Associations between Sperm Epigenetic Age and Semen Parameters: An Evaluation of Clinical and Non-Clinical Cohorts.

The well-documented relationship between chronological age and the sperm methylome has allowed for the construction of epigenetic clocks that estimate the biological age of sperm based on DNA methylation, which we previously termed sperm epigenetic age (SEA). Our lab demonstrated that SEA is positively associated with the time taken to achieve pregnancy; however, its relationship with semen parameters is unknown. A total of 379 men from the Longitudinal Investigation of Fertility and Environment (LIFE) study, a non-clinical cohort, and 192 men seeking fertility treatment from the Sperm Environmental Epigenetics and Development Study (SEEDS) were included in the study. Semen analyses were conducted for both cohorts, and SEA was previously generated using a machine learning algorithm and DNA methylation array data. Association analyses were conducted via multivariable linear regression models adjusting for BMI and smoking status. We found that SEA was not associated with standard semen characteristics in SEEDS and LIFE cohorts. However, SEA was significantly associated with higher sperm head length and perimeter, the presence of pyriform and tapered sperm, and lower sperm elongation factor in the LIFE study (p < 0.05). Based on our results, SEA is mostly associated with defects in sperm head morphological factors that are less commonly evaluated during male infertility assessments. SEA shows promise to be an independent biomarker of sperm quality to assess male fecundity.

Quantification of changes in myocardial T1 * values with exercise cardiac MRI using a free-breathing non-electrocardiograph radial imaging.

PURPOSE: To develop and evaluate a free breathing non-electrocardiograph (ECG) myocardial T1 * mapping sequence using radial imaging to quantify the changes in myocardial T1 * between rest and exercise (T1 *reactivity ) in exercise cardiac MRI (Ex-CMR). METHODS: A free-running T1 * sequence was developed using a saturation pulse followed by three Look-Locker inversion-recovery experiments. Each Look-Locker continuously acquired data as radial trajectory using a low flip-angle spoiled gradient-echo readout. Self-navigation was performed with a temporal resolution of ∼100 ms for retrospectively extracting respiratory motion. The mid-diastole phase for every cardiac cycle was retrospectively detected on the recorded electrocardiogram signal using an empirical model. Multiple measurements were performed to obtain mean value to reduce effects from the free-breathing acquisition. Finally, data acquired at both mid-diastole and end-expiration are picked and reconstructed by a low-rank plus sparsity constraint algorithm. The performance of this sequence was evaluated by simulations, phantoms, and in vivo studies at rest and after physiological exercise. RESULTS: Numerical simulation demonstrated that changes in T1 * are related to the changes in T1 ; however, other factors such as breathing motion could influence T1 * measurements. Phantom T1 * values measured using free-running T1 * mapping sequence had good correlation with spin-echo T1 values and was insensitive to heart rate. In the Ex-CMR study, the measured T1 * reactivity was 10% immediately after exercise and declined over time. CONCLUSION: The free-running T1 * mapping sequence allows free-breathing non-ECG quantification of changes in myocardial T1 * with physiological exercise. Although, absolute myocardial T1 * value is sensitive to various confounders such as B1 and B0 inhomogeneity, quantification of its change may be useful in revealing myocardial tissue properties with exercise.

Free-breathing whole-heart multi-slice myocardial T1 mapping in 2 minutes.

PURPOSE: To develop and validate a saturation-delay-inversion recovery preparation, slice tracking and multi-slice based sequence for measuring whole-heart native T1 . METHOD: The proposed free-breathing sequence performs T1 mapping of multiple left-ventricular slices by slice-interleaved acquisition to collect 10 electrocardiogram-triggered single-shot slice-selective images for each slice. A saturation-delay-inversion recovery pulse is used for T1 preparation. Prospective slice tracking by the diaphragm navigator and retrospective registration are used to reduce through-plane and in-plane motion, respectively. The proposed sequence was validated in both phantom and human subjects (12 healthy subjects and 15 patients who were referred for a clinical cardiac MR exam) and compared with saturation recovery single-shot acquisition (SASHA) and modified Look-Locker inversion recovery (MOLLI). RESULTS: Phantom T1 measured by the proposed sequence had excellent agreement (R2  = 0.99) with the ground-truth T1 and was insensitive to heart rate. In both healthy subjects and patients, the proposed sequence yielded nine left-ventricular T1 maps per volume in less than 2 minutes (healthy volunteers: 1.8 ± 0.4 minutes; patients: 1.9 ± 0.2 minutes). The average T1 of whole left ventricle for all healthy subjects and patients were 1560 ± 61 and 1535 ± 49 ms by SASHA, 1208 ± 42 and 1233 ± 56 ms by MOLLI5(3)3, and 1397 ± 34 and 1433 ± 56 ms by the proposed sequence, respectively. The corresponding coefficient of variation of T1 were 6.2 ± 1.4% and 5.8 ± 1.6%, 5.3 ± 1.1% and 5.1 ± 0.8%, and 4.9 ± 0.8% and 4.5 ± 0.8%, respectively. CONCLUSION: The proposed sequence enables quantification of whole heart T1 with good accuracy and precision in less than 2 minutes during free breathing.

Free-breathing simultaneous myocardial T1 and T2 mapping with whole left ventricle coverage.

PURPOSE: To develop a free-breathing sequence, that is, Multislice Joint T1 -T2 , for simultaneous measurement of myocardial T1 and T2 for multiple slices to achieve whole left-ventricular coverage. METHODS: Multislice Joint T1 -T2 adopts slice-interleaved acquisition to collect 10 single-shot electrocardiogram-triggered images for each slice prepared by saturation and T2 preparation to simultaneously estimate myocardial T1 and T2 and achieve whole left-ventricular coverage. Prospective slice-tracking using a respiratory navigator and retrospective image registration are used to reduce through-plane and in-plane motion, respectively. Multislice Joint T1 -T2 was validated through numerical simulations and phantom and in vivo experiments, and compared with saturation-recovery single-shot acquisition and T2 -prepared balanced Steady-State Free Precession (T2 -prep SSFP) sequences. RESULTS: Phantom T1 and T2 from Multislice Joint T1 -T2 had good accuracy and precision, and were insensitive to heart rate. Multislice Joint T1 -T2 yielded T1 and T2 maps of nine left-ventricular slices in 1.4 minutes. The mean left-ventricular T1 difference between saturation-recovery single-shot acquisition and Multislice Joint T1 -T2 across healthy subjects and patients was 191 ms (1564 ± 60 ms versus 1373 ± 50 ms; P < .05) and 111 ms (1535 ± 49 ms vs 1423 ± 49 ms; P < .05), respectively. The mean difference in left-ventricular T2 between T2 -prep SSFP and Multislice Joint T1 -T2 across healthy subjects and patients was -6.3 ms (42.4 ± 1.4 ms vs 48.7 ± 2.5; P < .05) and -5.7 ms (41.6 ± 2.5 ms vs 47.3 ± 2.7; P < .05), respectively. CONCLUSION: Multislice Joint T1 -T2 enables quantification of whole left-ventricular T1 and T2 during free breathing within a clinically feasible scan time of less than 2 minutes.

Highly accelerated free-breathing real-time phase contrast cardiovascular MRI via complex-difference deep learning.

PURPOSE: To develop and evaluate a real-time phase contrast (PC) MRI protocol via complex-difference deep learning (DL) framework. METHODS: DL used two 3D U-nets to separately filter aliasing artifact from radial real-time velocity-compensated and complex-difference images. U-nets were trained with synthetic real-time PC generated from electrocardiograph (ECG) -gated, breath-hold, segmented PC (ECG-gated segmented PC) acquired at the ascending aorta of 510 patients. In 21 patients, free-breathing, ungated real-time (acceleration rate = 28.8) and ECG-gated segmented (acceleration rate = 2) PC were prospectively acquired at the ascending aorta. Hemodynamic parameters (cardiac output [CO], stroke volume [SV], and mean velocity at peak systole [peak mean velocity]) were measured for ECG-gated segmented and DL-filtered synthetic real-time PC and compared using Bland-Altman and linear regression analyses. Additionally, hemodynamic parameters were quantified from DL-filtered, compressed-sensing (CS) -reconstructed, and gridding reconstructed prospective real-time PC and compared to ECG-gated segmented PC. RESULTS: Synthetic real-time PC with DL showed strong correlation (R > 0.98) and good agreement with ECG-gated segmented PC for quantified hemodynamic parameters (mean-difference: CO = -0.3 L/min, SV = -4.3 mL, peak mean velocity = -2.3 cm/s). On average, DL required 0.39 s/frame to filter prospective real-time PC, which was 4.6-fold faster than CS. Compared to CS, DL showed superior correlation, tighter limits of agreement (LOAs), better bias for peak mean velocity, and worse bias for CO and SV. Compared to gridding, DL showed similar correlation, tighter LOAs for CO and SV, similar bias for CO, and worse bias for SV and peak mean velocity. CONCLUSION: The complex-difference DL framework accelerated real-time PC-MRI by nearly 28-fold, enabling rapid free-running real-time assessment of flow hemodynamics.

Deep complex convolutional network for fast reconstruction of 3D late gadolinium enhancement cardiac MRI.

Several deep-learning models have been proposed to shorten MRI scan time. Prior deep-learning models that utilize real-valued kernels have limited capability to learn rich representations of complex MRI data. In this work, we utilize a complex-valued convolutional network (ℂNet) for fast reconstruction of highly under-sampled MRI data and evaluate its ability to rapidly reconstruct 3D late gadolinium enhancement (LGE) data. ℂNet preserves the complex nature and optimal combination of real and imaginary components of MRI data throughout the reconstruction process by utilizing complex-valued convolution, novel radial batch normalization, and complex activation function layers in a U-Net architecture. A prospectively under-sampled 3D LGE cardiac MRI dataset of 219 patients (17 003 images) at acceleration rates R = 3 through R = 5 was used to evaluate ℂNet. The dataset was further retrospectively under-sampled to a maximum of R = 8 to simulate higher acceleration rates. We created three reconstructions of the 3D LGE dataset using (1) ℂNet, (2) a compressed-sensing-based low-dimensional-structure self-learning and thresholding algorithm (LOST), and (3) a real-valued U-Net (realNet) with the same number of parameters as ℂNet. LOST-reconstructed data were considered the reference for training and evaluation of all models. The reconstructed images were quantitatively evaluated using mean-squared error (MSE) and the structural similarity index measure (SSIM), and subjectively evaluated by three independent readers. Quantitatively, ℂNet-reconstructed images had significantly improved MSE and SSIM values compared with realNet (MSE, 0.077 versus 0.091; SSIM, 0.876 versus 0.733, respectively; p < 0.01). Subjective quality assessment showed that ℂNet-reconstructed image quality was similar to that of compressed sensing and significantly better than that of realNet. ℂNet reconstruction was also more than 300 times faster than compressed sensing. Retrospective under-sampled images demonstrate the potential of ℂNet at higher acceleration rates. ℂNet enables fast reconstruction of highly accelerated 3D MRI with superior performance to real-valued networks, and achieves faster reconstruction than compressed sensing.

Casein kinase 2-mediated phosphorylation of Brahma-related gene 1 controls myoblast proliferation and contributes to SWI/SNF complex composition.

Transcriptional regulation is modulated in part by chromatin-remodeling enzymes that control gene accessibility by altering chromatin compaction or nucleosome positioning. Brahma-related gene 1 (Brg1), a catalytic subunit of the mammalian SWI/SNF chromatin-remodeling enzymes, is required for both myoblast proliferation and differentiation, and the control of Brg1 phosphorylation by calcineurin, PKCß1, and p38 regulates the transition to differentiation. However, we hypothesized that Brg1 activity might be regulated by additional kinases. Here, we report that Brg1 is also a target of casein kinase 2 (CK2), a serine/threonine kinase, in proliferating myoblasts. We found that CK2 interacts with Brg1, and mutation of putative phosphorylation sites to non-phosphorylatable (Ser to Ala, SA) or phosphomimetic residues (Ser to Glu, SE) reduced Brg1 phosphorylation by CK2. Although BRG1-deleted myoblasts that ectopically express the SA-Brg1 mutant proliferated similarly to the parental cells or cells ectopically expressing wild-type (WT) Brg1, ectopic expression of the SE-Brg1 mutant reduced proliferation and increased cell death, similar to observations from cells lacking Brg1. Moreover, pharmacological inhibition of CK2 increased myoblast proliferation. Furthermore, the Pax7 promoter, which controls expression of a key transcription factor required for myoblast proliferation, was in an inaccessible chromatin state in the SE-Brg1 mutant, suggesting that hyperphosphorylated Brg1 cannot remodel chromatin. WT-, SA-, and SE-Brg1 exhibited distinct differences in interacting with and affecting expression of the SWI/SNF subunits Baf155 and Baf170 and displayed differential sub-nuclear localization. Our results indicate that CK2-mediated phosphorylation of Brg1 regulates myoblast proliferation and provides insight into one mechanism by which composition of the mammalian SWI/SNF enzyme complex is regulated.

Mixtures of per- and polyfluoroalkyl substances (PFAS) alter sperm methylation and long-term reprogramming of offspring liver and fat transcriptome.

Male fertility has been declining worldwide especially in countries with high levels of endocrine disrupting chemicals (EDCs). Per- and polyfluorinated alkyl Substances (PFAS) have been classified as EDCs and have been linked to adverse male reproductive health. The mechanisms of these associations and their implications on offspring health remain unknown. The aims of the current study were to assess the effect of PFAS mixtures on the sperm methylome and transcriptional changes in offspring metabolic tissues (i.e., liver and fat). C57BL/6 male mice were exposed to a mixture of PFAS (PFOS, PFOA, PFNA, PFHxS, Genx; 20 µg/L each) for 18-weeks or water as a control. Genome-wide methylation was assessed on F0 epidydimal sperm using reduced representation bisulfite sequencing (RRBS) and Illumina mouse methylation array, while gene expression was assessed by bulk RNA sequencing in 8-week-old offspring derived from unexposed females. PFAS mixtures resulted in 2,861 (RRBS) and 83 (Illumina) sperm DMRs (q < 0.05). Functional enrichment revealed that PFAS-induced sperm DMRs were associated with behavior and developmental pathways in RRBS, while Illumina DMRs were related to lipid metabolism and cell signaling. Additionally, PFAS mixtures resulted in 40 and 53 differentially expressed genes (DEGs) in the liver and fat of males, and 9 and 31 DEGs in females, respectively. Functional enrichment of DEGs revealed alterations in cholesterol metabolism and mitotic cell cycle regulation in the liver and myeloid leukocyte migration in fat of male offspring, while in female offspring, erythrocyte development and carbohydrate catabolism were affected in fat. Our results demonstrate that exposure to a mixture of legacy and newly emerging PFAS chemicals in adult male mice result in aberrant sperm methylation and altered gene expression of offspring liver and fat in a sex-specific manner. These data indicate that preconception PFAS exposure in males can be transmitted to affect phenotype in the next generation.

Association Between Left Ventricular Mechanical Deformation and Myocardial Fibrosis in Nonischemic Cardiomyopathy.

Background In patients with nonischemic cardiomyopathy, nonischemic fibrosis detected by late gadolinium enhancement (LGE) cardiovascular magnetic resonance is related to adverse cardiovascular outcomes. However, its relationship with left ventricular (LV) mechanical deformation parameters remains unclear. We sought to investigate the association between LV mechanics and the presence, location, and extent of fibrosis in patients with nonischemic cardiomyopathy. Methods and Results We retrospectively identified 239 patients with nonischemic cardiomyopathy (67% male; 55±14 years) referred for a clinical cardiovascular magnetic resonance. LGE was present in 109 patients (46%), most commonly (n=52; 22%) in the septum. LV deformation parameters did not differentiate between LGE-positive and LGE-negative groups. Global longitudinal, radial, and circumferential strains, twist and torsion showed no association with extent of fibrosis. Patients with septal fibrosis had a more depressed LV ejection fraction (30±12% versus 35±14%; P=0.032) and more impaired global circumferential strain (-7.9±3.5% versus -9.7±4.4%; P=0.045) and global radial strain (10.7±5.2% versus 13.3±7.7%; P=0.023) than patients without septal LGE. Global longitudinal strain was similar in both groups. While patients with septal-only LGE (n=28) and free wall-only LGE (n=32) had similar fibrosis burden, the septal-only LGE group had more impaired LV ejection fraction and global circumferential, longitudinal, and radial strains (all P<0.05). Conclusions There is no association between LV mechanical deformation parameters and presence or extent of fibrosis in patients with nonischemic cardiomyopathy. Septal LGE was associated with poor global LV function, more impaired global circumferential and radial strains, and more impaired global strain rates.

Atomic Absorbance Spectroscopy to Measure Intracellular Zinc Pools in Mammalian Cells.

Transition metals are essential micronutrients for organisms but can be toxic to cells at high concentrations by competing with physiological metals in proteins and generating redox stress. Pathological conditions that lead to metal depletion or accumulation are causal agents of different human diseases. Some examples include anemia, acrodermatitis enteropathica, and Wilson's and Menkes' diseases. It is therefore important to be able to measure the levels and transport of transition metals in biological samples with high sensitivity and accuracy in order to facilitate research exploring how these elements contribute to normal physiological functions and toxicity. Zinc (Zn), for example, is a cofactor in many mammalian proteins, participates in signaling events, and is a secondary messenger in cells. In excess, Zn is toxic and can inhibit absorption of other metals, while in deficit, it can lead to a variety of potentially lethal conditions. Graphite furnace atomic absorption spectroscopy (GF-AAS) provides a highly sensitive and effective method for determining Zn and other transition metal concentrations in diverse biological samples. Electrothermal atomization via GF-AAS quantifies metals by atomizing small volumes of samples for subsequent selective absorption analysis using wavelength of excitation of the element of interest. Within the limits of linearity of the Beer-Lambert Law, the absorbance of light by the metal is directly proportional to concentration of the analyte. Compared to other methods of determining Zn content, GF-AAS detects both free and complexed Zn in proteins and possibly in small intracellular molecules with high sensitivity in small sample volumes. Moreover, GF-AAS is also more readily accessible than inductively coupled plasma mass spectrometry (ICP-MS) or synchrotron-based X-ray fluorescence. In this method, the systematic sample preparation of different cultured cell lines for analyses in a GF-AAS is described. Variations in this trace element were compared in both whole cell lysates and subcellular fractions of proliferating and differentiated cells as proof of principle.

Dynamic changes in copper homeostasis and post-transcriptional regulation of Atp7a during myogenic differentiation.

Copper (Cu) is an essential metal required for activity of a number of redox active enzymes that participate in critical cellular pathways such as metabolism and cell signaling. Because it is also a toxic metal, Cu must be tightly controlled by a series of transporters and chaperone proteins that regulate Cu homeostasis. The critical nature of Cu is highlighted by the fact that mutations in Cu homeostasis genes cause pathologic conditions such as Menkes and Wilson diseases. While Cu homeostasis in highly affected tissues like the liver and brain is well understood, no study has probed the role of Cu in development of skeletal muscle, another tissue that often shows pathology in these conditions. Here, we found an increase in whole cell Cu content during differentiation of cultured immortalized or primary myoblasts derived from mouse satellite cells. We demonstrate that Cu is required for both proliferation and differentiation of primary myoblasts. We also show that a key Cu homeostasis gene, Atp7a, undergoes dynamic changes in expression during myogenic differentiation. Alternative polyadenylation and stability of Atp7a mRNA fluctuates with differentiation stage of the myoblasts, indicating post-transcriptional regulation of Atp7a that depends on the differentiation state. This is the first report of a requirement for Cu during myogenic differentiation and provides the basis for understanding the network of Cu transport associated with myogenesis.

Differential expression of zinc transporters accompanies the differentiation of C2C12 myoblasts.

Zinc transporters facilitate metal mobilization and compartmentalization, playing a key role in cellular development. Little is known about the mechanisms and pathways of Zn movement between Zn transporters and metalloproteins during myoblast differentiation. We analyzed the differential expression of ZIP and ZnT transporters during C2C12 myoblast differentiation. Zn transporters account for a transient decrease of intracellular Zn upon myogenesis induction followed by a gradual increase of Zn in myotubes. Considering the subcellular localization and function of each of the Zn transporters, our findings indicate that a fine regulation is necessary to maintain correct metal concentrations in the cytosol and subcellular compartments to avoid toxicity, maintain homeostasis, and for loading metalloproteins needed during myogenesis. This study advances our basic understanding of the complex Zn transport network during muscle differentiation.