Jennifer A. Schrack

Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake

Background: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants. Objective: The objective of the study was to identify common genetic variants that are associated with macronutrient intake. Design: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10−6 were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data. Results: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10−8) and lower fat (β ± SE: −0.21 ± 0.04%; P = 1.57 × 10−9) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)–increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10−10), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10−7). Conclusion: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

The Energetic Pathway to Mobility Loss: An Emerging New Framework for Longitudinal Studies on Aging

The capacity to walk independently is a central component of independent living. Numerous large and well‐designed longitudinal studies have shown that gait speed, a reliable marker of mobility, tends to decline with age and as a consequence of chronic disease. This decline in performance is of utmost importance because slow walking speed is a strong, independent predictor of disability, healthcare utilization, nursing home admission, and mortality. Based on these robust findings, it has been postulated that age‐associated decline in walking speed is a reliable barometer of the effect of biological aging on health and functional status. Despite the extraordinary prognostic information that walking speed provides, which is often superior to traditional medical information, there is a limited understanding of the mechanisms that underlie age‐ and disease‐related gait speed decline. Identifying the mechanisms that underlie the prognostic value of walking speed should be a central theme in the design of the next generation of longitudinal studies of aging, with appropriate measures introduced and analytical approaches incorporated.

Assessing the “Physical Cliff”: Detailed Quantification of Age-Related Differences in Daily Patterns of Physical Activity

BACKGROUND In spite of evidence that physical activity has beneficial effects on health and age-related functional decline, there is a scarcity of detailed and accurate information on objectively measured daily activity and patterns of such activity in older adults. METHODS Participants in the Baltimore Longitudinal Study of Aging (n = 611, 50% male, mean age 67, range 32-93) wore the Actiheart portable activity monitor for 7 days in the free-living environment. The association between activity and age was modeled using a continuous log-linear regression of activity counts on age with sex, body mass index, employment status, functional performance, and comorbid conditions as covariates. RESULTS In the fully adjusted model, continuous analyses demonstrated that overall physical activity counts were 1.3% lower for each year increase in age. Although there were no differences among morning levels of activity, there was significantly lower afternoon and evening activity in older individuals (p < .01). After adjusting for age, poor functional performance, nonworking status, and higher body mass index were independently associated with less physical activity (p < .001). CONCLUSIONS The use of accelerometers to characterize minute-by-minute intensity, cumulative physical activity counts, and daily activity patterns provides detailed data not gathered by traditional subjective methods, particularly at low levels of activity. The findings of a 1.3% decrease per year in activity from mid-to-late life, and the corresponding drop in afternoon and evening activity, provide new information that may be useful when targeting future interventions. Further, this methodology addresses essential gaps in understanding activity patterns and trends in more sedentary sectors of the population.

The Role of Energetic Cost in the Age‐Related Slowing of Gait Speed

To determine whether slow gait represents a compensatory strategy to reduce the energetic cost of walking with age.

Comparison of the Cosmed K4b2 Portable Metabolic System in Measuring Steady-State Walking Energy Expenditure

Background and Aims Recent introduction of the Cosmed K4b2 portable metabolic analyzer allows measurement of oxygen consumption outside of a laboratory setting in more typical clinical or household environments and thus may be used to obtain information on the metabolic costs of specific daily life activities. The purpose of this study was to assess the accuracy of the Cosmed K4b2 portable metabolic analyzer against a traditional, stationary gas exchange system (the Medgraphics D-Series) during steady-state, submaximal walking exercise. Methods Nineteen men and women (9 women, 10 men) with an average age of 39.8 years (±13.8) completed two 400 meter walk tests using the two systems at a constant, self-selected pace on a treadmill. Average oxygen consumption (VO2) and carbon dioxide production (VCO2) from each walk were compared. Results Intraclass Correlation Coefficient (ICC) and Pearson correlation coefficients between the two systems for weight indexed VO2 (ml/kg/min), total VO2 (ml/min), and VCO2 (ml/min) ranged from 0.93 to 0.97. Comparison of the average values obtained using the Cosmed K4b2 and Medgraphics systems using paired t-tests indicate no significant difference for VO2 (ml/kg/min) overall (p = 0.25), or when stratified by sex (p = 0.21 women, p = 0.69 men). The mean difference between analyzers was – 0.296 ml/kg/min (±0.26). Results were not significantly different for VO2 (ml/min) or VCO2 (ml/min) within the study population (p = 0.16 and p = 0.08, respectively), or when stratified by sex (VO2: p = 0.51 women, p = 0.16 men; VCO2: p = .11 women, p = 0.53 men). Conclusion The Cosmed K4b2 portable metabolic analyzer provides measures of VO2 and VCO2 during steady-state, submaximal exercise similar to a traditional, stationary gas exchange system.

Functional impairment, disability, and frailty in adults aging with HIV-infection

The integration of antiretroviral therapy (i.e., ART) into HIV care has dramatically extended the life expectancy of those living with HIV. However, in comparison to similar HIV-uninfected populations, HIV-infected persons experience an excess of morbidity and mortality with an early onset of aging complications including neurocognitive decline, osteoporosis, impaired physical function, frailty, and falls. Recent consensus guidelines encourage clinicians and researchers to consider functional impairment of HIV-infected adults as a measure to understand the impact of aging across a range of abilities. Despite the importance of assessing function in persons aging with HIV infection, a lack of consistent terminology and standardization of assessment tools has limited the application of functional assessments in clinical or research settings. Herein, we distinguish between different approaches used to assess function, describe what is known about function in the aging HIV population, and consider directions for future research.

Assessing Daily Physical Activity in Older Adults: Unraveling the Complexity of Monitors, Measures, and Methods

At the 67th Gerontological Society of America Annual Meeting, a preconference workshop was convened to discuss the challenges of accurately assessing physical activity in older populations. The advent of wearable technology (eg, accelerometers) to monitor physical activity has created unprecedented opportunities to observe, quantify, and define physical activity in the real-world setting. These devices enable researchers to better understand the associations of physical activity with aging, and subsequent health outcomes. However, a consensus on proper methodological use of these devices in older populations has not been established. To date, much of the validation research regarding device type, placement, and data interpretation has been performed in younger, healthier populations, and translation of these methods to older populations remains problematic. A better understanding of these devices, their measurement properties, and the data generated is imperative to furthering our understanding of daily physical activity, its effects on the aging process, and vice versa. The purpose of this article is to provide an overview of the highlights of the preconference workshop, including properties of the different types of accelerometers, the methodological challenges of employing accelerometers in older study populations, a brief summary of ongoing aging-related research projects that utilize different types of accelerometers, and recommendations for future research directions.

Assessing Fatigability in Mobility-Intact Older Adults

To evaluate the criterion validity of two measures of fatigability, defined as performance deterioration or perceived effort to perform a standardized task.

IDEAL aging is associated with lower resting metabolic rate: the Baltimore Longitudinal Study of Aging.

To assess the associations among age, health status, and resting metabolic rate (RMR) in a large population of older adults.

Generalized multilevel function-on-scalar regression and principal component analysis.

This manuscript considers regression models for generalized, multilevel functional responses: functions are generalized in that they follow an exponential family distribution and multilevel in that they are clustered within groups or subjects. This data structure is increasingly common across scientific domains and is exemplified by our motivating example, in which binary curves indicating physical activity or inactivity are observed for nearly 600 subjects over 5 days. We use a generalized linear model to incorporate scalar covariates into the mean structure, and decompose subject-specific and subject-day-specific deviations using multilevel functional principal components analysis. Thus, functional fixed effects are estimated while accounting for within-function and within-subject correlations, and major directions of variability within and between subjects are identified. Fixed effect coefficient functions and principal component basis functions are estimated using penalized splines; model parameters are estimated in a Bayesian framework using Stan, a programming language that implements a Hamiltonian Monte Carlo sampler. Simulations designed to mimic the application have good estimation and inferential properties with reasonable computation times for moderate datasets, in both cross-sectional and multilevel scenarios; code is publicly available. In the application we identify effects of age and BMI on the time-specific change in probability of being active over a 24-hour period; in addition, the principal components analysis identifies the patterns of activity that distinguish subjects and days within subjects.