No abstract

Lifestyle may be one source of unexplained variance in the great interindividual variability of the brain in age-related structural differences. While physical and social activity may protect against structural decline, other lifestyle behaviors may be accelerating factors. We examined whether riskier lifestyle correlates with accelerated brain aging using the BrainAGE score in 622 older adults from the 1000BRAINS cohort. Lifestyle was measured using a combined lifestyle risk score, composed of risk (smoking, alcohol intake) and protective variables (social integration and physical activity). We estimated individual BrainAGE from T1-weighted MRI data indicating accelerated brain atrophy by higher values. Then, the effect of combined lifestyle risk and individual lifestyle variables was regressed against BrainAGE. One unit increase in combined lifestyle risk predicted 5.04 months of additional BrainAGE. This prediction was driven by smoking (0.6 additional months of BrainAGE per pack-year) and physical activity (0.55 less months in BrainAGE per metabolic equivalent). Stratification by sex revealed a stronger association between physical activity and BrainAGE in males than females. Overall, our observations may be helpful with regard to lifestyle-related tailored prevention measures that slow changes in brain structure in older adults.

Lifestyle contributes to inter-individual variability in brain aging, but previous studies focused on the effects of single lifestyle variables. Here, we studied the combined and individual contributions of four lifestyle variables - alcohol consumption, smoking, physical activity, and social integration - to brain structure and functional connectivity in a population-based cohort of 549 older adults. A combined lifestyle risk score was associated with decreased gyrification in left premotor and right prefrontal cortex, and higher functional connectivity to sensorimotor and prefrontal cortex. While structural differences were driven by alcohol consumption, physical activity, and social integration, higher functional connectivity was driven by smoking. Results suggest that combining differentially contributing lifestyle variables may be more than the sum of its parts. Associations generally were neither altered by adjustment for genetic risk, nor by depressive symptomatology or education, underlining the relevance of daily habits for brain health.

Objective: While Hungary is often reported to have the highest incidence and mortality rates of lung cancer, until 2018 no nationwide epidemiology study was conducted to confirm these trends. The objective of this study was to estimate the occurrence of lung cancer in Hungary based on a retrospective review of the National Health Insurance Fund (NHIF) database.Methods: Our retrospective, longitudinal study included patients aged ≥20 years who were diagnosed with lung cancer (ICD-10 C34) between 1 Jan 2011 and 31 Dec 2016. Age-standardized incidence and mortality rates were calculated using both the 1976 and 2013 European Standard Populations (ESP).Results: Between 2011 and 2016, 6,996 – 7,158 new lung cancer cases were recorded in the NHIF database annually, and 6,045 – 6,465 all-cause deaths occurred per year. Age-adjusted incidence rates were 115.7–101.6/100,000 person-years among men (ESP 1976: 84.7–72.6), showing a mean annual change of − 2.26% (p = 0.008). Incidence rates among women increased from 48.3 to 50.3/100,000 person-years (ESP 1976: 36.9–38.0), corresponding to a mean annual change of 1.23% (p = 0.028). Age-standardized mortality rates varied between 103.8 and 97.2/100,000 person-years (ESP 1976: 72.8–69.7) in men and between 38.3 and 42.7/100,000 person-years (ESP 1976: 27.8–29.3) in women.Conclusion: Age-standardized incidence and mortality rates of lung cancer in Hungary were found to be high compared to Western-European countries, but lower than those reported by previous publications. The incidence of lung cancer decreased in men, while there was an increase in incidence and mortality among female lung cancer patients.

Lung cancer is the leading cause of cancer related mortality all over the world, and a number of developments have indicated future clinical benefit recently. The development of molecular pathology methods has become increasingly important in the prediction of chemotherapy sensitivity and mutation analysis to identify driver mutations as important targets of new therapeutic agents. The most significant changes in the treatment of NSCLC revealed in new pathologic classification and in the introduction of molecularly targeted therapies, which include monoclonal antibodies and small molecule tyrosine kinase inhibitors. The side effects of these agents are generally better tolerated than those of conventional chemotherapy and show higher efficacy. The most important factor follows: histology subtypes, gene mutation status, patients' selection, drug toxicities and occurence of drug resistance. In the advanced disease, the hope of cure is less than 3%, but improvements in survival have been clearly achieved. Some years ago the median lung cancer survival rate was 10-12 months, now in case of available specific molecular targets, a significant increase in median survival rates to 24-36 months has been achieved. These agents give an opportunity to provide a new standard of care. Therefore testing EGFR mutations and ALK rearrangements in patients with advanced lung adenocarcinoma should be incorporated into routine clinical practice. This review focuses on the rationale for targeted agents and new treatment possibilities in case of advanced lung adenocarcinoma.

No abstract

Healthy aging is accompanied by heterogeneous decline of cognitive abilities among individuals, especially during senescence. The mechanisms of this variability are not understood, but have been associated with the reorganization of white matter fiber tracts and the functional co-activations of brain regions. Here, we built a causal inference framework to provide mechanistic insight into the link between structural connectivity and brain function, informed by brain imaging data and network modeling. By applying various degrees of interhemispheric degradation of structural connectivity, we were not only able to reproduce the age-related decline in interhemispheric functional communication and the associated dynamical flexibility, but we obtained an increase of global modulation of structural connectivity over the brain function during senescence. Notably, the increase in modulation between structural connectivity and brian function was higher in magnitude and steeper in its increase in older adults with poor cognitive performance. We independently validated the causal hypothesis of our framework via a Bayesian approach based on deep-learning. The current results might be the first mechanistic demonstration of dedifferentiation and scaffolding during aging leading to cognitive decline demonstrated in a large cohort.

Brain aging is highly variable and represents a challenge to delimit aging from disease processes. Moreover, genetic factors may influence both aging and disease. Here we focused on this issue and investigated effects of multiple genetic loci previously identified to be associated with late-onset Alzheimer’s disease (AD) on brain structure of older adults from a population sample. We calculated a genetic risk score (GRS) using genome-wide significant single-nucleotide polymorphisms from genome-wide association studies of AD and tested its effect on cortical thickness (CT). We observed a common pattern of cortical thinning (right inferior frontal, left posterior temporal, medial occipital cortex). To identify CT changes by specific biological processes, we subdivided the GRS effect according to AD-associated pathways and performed follow-up analyses. The common pattern from the main analysis was further differentiated by pathway-specific effects yielding a more bilateral pattern. Further findings were located in the superior parietal and mid/anterior cingulate regions representing 2 unique pathway-specific patterns. All patterns, except the superior parietal pattern, were influenced by apolipoprotein E. Our step-wise approach revealed atrophy patterns that partially resembled imaging findings in early stages of AD. Our study provides evidence that genetic burden for AD contributes to structural brain variability in normal aging.