Cardiac Glycogen Fluctuations Are Robust in Short-Term Than Long-Term Binge Drinking and Follows a Sex Specific Manner.

Alcohol use is increasing among adults in midlife (i.e., ages 35-60), but few studies examine specific alcohol use behaviors in this age group. We examined measures of typical drinks, maximum drinks, binge drinking, and high-intensity drinking by age, sex, and race/ethnicity among midlife adults, as well as the prospective association between age 18 binge drinking and midlife behaviors. Data from 5180 respondents participating in the national Monitoring the Future Panel study who were aged 35-60 in 2022 (followed since they were in 12th grade in 1980-2005) were used to estimate past 30-day midlife drinking behaviors (i.e., typical drinks, maximum drinks, binge, and high-intensity drinking) by age group, sex, and race/ethnicity. Associations between age 18 binge drinking status and midlife drinking outcomes were examined, as well as moderation by sociodemographic characteristics. Across ages 35-60, the mean typical number of drinks on drinking days within the past month ranged from 1.4 to 1.8; the mean maximum drinks ranged from 2.3 to 3.2. Past-month binge and high-intensity drinking prevalence ranged from 19.1% to 31.2% and 3.6% to 8.1%, respectively. Estimates of drinking behaviors were generally higher among respondents aged 35-40 (vs. older age groups), males (vs. females), those identifying as White (vs. other racial/ethnic groups), and those who reported age 18 binge drinking (vs. not). Adolescent binge drinking was a stronger predictor of high-intensity drinking among females than males and of typical and maximum drinks among older (age 60) than younger (age 35) respondents. Binge and high-intensity drinking were reported by a meaningful percentage of the US midlife adults. Binge drinking in adolescence was a predictor of subsequent alcohol-related risks. These long-term connections were especially strong among females. Age 18 binge drinking was a stronger predictor of high-intensity drinking at age 60 than earlier in midlife, underscoring that adolescent binge drinking is a key indicator of risk across the lifespan.

AIMS: To study the mechanism of action of steroids in patients with peritumorous oedema. METHODS: To investigate early cerebral metabolic changes proton magnetic resonance spectroscopy (1H-MRS) was used before and...

In newborn rabbits, the early cerebral metabolic changes caused by hypoxic-ischemic (H-I) insult was examined by using volume localized 1H-MRS (STEAM). Partial ischemia was caused by unilateral carotid artery ligation, and hypoxia was induced by 10% oxygen inspiration for 150 minutes. Lactate immediately increased after hypoxia induction and almost disappeared 120 to 150 minutes after removal of hypoxia in both H-I and hypoxia-only experiments. Lactate production correlated well with decrease of the blood oxygen saturation. More lactate was produced on ischemic side 50 minutes post-hypoxia induction in H-I study. Ischemia alone did not cause any significant lactate production. Lactate caused by hypoxia can be dynamically monitored by localized 1H-MRS. Existence of regional ischemia can induce greater anaerobic glycolysis and may affect the pattern of brain injury under hypoxia. 1H-MRS is a sensitive tool to detect the acute metabolic change caused by H-I insult.

Stargardt disease (SD) is an inherited retinal disorder that leads to progressive vision loss. Currently, no approved treatments exist. Identifying early metabolic changes in the retina could be critical for the development of new therapies. Flavoprotein fluorescence (FPF) imaging has the potential to serve as a non-invasive biomarker for detecting these early changes before structural damage is evident. Therefore, this study evaluated FPF patterns in patients with SD and correlated these findings with structural imaging modalities, specifically fundus autofluorescence (FAF) and optical coherence tomography (OCT). This cross-sectional study enrolled 36 subjects with genetically confirmed ABCA4-associated SD between June 1, 2023, and January 31, 2024, at the University Eye Clinic Tübingen, Germany. FPF patterns were qualitatively and quantitatively analyzed and correlated with FAF and OCT findings to identify distinct lesion types. Several distinct lesion types were identified based on FPF signal patterns and their correlation with FAF and OCT findings. Increased FPF signals were primarily associated with outer retinal damage. In some cases, increased FPF was observed in the absence of significant structural changes, indicating early metabolic stress. This study demonstrates that FPF imaging is a promising tool for detecting early metabolic changes in Stargardt disease, potentially serving as a non-invasive biomarker for monitoring disease progression and treatment response. However, current FPF imaging technology is insufficient to discern true FPF signals from lipofuscin-derived fluorescence, making location-specific and FAF comparative analyses imperative and highlighting the need for longitudinal studies.

Currently, there are no reliable methods to optimize treatment regimens for individual breast cancer patients. Oncologists choose drug treatments based on expression levels of tumor cell signaling receptors (i.e. HER2, ER, PR) and other factors, and assess whether the treatment is effective after significant time has passed. Unfortunately, over one third of patients exhibit resistance to their initial treatment, increasing their risk of future metastasis and death. Morbidities from sub-optimal drug regimens could be reduced with a personalized drug screen for breast cancer at the time of diagnosis. With the vast number of therapeutic options available to patients (>50 drugs approved with more on the way), a high-throughput screening technology is needed to accurately evaluate how a patient will respond to these options. Here we present Optical Metabolic Imaging (OMI) of tumor-derived organoids as a predictive drug screening platform for individual breast cancer patients. Changes in cell metabolism precede changes in tumor volume and thus present an earlier marker of treatment response. OMI is sensitive to these early changes by exploiting the intrinsic fluorescent properties of NAD(P)H and FAD, coenzymes of metabolic reactions. OMI endpoints include the optical redox ratio (the fluorescence intensity of NAD(P)H divided by the fluorescence intensity of FAD), as well as the fluorescence lifetimes of NAD(P)H and FAD. The redox ratio reflects the cellular redox balance, and the fluorescence lifetimes report on the binding activity of these coenzymes. OMI has the unique ability to non-invasively monitor metabolism in living, intact samples on the single-cell level, and can thus quantify heterogeneity in drug response. Changes were quantified at the single-cell level using the OMI Index, a linear combination of the optical redox ratio and the mean NAD(P)H and FAD fluorescence lifetimes. This index was derived using a multivariate analysis of variance and has been shown previously to correlate with treatment response in human cancer cells. OMI also allows for high-throughput screening of potential cancer drugs and drug combinations on patient biopsy samples cultured ex vivo. These samples are grown as organoids in a 3D matrix that mimics the natural tumor environment. Organoids were successfully generated from core needle biopsies of untreated breast tumors. These organoids were treated with the patient's prescribed neoadjuvant therapy, and early metabolic changes were quantified using OMI. Organoids grew from a variety of untreated breast tumor subtypes, and early metabolic changes could be resolved at the single-cell level after only 24 hours of treatment in vitro. In parallel, each patient's Residual Cancer Burden (RCB) score was quantified by a surgical pathologist after neoadjuvant treatment and served as gold standard validation of tumor drug response. Results from an early cohort of patients suggest that OMI could be used to predict patient clinical response to therapy. A linear combination of OMI variables measured in vitro in only 48 hours correlated strongly with patient RCB score (Pearson correlation coefficient=0.97, n=5). This methodology could allow oncologists to determine the ideal treatment regimen for their patients at the time of diagnosis. Citation Format: Sharick JT, Walsh AJ, Sanders ME, Kelley MC, Meszoely IM, Hooks MA, Burkard ME, Esbona K, Choudhary A, Skala MC. Personalized neoadjuvant treatment planning using optical metabolic imaging [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-01-01.

<div>Abstract<p>Multiple studies have identified metabolic changes within the tumor and its microenvironment during carcinogenesis. Yet, the mechanisms by which tumors affect the host metabolism are unclear. We find that systemic inflammation induced by cancer leads to liver infiltration of myeloid cells at early extrahepatic carcinogenesis. The infiltrating immune cells via IL6–pSTAT3 immune–hepatocyte cross-talk cause the depletion of a master metabolic regulator, HNF4α, consequently leading to systemic metabolic changes that promote breast and pancreatic cancer proliferation and a worse outcome. Preserving HNF4α levels maintains liver metabolism and restricts carcinogenesis. Standard liver biochemical tests can identify early metabolic changes and predict patients’ outcomes and weight loss. Thus, the tumor induces early metabolic changes in its macroenvironment with diagnostic and potentially therapeutic implications for the host.</p>Significance:<p>Cancer growth requires a permanent nutrient supply starting from early disease stages. We find that the tumor extends its effect to the host's liver to obtain nutrients and rewires the systemic and tissue-specific metabolism early during carcinogenesis. Preserving liver metabolism restricts tumor growth and improves cancer outcomes.</p></div>

(31)P-magnetic resonance spectroscopy ((31)P-MRS) is a non-invasive tool to study high-energy phosphate (HEP) metabolism. We evaluate whether 31P-MRS can detect early changes in kidney HEP metabolism during a 6-month trial with Valsartan. Twenty consecutive stable and normotensive kidney-transplanted patients were enrolled. Nine of them received short-term low-dose Valsartan treatment (80 mg/day) for 6 months, while 11 controls received no medication. Kidney HEP metabolism was evaluated both at baseline and after treatment by (31)P-MRS with a 1.5 T system (Gyroscan Intera Master 1.5 MR System; Philips Medical Systems, Best, The Netherlands). Valsartan-treated patients (n = 9) showed a significant increase in β-ATP/Pi ratio, a marker of kidney HEP metabolism (baseline = 1.03 ± 0.08 vs. 6 months = 1.26 ± 0.07, p = 0.03). In contrast, the b-ATP/Pi ratio in the control group (n = 11) did not change (baseline = 0.85 ± 0.10 vs. 6 months = 0.89 ± 0.08, ns). The improvement in the β-ATP/Pi ratio was not associated with a reduction in arterial blood pressure or in urinary albumin excretion. Kidney-localized (31)P-MRS can detect early changes in kidney HEP metabolism during a short-term low-dose Valsartan treatment in stable normotensive kidney-transplanted patients.

MicroPET assessment of androgenic control of glucose and acetate uptake in the rat prostate and a prostate cancer tumor model

<div>Abstract<p>Multiple studies identified metabolic changes within the tumor and its microenvironment during carcinogenesis. Yet, the mechanisms by which tumors affect the host metabolism are unclear. We find that systemic inflammation induced by the cancer leads to liver infiltration of myeloid cells at early extrahepatic carcinogenesis. The infiltrating immune cells via IL-6-pSTAT3 immune-hepatocyte crosstalk cause the depletion of a master metabolic regulator, HNF4a, consequently leading to systemic metabolic changes that promote breast and pancreatic cancer proliferation and a worse outcome. Preserving HNF4 levels maintains liver metabolism and restricts carcinogenesis. Standard liver biochemical tests can identify early metabolic changes and predict patients' outcomes and weight loss. Thus, the tumor induces early metabolic changes in its macro-environment with diagnostic and potentially therapeutic implications for the host.</p></div>

Evaluation of early metabolic changes in metastatic brain tumors after Gamma Knife radiosurgery was performed by long-echo (TR, 2000ms; TE, 136ms; 128-236 acquisitions) volume-selected single-voxel proton magnetic resonance spectroscopy (MRS). Eighty-five brain metastases in 81 patients were investigated before treatment and 16-18h thereafter. Standard metabolic ratios, namely N-acetylaspartate (NAA)/creatine (Cr), phosphorylcholine/glycerophosphorylcholine (Cho)/Cr, NAA/Cho, lactate (Lac)/Cr, and mobile lipids (Lip)/Cr, were calculated, and comparison of their values before and after irradiation was done. No volumetric changes of any neoplasm were found in any case on the next day after treatment. At the same time, significant reduction of Cho/Cr (P < 0.001) and NAA/Cr (P < 0.01) ratios on the proton MRS of the tumor was disclosed. Reduction of Cho/Cr ratio was significantly more prominent in neoplasms with higher pretreatment Cho/Cr ratios (P < 0.001) and heterogeneous contrast enhancement (P < 0.01). Reduction of NAA/Cr ratio was predominantly determined by its pretreatment value (P < 0.001). The observed decrease of Cho/Cr ratio probably reflects inhibition of proliferative activity and early apoptotic cell loss, whereas reduction of NAA/Cr may result from radiation-induced modulation of neuronal activity in the peritumoral brain tissue. Serial proton MRS represents a valuable diagnostic tool for evaluation of metabolic changes in intracranial neoplasms after radiosurgical treatment.

.Radiation resistance remains a significant problem for cancer patients, especially due to the time required to definitively determine treatment outcome. For fractionated radiation therapy, nearly 7 to 8 weeks can elapse before a tumor is deemed to be radiation-resistant. We used the optical redox ratio of to identify early metabolic changes in radiation-resistant lung cancer cells. These radiation-resistant human A549 lung cancer cells were developed by exposing the parental A549 cells to repeated doses of radiation (2 Gy). Although there were no significant differences in the optical redox ratio between the parental and resistant cell lines prior to radiation, there was a significant decrease in the optical redox ratio of the radiation-resistant cells 24 h after a single radiation exposure (). This change in the redox ratio was indicative of increased catabolism of glucose in the resistant cells after radiation and was associated with significantly greater protein content of hypoxia-inducible factor 1 (), a key promoter of glycolytic metabolism. Our results demonstrate that the optical redox ratio could provide a rapid method of determining radiation resistance status based on early metabolic changes in cancer cells.

Metabolic health improvements in response to exercise and energy restriction may be mediated by the gut microbiome, yet causal evidence in humans remains limited. We used a 3-week exercise and energy restriction intervention to examine changes to the gut microbiome in otherwise healthy sedentary men and postmenopausal women with overweight/obesity. Intervention participants (n=18) reduced habitual energy intake by 5000 kcal/week and expended 2000 kcal/week in addition to habitual physical activity through treadmill walking at 70% V̇O2Peak. Control participants (n=12) maintained their usual lifestyle. Participants underwent dual-energy X-ray absorptiometry (DEXA), and samples of faeces, fasted venous blood, subcutaneous adipose tissue and skeletal muscle were collected. Faecal DNA was sequenced and profiled using shotgun metagenomics, Kraken2/Bracken and Human Microbiome Project Unified Metabolic Analysis Network 2 (HUMAnN2). The intervention significantly reduced body mass (mean Δ ± SD: -2.6 ± 1.5 kg), fat mass (-1.5 ± 1.3 kg), fasted insulin (-23.5 ± 38.1 pmol/l), leptin (-10.6 ± 7.3 ng/ml) and total cholesterol (-0.70 ± 0.42mmol/l) concentrations, and also improved insulin sensitivity (HOMA2%S (homeostatic model of assessment)). Despite these significant metabolic changes the gut microbiome was unchanged in terms of α and β diversity and relative abundance. Thus, despite clinically meaningful improvements in body composition and metabolic health, we found no evidence for changes to the gut microbiome. In conclusion early metabolic changes with weight loss in humans are unlikely to be mediated by changes to the gut microbiome. KEY POINTS: Changes to the gut microbiome could contribute to metabolic improvements associated with weight loss in humans, but there have been limited attempts to address this question using robust randomised controlled trials (RCTs). We used a parallel-group RCT to examine whether a 3-week combined energy intake restriction and vigorous-intensity exercise intervention in people with overweight and obesity was temporally associated with changes to gut microbiome taxonomic composition and functional potential, short-chain fatty acid concentrations and expression of genes related to host-microbiome interactions in skeletal muscle and subcutaneous adipose tissue. We found that the human gut microbiome remains unchanged in the face of an intensive energy intake restriction and vigorous exercise intervention that significantly improved body composition and metabolic health in people with overweight/obesity. These findings indicate that early metabolic changes with weight loss in humans are unlikely to be mediated by changes to the gut microbiome.

163 - Early Perturbations in Mitochondrial Metabolism and Bioenergetics Exerted by Trypanosoma cruzi Infection in Human Cardiomyocytes

While over 50 drugs have been approved by the FDA to treat breast cancer, there are no reliable methods for optimizing treatment regimens for individual patients. Currently, oncologists choose drug treatments based on expression levels of tumor cell signaling receptors (i.e. HER2, ER) and assess whether the treatment is effective after weeks or months of precious time have passed. Unfortunately, over one third of patients exhibit resistance to their initial treatment. The toxic side effects and morbidities resulting from suboptimal drug regimens could be eradicated by applying a personalized medicine approach to breast cancer treatment. This approach would allow clinicians to determine the optimal treatment plan for individual patients early on, at the time of diagnosis. While current methods track therapy response via changes in tumor size (i.e. MRI, mammography, ultrasound), changes in cell metabolism precede changes in tumor size and thus present an earlier marker of treatment response. Optical metabolic imaging (OMI) is sensitive to these early changes in metabolism by exploiting the intrinsic fluorescent properties of NAD(P)H and FAD, coenzymes of metabolic reactions. OMI endpoints include the optical redox ratio (the fluorescence intensity of NAD(P)H divided by the fluorescence intensity of FAD), as well as the fluorescence lifetimes of NAD(P)H and FAD. The redox ratio reflects the cellular redox state, and the fluorescence lifetimes of NAD(P)H and FAD report on the binding activity of these coenzymes. Additionally, OMI has the unique ability to measure these endpoints in individual cells, which allows for the detection of heterogeneous subpopulations of responsive or resistant cells within a tumor. OMI also allows for high-throughput screening of potential cancer drugs and drug combinations on patient biopsy samples cultured ex vivo. These samples are grown as “organoids” in a 3D matrix that mimics the natural tumor environment. We have demonstrated that OMI accurately predicts treatment response in organoids derived from breast cancer xenografts compared with gold standard tumor growth curves in vivo. We have also shown that OMI can measure drug response and detect heterogeneous cell populations in organoids derived from triple negative, ER+, and HER2+ human breast tumors. The ability of OMI to predict treatment response has also been demonstrated in the polyoma middle-T mouse model of breast cancer, which exhibits more cellular heterogeneity than cell line xenografts and also incorporates the influence of the immune system on cancer drug response. Preliminary data shows that OMI of organoids generated from biopsies of newly diagnosed breast cancer patients can accurately predict how the patient clinically responds to neoadjuvant treatment. This methodology could allow oncologists to determine the ideal treatment regimen for their patients at the time of diagnosis. Citation Format: Joe T. Sharick, Alex J. Walsh, Melinda E. Sanders, Ingrid Meszoely, Mary A. Hooks, Mark C. Kelley, Melissa C. Skala. Predicting clinical response in breast cancer using cellular-resolution optical metabolic imaging. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4241.

<h3>Background</h3> We are interested in mapping and understanding phenotypes that precede the development of overt signs of Huntington’s disease, in hopes of identifying pathways with the potential to be disease-modifying. Notably, the Huntington’s disease mutation is associated with early metabolic alterations of unknown aetiology in both humans and various model systems. Our own data suggest that widespread metabolic alterations occur very early in B6. HttQ111/Q7 mice, which precisely recapitulate the genetics of human HD patients. <h3>Aims</h3> We aim to understand which tissues reveal the earliest transcriptional and metabolic changes in the B6. HttQ111/Q7 mice. <h3>Methods</h3> We are applying stable isotope-based dynamic metabolic profiling (SiDMAP) to cells and tissues to quantify metabolic flux, and RNA sequencing (RNASeq) to quantify transcript abundance. <h3>Results/outcome</h3> In a cross-tissue metabolic flux study of 90-day-old mice using U13C-glucose as a stable tracer, we observe that the most robust metabolic changes are observed in the liver. Transcriptomic analysis of matched samples with RNASeq reveals that the liver has more genotype-sensitive transcripts at this stage than does the striatum, the most vulnerable tissue in HD. Based on these <i>in vivo</i>results, we hypothesise that very early changes in fatty acid synthesis, mobilisation and/or catabolism are occuring in the liver of HttQ111/+ mice. To study this hypothesis in more mechanistic detail, we have established a system of primary hepatocytes isolated from 90 day old mice fed one of 3 diets from weaning as a lipid-relevant perturbagen: high fat (65% kcal/fat), medium fat (45% kcal/fat) and normal chow (10% kcal/fat). We reason that examining phenotypes in HttQ111/Q7 cells at steady states may not be as informative as investigating their dynamic responses to chemically defined perturbations. Our phenotypic analysis <i>in vitro</i>includes quantifying metabolic flux using multiple flux tracers (1,2–13C2-glucose and U13C-palmitate). We are also collecting transcriptomic data from matched samples using RNASeq, in hopes of identifying genotype-sensitive flux changes that are associated with coherent transcriptional alterations. <h3>Conclusions</h3> We conclude that early transcriptional and metabolic flux changes occur in the livers of B6. HttQ111/Q7 mice.