Investigate whether socioeconomic status (SES) was related to brain volume in aging related regions, and if so, determine whether this relationship was mediated by lifestyle factors that are known to associate with risk of dementia in a population-based sample of community dwelling middle-aged adults.

Animal and human studies suggest the gut microbiome is linked to diabetes but additional data are needed on the associations of the gut microbiome to specific diabetes characteristics. The aim of this study was to examine the associations of gut microbiome composition to insulin resistance [Homeostatic Model Assessment of Insulin Resistance (HOMA-IR)], duration of diabetes, and 4 stages of diabetes [normoglycemia, pre-diabetes, and diabetes with (+) and without (-) medication for diabetes].

To examine longitudinal race and sex differences in mid-life brain health and to evaluate whether cardiovascular health (CVH) or apolipoprotein E (APOE) ε4 explain differences.

To identify early changes in brain structure and function that are associated with cardiovascular risk factors (CVRF).

Several findings suggest that testosterone (T) is neuroprotective and that declining T levels during aging are associated with cognitive and brain pathologies; however, little is known on T and brain health in middle-age. We examined the relationships of total T, bioavailable T, and sex hormone binding globulin (SHBG) levels with total and regional gray matter (GM) and white matter (WM) volumes in middle-aged men. We also evaluated the association of sex hormone levels with cognitive function.

Clinical and epidemiological studies of older persons have implicated clusterin in Alzheimer's disease (AD) pathogenesis. In the context of identifying early biomarkers of risk, we examined associations of plasma clusterin and characteristics of AD in middle-aged individuals from the community.

Decreased cerebral tissue integrity and cerebral blood flow (CBF) are features of neurodegenerative diseases. Brain tissue maintenance is an energy-demanding process, making it particularly sensitive to hypoperfusion. However, little is known about the association between blood flow and brain microstructural integrity, including in normative aging.

The purpose of this study was to investigate whether long-term television viewing patterns, a common sedentary behavior, in early to mid-adulthood is associated with gray matter brain volume in midlife and if this is independent of physical activity. We evaluated 599 participants (51% female, 44% black, mean age 30.3 ± 3.5 at baseline and 50.2 ± 3.5 years at follow-up and MRI) from the prospective Coronary Artery Risk Development in Young Adults (CARDIA) study. We assessed television patterns with repeated interviewer-administered questionnaire spanning 20 years. Structural MRI (3T) measures of frontal cortex, entorhinal cortex, hippocampal, and total gray matter volumes were assessed at midlife. Over the 20 years, participants reported viewing an average of 2.5 ± 1.7 h of television per day (range: 0-10 h). After multivariable adjustment, greater television viewing was negatively associated with gray matter volume in the frontal (β = - 0.77; p = 0.01) and entorhinal cortex (β = - 23.83; p = 0.05) as well as total gray matter (β = - 2.09; p = 0.003) but not hippocampus. These results remained unchanged after additional adjustment for physical activity. For each one standard deviation increase in television viewing, the difference in gray matter volume z-score was approximately 0.06 less for each of the three regions (p < 0.05). Among middle-aged adults, greater television viewing in early to mid-adulthood was associated with lower gray matter volume. Sedentariness or other facets of television viewing may be important for brain aging even in middle age.

Cumulating evidence from epidemiologic studies implicates cardiovascular health and cerebrovascular function in several brain diseases in late life. We examined vascular risk factors with respect to a cerebrovascular measure of brain functioning in subjects in mid-life, which could represent a marker of brain changes in later life. Breath-hold functional MRI (fMRI) was performed in 541 women and men (mean age 50.4 years) from the Coronary Artery Risk Development in Young Adults (CARDIA) Brain MRI sub-study. Cerebrovascular reactivity (CVR) was quantified as percentage change in blood-oxygen level dependent (BOLD) signal in activated voxels, which was mapped to a common brain template and log-transformed. Mean CVR was calculated for anatomic regions underlying the default-mode network (DMN) - a network implicated in AD and other brain disorders - in addition to areas considered to be relatively spared in the disease (e.g. occipital lobe), which were utilized as reference regions. Mean CVR was significantly reduced in the posterior cingulate/precuneus (β=-0.063, 95% CI: -0.106, -0.020), anterior cingulate (β=-0.055, 95% CI: -0.101, -0.010), and medial frontal lobe (β=-0.050, 95% CI: -0.092, -0.008) relative to mean CVR in the occipital lobe, after adjustment for age, sex, race, education, and smoking status, in subjects with pre-hypertension/hypertension compared to normotensive subjects. By contrast, mean CVR was lower, but not significantly, in the inferior parietal lobe (β=-0.024, 95% CI: -0.062, 0.014) and the hippocampus (β=-0.006, 95% CI: -0.062, 0.050) relative to mean CVR in the occipital lobe. Similar results were observed in subjects with diabetes and dyslipidemia compared to those without these conditions, though the differences were non-significant. Reduced CVR may represent diminished vascular functionality for the DMN for individuals with prehypertension/hypertension in mid-life, and may serve as a preclinical marker for brain dysfunction in later life.

Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1)), and its ratio to forced vital capacity (FEV(1)/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV(1) and FEV(1)/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = )5.00×10(-11)), HLA-DQB1 and HLA-DQA2 (smallest P(JMA = )4.35×10(-9)), and KCNJ2 and SOX9 (smallest P(JMA = )1.28×10(-8)) were associated with FEV(1)/FVC or FEV(1) in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.