Interactions between age, sex and visceral adipose tissue on brain ageing.

AIM: To examine the associations between visceral adipose tissue (VAT) and brain structural measures at midlife and explore how these associations may be affected by age, sex and cardiometabolic factors. METHODS: We used abdominal and brain magnetic resonance imaging data from a population-based cohort of people at midlife in the UK Biobank. Regression modelling was applied to study associations of VAT volume with total brain volume (TBV), grey matter volume (GMV), white matter volume, white matter hyperintensity volume (WMHV) and total hippocampal volume (THV), and whether these associations were altered by age, sex or cardiometabolic factors. RESULTS: Complete data were available for 17 377 participants (mean age 63 years, standard deviation = 12, 53% female). Greater VAT was associated with lower TBV, GMV and THV (P < .001). We found an interaction between VAT and sex on TBV (P < .001), such that the negative association of VAT with TBV was greater in men (ß = -2.89, 95% confidence interval [CI] -2.32 to -10.15) than in women (ß = -1.32, 95% CI -0.49 to -3.14), with similar findings for GMV. We also found an interaction between VAT and age (but not sex) on WMHV (P < .001). The addition of other cardiometabolic factors or measures of physical activity resulted in little change to the models. CONCLUSIONS: VAT volume is associated with poorer brain health in midlife and this relationship is greatest in men and those at younger ages.

Associations of Sex, Age, and Cardiometabolic Risk Profiles With Brain Structure and Cognition: A UK Biobank Latent Class Analysis.

BACKGROUND AND OBJECTIVES: It is unknown whether there are sex-related profiles of cardiometabolic health that contribute differently to age-related changes in brain health during midlife. We studied how latent classes of middle-aged individuals clustering by age, sex, menopause, and cardiometabolic health were associated with brain structure and cognitive performance. METHODS: Health, brain, and abdominal MRI data from the UK Biobank cohort (men and women aged >40 years in the United Kingdom) were used. We applied latent class analysis to identify groups of individuals based on age, sex, menopausal status, and cardiometabolic health. We examined associations of class membership with brain volumes (total brain volume [TBV], gray matter volume [GMV], white matter volume [WMV], hippocampal volume, and white matter hyperintensity volume) and cognitive performance. RESULTS: Data were available for 36,420 individuals (mean age 64.9 years, 48.5% women). Eight latent classes differing in age, sex, and cardiometabolic risk were identified. Class 1 (reference class) included individuals with the lowest probability of older age and cardiometabolic risk, and the healthiest levels of brain volumes and cognition. In those aged >60 years, but not in those aged 50-60 years, the negative associations of age with TBV, GMV, and WMV were greater in the class comprising healthier older women than classes comprising older men of varying cardiometabolic and vascular health. There were no age-class interactions for cognitive test performance. DISCUSSION: Latent class analysis detected groups of middle-aged individuals clustering by cardiometabolic health. The relationship of age with brain volumes varies by sex, menopausal status, and cardiometabolic health profile.

New Horizons-Cognitive Dysfunction Associated With Type 2 Diabetes.

The prevalence of type 2 diabetes (T2D) and cognitive dysfunction increases with age. As society ages, clinicians will be increasingly tasked with managing older people who have both T2D and cognitive dysfunction. T2D is associated with an increased risk of cognitive dysfunction and hence there is increasing interest in whether T2D is a causal factor in the pathogenesis of cognitive decline and dementia. Recent advances in the use of sensitive measures of in vivo brain dysfunction in life-course studies can help understand potential mechanistic pathways and also help guide recommendations for clinical practice. In this article we will describe new horizons in the understanding of cognitive dysfunction associated with T2D. Coming from a clinical perspective, we discuss potential mechanisms and pathways linking the 2 conditions and the contribution of multimodal neuroimaging and study designs to advancing understanding in the field. We also highlight the important issues on the horizon that will need addressing in clinical identification, management, and risk reduction for people with coexistent T2D and cognitive dysfunction.

Interactions Between Age, Sex, Menopause, and Brain Structure at Midlife: A UK Biobank Study.

OBJECTIVES: Age and female sex are risk factors for dementia, and menopause is associated with cognitive dysfunction. Previous work largely considered the effects of sex and menopause as being independent of age. We studied whether age interacts with sex or menopause in explaining imaging biomarkers of dementia during midlife. METHODS: In this cross-sectional study of UK Biobank participants with brain magnetic resonance imaging (MRI), we explored the interaction of age with sex or menopausal status in explaining total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), white matter hyperintensity volume (WMHV), regional cortical volume , and subcortical volume. RESULTS: Data were available for 1827 postmenopausal women, 230 pre/perimenopausal women and 2165 men (median age 63.3 years). There was a significant interaction between age and sex (P = .024) for TBV, where the inverse association age with TBV was steeper in women (ß = -5.35 mL/year) than in men (ß = -4.77 mL/year). Similar age-sex interactions were also observed for GMV and WMV. In women, there was a significant interaction between age and menopausal status (P = .007) where the inverse association of age with TBV was steeper in postmenopausal (ß = -5.89 mL/year) than in pre/perimenopausal women (ß = -1.61 mL/year). Similar age-menopause interactions were found in predicting lower GMV and higher WMHV. Differences in the direction of these age-sex and age-menopause interactions were found for regional cortical and subcortical brain volumes. CONCLUSION: Sex and menopause both interact with age during midlife in explaining MRI biomarkers of dementia. Further work is required to understand the mechanisms driving these interactions to develop strategies for delaying dementia.

Examination of risk scores to better predict hospital-related harms.

BACKGROUND: Many hospitals use predictive scores to identify a person's risk of inpatient falls, pressure injury and malnutrition despite evidence of limited predictive accuracy. AIM: To examine whether we could improve predictive accuracy by generating a score combining all components of currently used tools. METHODS: We performed a retrospective, cross-validation study in a single sub-acute (geriatrics and rehabilitation) hospital, extracting data regarding hospital risk scores, and incidence of falls, pressure injury and malnutrition from January 2014 to June 2016. The sample was randomly halved into training and testing data sets. For each harm outcome, model fit was examined using area under receiver operating characteristic curves (AUC) and proportions of people reclassified based on a combined score were calculated. Secondary analyses explored the predictive performance of individual question-responses. RESULTS: Data were available for 4487 admissions (median age 83.0 years). A total of 667 (15%) people had at least one fall, 499 (11%) had at least one pressure injury and 20 (0.4%) malnutrition. The currently used tools had, at best, moderate ability to predict risk of harm outcomes (AUC 0.56-0.73). Testing of the combined score models resulted in minimal change in AUC (<5.1%) and did not add value to risk category reclassification. Most of the predictive ability of the currently used tools relied on the performance of two individual question-responses. CONCLUSION: Combining scores or reducing to two-item question-responses did little to change predictive accuracy. This study highlights the limitations of hospital harm predictive scores and emphasises the importance of rigorous testing of predictive scores.

Cadaveric lobar lung transplantation: technical aspects.

BACKGROUND: The use of lobar transplantation and other size reduction techniques has allowed larger donor lungs to be utilized for smaller recipients who tend to have longer waiting times for transplantation. However, despite these advantages, the techniques have not been widely adopted. We outline the surgical and sizing issues associated with this technique. METHODS: A retrospective review of 23 consecutive patients who received lung transplantation with anatomic lobar reduction was performed, focusing on surgical technique and outcomes. RESULTS: All 23 patients received an anatomic lobar reduction of between 1 and 3 lobes. Survival analysis showed no difference between the lobar reduction cohort and the other historically comparable lung transplant patients from our institution (p=0.115). Percent predicted forced vital capacity and forced expiratory volume in 1 second at 3 months correlated with transplanted donor to recipient total lung capacity ratio, confirming the importance of correct sizing. CONCLUSIONS: Anatomic lobar reduction in lung transplantation is a safe and effective means of transplanting pediatric and small adult recipients, and urgently listed patients.