We demonstrate noninvasive near-infrared diffuse optical spectroscopy (DOS) measurements of tissue hemoglobin contents that can track progressive reductions in central blood volume in human volunteers. Measurements of mean arterial blood pressure (MAP), heart rate (HR), stroke volume (SV), and cardiac output (Q) are obtained in ten healthy human subjects during baseline supine rest and exposure to progressive reductions of central blood volume produced by application of lower body negative pressure (LBNP). Simultaneous quantitative noninvasive measurements of tissue oxyhemoglobin (OHb), deoxyhemoglobin (RHb), total hemoglobin concentration (THb), and tissue hemoglobin oxygen saturation (S(t)O(2)) are performed throughout LBNP application using broadband DOS. As progressively increasing amounts of LBNP are applied, HR increases, and MAP, SV, and Q decrease (p<0.001). OHb, S(t)O(2), and THb decrease (p<0.001) in correlation with progressive increases in LBNP, while tissue RHb remained relatively constant (p=0.378). The average fractional changes from baseline values in DOS OHb (fOHb) correlate closely with independently measured changes in SV (r(2)=0.95) and Q (r(2)=0.98) during LBNP. Quantitative noninvasive broadband DOS measurements of tissue hemoglobin parameters of peripheral perfusion are capable of detecting progressive reductions in central blood volume, and appear to be sensitive markers of early hypoperfusion associated with hemorrhage as simulated by LBNP.

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.