoy good physical and cognitive health into old age, others suffer from a multitude of age-related disorders and impairments which reduce life expectancy and affect quality of life. To identify and characterize the factors associated with 'healthy' vs. 'unhealthy' ageing, we have launched the Berlin Aging Study II (BASE-II), a multidisciplinary and multi-institutional project that ascertains a large number of ageing-related variables from a wide range of different functional domains. Phenotypic assessments include factors related to geriatrics and internal medicine, immunology, genetics, psychology, sociology and economics. Baseline recruitment of the BASE-II cohort was recently completed and has led to the sampling of 1600 older adults (age range 60-80 years), as well as 600 younger adults (20-35 years) serving as the basic population for in-depth analyses. BASE-II data are linked to the German Socio-Economic Panel Study (SOEP), a long-running panel survey representative of the German population, to estimate sample selectivity. A major goal of BASE-II is to facilitate collaboration with other research groups by freely sharing relevant phenotypic and genotypic data with qualified outside investigators.

Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups.

BACKGROUND: Hospital in-patient falls constitute a prominent problem in terms of costs and consequences. Geriatric institutions are most often affected, and common screening tools cannot predict in-patient falls consistently. Our objectives are to derive comprehensible fall risk classification models from a large data set of geriatric in-patients' assessment data and to evaluate their predictive performance (aim#1), and to identify high-risk subgroups from the data (aim#2). METHODS: A data set of n = 5,176 single in-patient episodes covering 1.5 years of admissions to a geriatric hospital were extracted from the hospital's data base and matched with fall incident reports (n = 493). A classification tree model was induced using the C4.5 algorithm as well as a logistic regression model, and their predictive performance was evaluated. Furthermore, high-risk subgroups were identified from extracted classification rules with a support of more than 100 instances. RESULTS: The classification tree model showed an overall classification accuracy of 66%, with a sensitivity of 55.4%, a specificity of 67.1%, positive and negative predictive values of 15% resp. 93.5%. Five high-risk groups were identified, defined by high age, low Barthel index, cognitive impairment, multi-medication and co-morbidity. CONCLUSIONS: Our results show that a little more than half of the fallers may be identified correctly by our model, but the positive predictive value is too low to be applicable. Non-fallers, on the other hand, may be sorted out with the model quite well. The high-risk subgroups and the risk factors identified (age, low ADL score, cognitive impairment, institutionalization, polypharmacy and co-morbidity) reflect domain knowledge and may be used to screen certain subgroups of patients with a high risk of falling. Classification models derived from a large data set using data mining methods can compete with current dedicated fall risk screening tools, yet lack diagnostic precision. High-risk subgroups may be identified automatically from existing geriatric assessment data, especially when combined with domain knowledge in a hybrid classification model. Further work is necessary to validate our approach in a controlled prospective setting.