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Previous studies in rodents suggest that mismatch between fetal and postnatal nutrition predisposes individuals to metabolic diseases. We hypothesized that in nonhuman primates (NHP), fetal programming of maternal undernutrition (MUN) persists postnatally with a dietary mismatch altering metabolic molecular systems that precede standard clinical measures. We used unbiased molecular approaches to examine response to a high fat, high-carbohydrate diet plus sugar drink (HFCS) challenge in NHP juvenile offspring of MUN pregnancies compared with controls (CON). Pregnant baboons were fed ad libitum (CON) or 30% calorie reduction from 0.16 gestation through lactation; weaned offspring were fed chow ad libitum . MUN offspring were growth restricted at birth. Liver, omental fat, and skeletal muscle gene expression, and liver glycogen, muscle mitochondria, and fat cell size were quantified. Before challenge, MUN offspring had lower body mass index (BMI) and liver glycogen, and consumed more sugar drink than CON. After HFCS challenge, MUN and CON BMIs were similar. Molecular analyses showed HFCS response differences between CON and MUN for muscle and liver, including hepatic splicing and unfolded protein response. Altered liver signaling pathways and glycogen content between MUN and CON at baseline indicate in utero programming persists in MUN juveniles. MUN catchup growth during consumption of HFCS suggests increased risk of obesity, diabetes, and cardiovascular disease. Greater sugar drink consumption in MUN demonstrates altered appetitive drive due to programming. Differences in blood leptin, liver glycogen, and tissue-specific molecular response to HFCS suggest MUN significantly impacts juvenile offspring ability to manage an energy rich diet.

Age is a prominent risk factor for cardiometabolic disease, often leading to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction exclusively resulting from physiological aging remain elusive. Previous research demonstrated age-related functional alterations in baboons, analogous to humans. The goal of this study is to identify early cardiac molecular alterations preceding functional adaptations, shedding light on the regulation of age-associated changes. Unbiased transcriptomics of left ventricle samples are performed from female baboons aged 7.5-22.1 years (human equivalent ≈30-88 years). Weighted-gene correlation network and pathway enrichment analyses are performed, with histological validation. Modules of transcripts negatively correlated with age implicated declined metabolism-oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggested a metabolic shift toward glucose-dependent anabolic pathways, including hexosamine biosynthetic pathway (HBP). This shift is associated with increased glycosaminoglycan synthesis, modification, precursor synthesis via HBP, and extracellular matrix accumulation, verified histologically. Upregulated extracellular matrix-induced signaling coincided with glycosaminoglycan accumulation, followed by cardiac hypertrophy-related pathways. Overall, these findings revealed a transcriptional shift in metabolism favoring glycosaminoglycan accumulation through HBP before cardiac hypertrophy. Unveiling this metabolic shift provides potential targets for age-related cardiac diseases, offering novel insights into early age-related mechanisms., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Objective: To investigate the outcomes of cochlear implantation in patients with TMTC2 -associated sensorineural hearing loss and auditory neuropathy/auditory dys-synchrony., Patients: Adult and pediatric cochlear implant (CI) patients followed in an academic center who tested positive for TMTC2 genetic variant rs35725509., Intervention: Cochlear implantation., Main Outcome Measures: Speech perception scores in quiet., Results: Ten CI patients were identified with TMTC2 variant rs35725509 out of 157 patients who underwent genetic testing (i.e., 6.3% of patients tested). All demonstrated progressive, bilateral hearing loss with severe-to-profound audiometric thresholds preoperatively. Pre-CI and 1-year post-CI speech recognition percent correct scores were compared. Post-CI speech perception (mean 61.0%, standard deviation 31.4%) was significantly higher than pre-CI speech perception (mean 21.0%, standard deviation 27.0%) ( p = 0.002). Individually, 9 of the 10 subjects experienced significant improvements in speech perception pre- to post-CI ( p < 0.05). Electrically evoked compound action potential measures were available for five patients, and all showed normal electrically evoked compound action potential thresholds., Conclusion: Patients with TMTC2 -associated sensorineural hearing loss and auditory neuropathy/auditory dys-synchrony have significantly improved speech perception outcomes with cochlear implantation and should be considered candidates for this intervention if there are no other contraindications., Competing Interests: The authors disclose no conflicts of interest., (Copyright © 2024, Otology & Neurotology, Inc.)

We previously demonstrated in baboons that maternal undernutrition (MUN), achieved by 70 % of control nutrition, impairs fetal liver function, but long-term changes associated with aging in this model remain unexplored. Here, we assessed clinical phenotypes of liver function, mitochondrial bioenergetics, and protein abundance in adult male and female baboons exposed to MUN during pregnancy and lactation and their control counterparts. Plasma liver enzymes were assessed enzymatically. Liver glycogen, choline, and lipid concentrations were quantified by magnetic resonance spectroscopy. Mitochondrial respiration in primary hepatocytes under standard culture conditions and in response to metabolic (1 mM glucose) and oxidative (100 µM H 2 O 2 ) stress were assessed with Seahorse XFe96. Hepatocyte mitochondrial membrane potential (MMP) and protein abundance were determined by tetramethylrhodamine ethyl ester staining and immunoblotting, respectively. Liver enzymes and metabolite concentrations were largely unaffected by MUN, except for higher aspartate aminotransferase levels in MUN offspring when male and female data were combined. Oxygen consumption rate, extracellular acidification rate, and MMP were significantly higher in male MUN offspring relative to control animals under standard culture. However, in females, cellular respiration was similar in control and MUN offspring. In response to low glucose challenge, only control male hepatocytes were resistant to low glucose-stimulated increase in basal and ATP-linked respiration. H 2 O 2 did not affect hepatocyte mitochondrial respiration. Protein markers of mitochondrial respiratory chain subunits, biogenesis, dynamics, and antioxidant enzymes were unchanged. Male-specific increases in mitochondrial bioenergetics in MUN offspring may be associated with increased energy demand in these animals. The similarity in systemic liver parameters suggests that changes in hepatocyte bioenergetics capacity precede detectable circulatory hepatic defects in MUN offspring and that the mitochondria may be an orchestrator of liver programming outcome., Competing Interests: Competing Interest The authors declare no competing interest.

Steady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWASs), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using non-human primate models., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The prefrontal cortex (PFC) has been implicated as a key brain region responsible for age-related cognitive decline. Little is known about aging-related molecular changes in PFC that may mediate these effects. To date, no studies have used untargeted discovery methods with integrated analyses to determine PFC molecular changes in healthy female primates. We quantified PFC changes associated with healthy aging in female baboons by integrating multiple omics data types (transcriptomics, proteomics, metabolomics) from samples across the adult age span. Our integrated omics approach using unbiased weighted gene co-expression network analysis to integrate data and treat age as a continuous variable, revealed highly interconnected known and novel pathways associated with PFC aging. We found Gamma-aminobutyric acid (GABA) tissue content associated with these signaling pathways, providing 1 potential biomarker to assess PFC changes with age. These highly coordinated pathway changes during aging may represent early steps for aging-related decline in PFC functions, such as learning and memory, and provide potential biomarkers to assess cognitive status in humans., Competing Interests: Declaration of Competing Interest The authors report no conflicts of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Steady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWAS), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using nonhuman primate models., Competing Interests: Declaration of interests The authors declare no competing interests.

Age is a prominent risk factor for cardiometabolic disease, and often leads to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction resulting from physiological aging per se remain elusive. Understanding these mechanisms requires biological models with optimal translation to humans. Previous research demonstrated that baboons undergo age-related reduction in ejection fraction and increased heart sphericity, mirroring changes observed in humans. The goal of this study was to identify early cardiac molecular alterations that precede functional adaptations, shedding light on the regulation of age-associated changes. We performed unbiased transcriptomics of left ventricle (LV) samples from female baboons aged 7.5-22.1 years (human equivalent ~30-88 years). Weighted-gene correlation network and pathway enrichment analyses were performed to identify potential age-associated mechanisms in LV, with histological validation. Myocardial modules of transcripts negatively associated with age were primarily enriched for cardiac metabolism, including oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggest upregulation of glucose uptake, pentose phosphate pathway, and hexosamine biosynthetic pathway (HBP), indicating a metabolic shift towards glucose-dependent anabolic pathways. Upregulation of HBP commonly results in increased glycosaminoglycan precursor synthesis. Transcripts involved in glycosaminoglycan synthesis, modification, and intermediate metabolism were also upregulated in older animals, while glycosaminoglycan degradation transcripts were downregulated with age. These alterations would promote glycosaminoglycan accumulation, which was verified histologically. Upregulation of extracellular matrix (ECM)-induced signaling pathways temporally coincided with glycosaminoglycan accumulation. We found a subsequent upregulation of cardiac hypertrophy-related pathways and an increase in cardiomyocyte width. Overall, our findings revealed a transcriptional shift in metabolism from catabolic to anabolic pathways that leads to ECM glycosaminoglycan accumulation through HBP prior to upregulation of transcripts of cardiac hypertrophy-related pathways. This study illuminates cellular mechanisms that precede development of cardiac hypertrophy, providing novel potential targets to remediate age-related cardiac diseases., Competing Interests: Conflicts of Interest: the author states there is no conflict of interest

Abstract: Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain.)

The liver is critical for functions that support metabolism, immunity, digestion, detoxification, and vitamin storage. Aging is associated with severity and poor prognosis of various liver diseases such as nonalcoholic fatty liver disease (NAFLD). Previous studies have used multi-omic approaches to study liver diseases or to examine the effects of aging on the liver. However, to date, no studies have used an integrated omics approach to investigate aging-associated molecular changes in the livers of healthy female nonhuman primates. The goal of this study was to identify molecular changes associated with healthy aging in the livers of female baboons ( Papio sp., n=35) by integrating multiple omics data types (transcriptomics, proteomics, metabolomics) from samples across the adult age span. To integrate omics data, we performed unbiased weighted gene co-expression network analysis (WGCNA), and the results revealed 3 modules containing 3,149 genes and 33 proteins were positively correlated with age, and 2 modules containing 37 genes and 216 proteins were negatively correlated with age. Pathway enrichment analysis showed that unfolded protein response (UPR) and endoplasmic reticulum (ER) stress were positively associated with age, whereas xenobiotic metabolism and melatonin and serotonin degradation pathways were negatively associated with age. The findings of our study suggest that UPR and a reduction in reactive oxygen species generated from serotonin degradation could protect the liver from oxidative stress during the aging process in healthy female baboons.

Fetal liver tissue collected from a nonhuman primate (NHP) baboon model of maternal nutrient reduction (MNR) at four gestational time points (90, 120, 140, and 165 days gestation [dG], term in the baboon is ∼185 dG) was used to quantify MNR effects on the fetal liver transcriptome. 28 transcripts demonstrated different expression patterns between MNR and control livers during the second half of gestation, a developmental period when the fetus undergoes rapid weight gain and fat accumulation. Differentially expressed transcripts were enriched for fatty acid oxidation and RNA splicing-related pathways. Increased RNA splicing activity in MNR was reflected in greater abundances of transcript splice variant isoforms in the MNR group. It can be hypothesized that the increase in splice variants is deployed in an effort to adapt to the poor in utero environment and ensure near-normal development and energy metabolism. This study is the first to study developmental programming across four critical gestational stages during primate fetal liver development and reveals a potentially novel cellular response mechanism mediating fetal programming in response to MNR.

The proteomic analysis of plasma holds great promise to advance precision medicine and identify biomarkers of disease. However, it is likely that many potential biomarkers circulating in plasma originate from other tissues and are only present in low abundances in the plasma. Accurate detection and quantification of low abundance proteins by standard mass spectrometry approaches remain challenging. In addition, it is difficult to link low abundance plasma proteins back to their specific tissues or organs of origin with confidence. To address these challenges, we developed a mass spectrometry approach based on the use of tandem mass tags (TMT) and a tissue reference sample. By applying this approach to nonhuman primate plasma samples, we were able to identify and quantify 820 proteins by using a kidney tissue homogenate as reference. On average, 643 ± 16 proteins were identified per plasma sample. About 58% of proteins identified in replicate experiments were identified both times. A ratio of 50 μg kidney protein to 10 μg plasma protein, and the use of the TMT label with the highest molecular weight (131) for the kidney reference yielded the largest number of proteins in the analysis, and identified low abundance proteins in plasma that are prominently found in the kidney. Overall, this methodology promises efficient quantification of plasma proteins potentially released from specific tissues, thereby increasing the number of putative disease biomarkers for future study.

Introduction: To gain insights into the mechanisms underlying distinct nonalcoholic fatty liver disease (NAFLD) histological phenotypes between children and adults, we compared hepatic gene expression profiles associated with NAFLD phenotypes between the two age groups., Methods: Histological characteristics of intra-operative liver biopsies from adolescents and adults undergoing bariatric surgery were assessed by the same pathologist using the non-alcoholic steatohepatitis (NASH) Clinical Research Network scoring system. Hepatic gene expression was measured by microarray analysis. Transcriptomic signatures of histological phenotypes between the two groups were compared, with significance defined as p-value <0.05 and a fold change >1.5., Results: In 67 adolescents and 76 adults, distribution of histological phenotypes was: not-NAFLD (controls) 51% vs 39%, NAFL 39% vs 37%, and NASH 10% vs 24%, respectively. There were 279 differentially expressed genes in adolescents and 213 in adults with NAFLD vs controls. In adolescents, transcriptomes for NAFL vs controls, and borderline vs definite NASH were undifferentiable, whereas in adults, NAFL and borderline NASH demonstrated a transcriptomic gradient between controls and definite NASH. When applied to adolescents, significant adult genes discriminated borderline and definite NASH from control and NAFL, but the majority of significant pediatric genes were not portable to adults. Genes associated with NASH in adolescents and adults showed some ontological consistency but notable differences., Conclusions: There is some similarity but major differences in the transcriptomic profiles associated with NAFLD between adolescents and adults with severe obesity. These data suggest different mechanisms contribute to the pathogenesis of NAFLD severity at different stages in life.

Maternal obesity (MO) during pregnancy is linked to increased and premature risk of age-related metabolic diseases in the offspring. However, the underlying molecular mechanisms still remain not fully understood. Using a well-established nonhuman primate model of MO, we analyzed tissue biopsies and plasma samples obtained from post-pubertal offspring (3-6.5 y) of MO mothers (n = 19) and from control animals born to mothers fed a standard diet (CON, n = 13). All offspring ate a healthy chow diet after weaning. Using untargeted gas chromatography-mass spectrometry metabolomics analysis, we quantified a total of 351 liver, 316 skeletal muscle, and 423 plasma metabolites. We identified 58 metabolites significantly altered in the liver and 46 in the skeletal muscle of MO offspring, with 8 metabolites shared between both tissues. Several metabolites were changed in opposite directions in males and females in both liver and skeletal muscle. Several tissue-specific and 4 shared metabolic pathways were identified from these dysregulated metabolites. Interestingly, none of the tissue-specific metabolic changes were reflected in plasma. Overall, our study describes characteristic metabolic perturbations in the liver and skeletal muscle in MO offspring, indicating that metabolic programming in utero persists postnatally, and revealing potential novel mechanisms that may contribute to age-related metabolic diseases later in life., (© 2022 The Authors. The FASEB Journal published by Wiley Periodicals LLC on behalf of Federation of American Societies for Experimental Biology.)

The purpose of this study was to identify molecular mechanisms by which the liver influences total lesion burden in a nonhuman primate model (NHP) of cardiovascular disease with acute and chronic feeding of a high cholesterol, high fat (HCHF) diet. Baboons (47 females, 64 males) were fed a HCHF diet for 2 years (y); liver biopsies were collected at baseline, 7 weeks (w) and 2y, and lesions were quantified in aortic arch, descending aorta, and common iliac at 2y. Unbiased weighted gene co-expression network analysis (WGCNA) revealed several modules of hepatic genes correlated with lesions at different time points of dietary challenge. Pathway and network analyses were performed to study the roles of hepatic module genes. More significant pathways were observed in males than females. In males, we found modules enriched for genes in oxidative phosphorylation at baseline, opioid signaling at 7w, and EIF2 signaling and HNF1A and HNF4A networks at baseline and 2y. One module enriched for fatty acid β oxidation pathway genes was found in males and females at 2y. To our knowledge, this is the first study of a large NHP cohort to identify hepatic genes that correlate with lesion burden. Correlations of baseline and 7w module genes with lesions at 2y were observed in males but not in females. Pathway analyses of baseline and 7w module genes indicate EIF2 signaling, oxidative phosphorylation, and μ-opioid signaling are possible mechanisms that predict lesion formation induced by HCHF diet consumption in males. Our findings of coordinated hepatic transcriptional response in male baboons but not female baboons indicate underlying molecular mechanisms differ between female and male primate atherosclerosis., Competing Interests: The authors have declared that no competing interests exist.

Background: Reliable and effective label-free quantification (LFQ) analyses are dependent not only on the method of data acquisition in the mass spectrometer, but also on the downstream data processing, including software tools, query database, data normalization and imputation. In non-human primates (NHP), LFQ is challenging because the query databases for NHP are limited since the genomes of these species are not comprehensively annotated. This invariably results in limited discovery of proteins and associated Post Translational Modifications (PTMs) and a higher fraction of missing data points. While identification of fewer proteins and PTMs due to database limitations can negatively impact uncovering important and meaningful biological information, missing data also limits downstream analyses (e.g., multivariate analyses), decreases statistical power, biases statistical inference, and makes biological interpretation of the data more challenging. In this study we attempted to address both issues: first, we used the MetaMorphues proteomics search engine to counter the limits of NHP query databases and maximize the discovery of proteins and associated PTMs, and second, we evaluated different imputation methods for accurate data inference. We used a generic approach for missing data imputation analysis without distinguising the potential source of missing data (either non-assigned m/z or missing values across runs)., Results: Using the MetaMorpheus proteomics search engine we obtained quantitative data for 1622 proteins and 10,634 peptides including 58 different PTMs (biological, metal and artifacts) across a diverse age range of NHP brain frontal cortex. However, among the 1622 proteins identified, only 293 proteins were quantified across all samples with no missing values, emphasizing the importance of implementing an accurate and statiscaly valid imputation method to fill in missing data. In our imputation analysis we demonstrate that Single Imputation methods that borrow information from correlated proteins such as Generalized Ridge Regression (GRR), Random Forest (RF), local least squares (LLS), and a Bayesian Principal Component Analysis methods (BPCA), are able to estimate missing protein abundance values with great accuracy., Conclusions: Overall, this study offers a detailed comparative analysis of LFQ data generated in NHP and proposes strategies for improved LFQ in NHP proteomics data., (© 2022. The Author(s).)

Gas chromatography-coupled mass spectrometry (GC-MS) has been used in biomedical research to analyze volatile, non-polar, and polar metabolites in a wide array of sample types. Despite advances in technology, missing values are still common in metabolomics datasets and must be properly handled. We evaluated the performance of ten commonly used missing value imputation methods with metabolites analyzed on an HR GC-MS instrument. By introducing missing values into the complete (i.e., data without any missing values) National Institute of Standards and Technology (NIST) plasma dataset, we demonstrate that random forest (RF), glmnet ridge regression (GRR), and Bayesian principal component analysis (BPCA) shared the lowest root mean squared error (RMSE) in technical replicate data. Further examination of these three methods in data from baboon plasma and liver samples demonstrated they all maintained high accuracy. Overall, our analysis suggests that any of the three imputation methods can be applied effectively to untargeted metabolomics datasets with high accuracy. However, it is important to note that imputation will alter the correlation structure of the dataset and bias downstream regression coefficients and p -values.

Chronic pain has become a global health problem contributing to years lived with disability and reduced quality of life. Advances in the clinical management of chronic pain have been limited due to incomplete understanding of the multiple risk factors and molecular mechanisms that contribute to the development of chronic pain. The Acute to Chronic Pain Signatures (A2CPS) Program aims to characterize the predictive nature of biomarkers (brain imaging, high-throughput molecular screening techniques, or "omics," quantitative sensory testing, patient-reported outcome assessments and functional assessments) to identify individuals who will develop chronic pain following surgical intervention. The A2CPS is a multisite observational study investigating biomarkers and collective biosignatures (a combination of several individual biomarkers) that predict susceptibility or resilience to the development of chronic pain following knee arthroplasty and thoracic surgery. This manuscript provides an overview of data collection methods and procedures designed to standardize data collection across multiple clinical sites and institutions. Pain-related biomarkers are evaluated before surgery and up to 3 months after surgery for use as predictors of patient reported outcomes 6 months after surgery. The dataset from this prospective observational study will be available for researchers internal and external to the A2CPS Consortium to advance understanding of the transition from acute to chronic postsurgical pain., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Berardi, Frey-Law, Sluka, Bayman, Coffey, Ecklund, Vance, Dailey, Burns, Buvanendran, McCarthy, Jacobs, Zhou, Wixson, Balach, Brummett, Clauw, Colquhoun, Harte, Harris, Williams, Chang, Waljee, Fisch, Jepsen, Laurent, Olivier, Langefeld, Howard, Fiehn, Jacobs, Dakup, Qian, Swensen, Lokshin, Lindquist, Caffo, Crainiceanu, Zeger, Kahn, Wager, Taub, Ford, Sutherland and Wandner.)

Background: Dietary high fructose (HFr) is a known metabolic disruptor contributing to development of obesity and diabetes in Western societies. Initial molecular changes from exposure to HFr on liver metabolism may be essential to understand the perturbations leading to insulin resistance and abnormalities in lipid and carbohydrate metabolism. We studied vervet monkeys (Clorocebus aethiops sabaeus) fed a HFr (n=5) or chow diet (n=5) for 6 weeks, and obtained clinical measures of liver function, blood insulin, cholesterol and triglycerides. In addition, we performed untargeted global transcriptomics, proteomics, and metabolomics analyses on liver biopsies to determine the molecular impact of a HFr diet on coordinated pathways and networks that differed by diet., Results: We show that integration of omics data sets improved statistical significance for some pathways and networks, and decreased significance for others, suggesting that multiple omics datasets enhance confidence in relevant pathway and network identification. Specifically, we found that sirtuin signaling and a peroxisome proliferator activated receptor alpha (PPARA) regulatory network were significantly altered in hepatic response to HFr. Integration of metabolomics and miRNAs data further strengthened our findings., Conclusions: Our integrated analysis of three types of omics data with pathway and regulatory network analysis demonstrates the usefulness of this approach for discovery of molecular networks central to a biological response. In addition, metabolites aspartic acid and docosahexaenoic acid (DHA), protein ATG3, and genes ATG7, and HMGCS2 link sirtuin signaling and the PPARA network suggesting molecular mechanisms for altered hepatic gluconeogenesis from consumption of a HFr diet., (© 2021. The Author(s).)

Background: Whole-exome sequencing (WES) can expedite research on genetic variation in non-human primate (NHP) models of human diseases. However, NHP-specific reagents for exome capture are not available. This study reports the use of human-specific capture reagents in WES for olive baboons, marmosets, and vervet monkeys., Methods: Exome capture was carried out using the SureSelect Human All Exon V6 panel from Agilent Technologies, followed by high-throughput sequencing. Capture of protein-coding genes and detection of single nucleotide variants were evaluated., Results: Exome capture and sequencing results showed that more than 97% of old world and 93% of new world monkey protein coding genes were detected. Single nucleotide variants were detected across the genomes and missense variants were found in genes associated with human diseases., Conclusions: A cost-effective approach based on commercial, human-specific reagents can be used to perform WES for the discovery of genetic variants in these NHP species., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Gas chromatography-mass spectrometry (GC-MS) platforms are typically run in electron ionization (EI) mode for mass spectral matching and metabolite annotation. With the advent of high resolution mass spectrometry (HRMS), soft ionization techniques such as chemical ionization (CI) may provide additional coverage for compound identification. We evaluated NIST SRM 1950 pooled plasma reference sample using a HRGC-MS instrument [GC-Orbitrap-MS with electron ionization (EI), positive chemical ionization (PCI), and negative CI (NCI) capabilities] for metabolite annotation and quantification to assess the suitability of the platform for routine discovery metabolomics. Using both open source and vendor workflows, we validated the spectral matches with an in-house spectral library (Wake Forest CPM GC-MS spectral and retention time libraries) of EI-MS and CI-MS/MS spectra obtained from chemical standards. We confidently [metabolomics standards initiative (MSI) confidence level 2] identified 263, 93, and 65 metabolites using EI, PCI, and NCI modes, respectively, of which 270 metabolites (64%) were validated using our Wake Forest CPM GC-MS spectral libraries. When compared to published LC-MS-based efforts using the same NIST SRM 1950 plasma sample, there was only 17% overlap between the two platforms. In addition, the metabolomics analysis of community approved standard human plasma demonstrated the ability of EI- and CI-MS modes of analysis using a HRGC-MS platform to enable reproducible and interoperable spectral matching.

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Recent advances in omics technologies have led to unprecedented efforts characterizing the molecular changes that underlie the development and progression of a wide array of complex human diseases, including cancer. As a result, multi-omics analyses-which take advantage of these technologies in genomics, transcriptomics, epigenomics, proteomics, metabolomics, and other omics areas-have been proposed and heralded as the key to advancing precision medicine in the clinic. In the field of precision oncology, genomics approaches, and, more recently, other omics analyses have helped reveal several key mechanisms in cancer development, treatment resistance, and recurrence risk, and several of these findings have been implemented in clinical oncology to help guide treatment decisions. However, truly integrated multi-omics analyses have not been applied widely, preventing further advances in precision medicine. Additional efforts are needed to develop the analytical infrastructure necessary to generate, analyze, and annotate multi-omics data effectively to inform precision medicine-based decision-making.

Background: Administration of amplitude modulated 27·12 MHz radiofrequency electromagnetic fields (AM RF EMF) by means of a spoon-shaped applicator placed on the patient's tongue is a newly approved treatment for advanced hepatocellular carcinoma (HCC). The mechanism of action of tumour-specific AM RF EMF is largely unknown., Methods: Whole body and organ-specific human dosimetry analyses were performed. Mice carrying human HCC xenografts were exposed to AM RF EMF using a small animal AM RF EMF exposure system replicating human dosimetry and exposure time. We performed histological analysis of tumours following exposure to AM RF EMF. Using an agnostic genomic approach, we characterized the mechanism of action of AM RF EMF., Findings: Intrabuccal administration results in systemic delivery of athermal AM RF EMF from head to toe at levels lower than those generated by cell phones held close to the body. Tumour shrinkage results from differentiation of HCC cells into quiescent cells with spindle morphology. AM RF EMF targeted antiproliferative effects and cancer stem cell inhibiting effects are mediated by Ca 2+ influx through Ca v 3·2 T-type voltage-gated calcium channels (CACNA1H) resulting in increased intracellular calcium concentration within HCC cells only., Interpretation: Intrabuccally-administered AM RF EMF is a systemic therapy that selectively block the growth of HCC cells. AM RF EMF pronounced inhibitory effects on cancer stem cells may explain the exceptionally long responses observed in several patients with advanced HCC. FUND: Research reported in this publication was supported by the National Cancer Institute's Cancer Centre Support Grant award number P30CA012197 issued to the Wake Forest Baptist Comprehensive Cancer Centre (BP) and by funds from the Charles L. Spurr Professorship Fund (BP). DWG is supported by R01 AA016852 and P50 AA026117., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Atherosclerotic plaques are characterized by an accumulation of macrophages, lipids, smooth muscle cells, and fibroblasts, and, in advanced stages, necrotic debris within the arterial walls. Dietary habits such as high fat and high cholesterol (HFHC) consumption are known risk factors for atherosclerosis. However, the key metabolic contributors to diet-induced atherosclerosis are far from established. Herein, we investigate the role of a 2-year HFHC diet challenge in the metabolic changes of development and progression of atherosclerosis. We used a non-human primate (NHP) model (baboons, n = 60) fed a HFHC diet for two years and compared metabolomic profiles in serum from animals on baseline chow with serum collected after the challenge diet using two-dimensional gas chromatography time-of-flight mass-spectrometry (2D GC-ToF-MS) for untargeted metabolomic analysis, to quantify metabolites that contribute to atherosclerotic lesion formation. Further, clinical biomarkers associated with atherosclerosis, lipoprotein measures, fat indices, and arterial plaque formation (lesions) were quantified. Using two chemical derivatization (i.e., silylation) approaches, we quantified 321 metabolites belonging to 66 different metabolic pathways, which revealed significantly different metabolic profiles of HFHC diet and chow diet fed baboon sera. We found heritability of two important metabolites, lactic acid and asparagine, in the context of diet-induced metabolic changes. In addition, abundance of cholesterol, lactic acid, and asparagine were sex-dependent. Finally, 35 metabolites correlated (R2, 0.068-0.271, P < 0.05) with total lesion burden assessed in three arteries (aortic arch, common iliac artery, and descending aorta) which could serve as potential biomarkers pending further validation. This study demonstrates the feasibility of detecting sex-specific and heritable metabolites in NHPs with diet-induced atherosclerosis using untargeted metabolomics allowing understanding of atherosclerotic disease progression in humans., Competing Interests: The authors have declared that no competing interests exist.

Rationale: Metabolomics analyses using gas chromatography/mass spectrometry (GC/MS)-based metabolomics are heavily impeded by the lack of high-resolution mass spectrometers and limited spectral libraries to complement the excellent chromatography that GC platforms offer, a challenge that is being addressed with the implementation of high-resolution (HR) platforms such as 1D-GC/Orbitrap-MS., Methods: We used serum samples from a non-human primate (NHP), a baboon (Papio hamadryas), with suitable quality controls to quantify the chemical space using an advanced HRMS platform for confident metabolite identification and robust quantification to assess the suitability of the platform for routine clinical metabolomics research. In a complementary approach, we also analyzed the same serum samples using two-dimensional gas chromatography/time-of-flight mass spectrometry (2D-GC/TOF-MS) for metabolite identification and quantification following established standard protocols., Results: Overall, the 2D-GC/TOF-MS (~5000 peaks per sample) and 1D-GC/Orbitrap-MS (~500 peaks per sample) analyses enabled identification and quantification of a total of 555 annotated metabolites from the NHP serum with a spectral similarity score R sim  ≥ 900 and signal-to-noise (S/N) ratio of >25. A common set of 30 metabolites with HMDB and KEGG IDs was quantified in the serum samples by both platforms where 2D-GC/TOF-MS enabled quantification of a total 384 metabolites (118 HMDB IDs) and 1D-GC/Orbitrap-MS analysis quantification of a total 200 metabolites (47 HMDB IDs). Thus, roughly 30-70% of the peaks remain unidentified or un-annotated across both platforms., Conclusions: Our study provides insights into the benefits and limitations of the use of a higher mass resolution and mass accuracy instrument for untargeted GC/MS-based metabolomics with multi-dimensional chromatography in future studies addressing clinical conditions or exposome studies., (© 2018 John Wiley & Sons, Ltd.)

With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics, or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing, and data archiving. The ultimate goal is towards the holistic realization of a 'systems biology' understanding of the biological question in hand. Commonly used approaches in these efforts are currently limited by the 3 i's - integration, interpretation, and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events, and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics, and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools, and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.

The hybridization capture of chromatin-associated proteins for proteomics (HyCCAPP) technology was initially developed to uncover novel DNA-protein interactions in yeast. It allows analysis of a target region of interest without the need for prior knowledge about likely proteins bound to the target region. This, in theory, allows HyCCAPP to be used to analyze any genomic region of interest, and it provides sufficient flexibility to work in different cell systems. This method is not meant to study binding sites of known transcription factors, a task better suited for Chromatin Immunoprecipitation (ChIP) and ChIP-like methods. The strength of HyCCAPP lies in its ability to explore DNA regions for which there is limited or no knowledge about the proteins bound to it. It can also be a convenient method to avoid biases (present in ChIP-like methods) introduced by protein-based chromatin enrichment using antibodies. Potentially, HyCCAPP can be a powerful tool to uncover truly novel DNA-protein interactions. To date, the technology has been predominantly applied to yeast cells or to high copy repeat sequences in mammalian cells. In order to become the powerful tool we envision, HyCCAPP approaches need to be optimized to efficiently capture single-copy loci in mammalian cells. Here, we present our adaptation of the initial yeast HyCCAPP capture protocol to human cell lines, and show that single-copy chromatin regions can be efficiently isolated with this modified protocol.

Introduction: Metabolomics is a promising approach for discovery of relevant biomarkers in cells, tissues, organs, and biofluids for disease identification and prediction. The field has mostly relied on blood-based biofluids (serum, plasma, urine) as non-invasive sources of samples as surrogates of tissue or organ-specific conditions. However, the tissue specificity of metabolites pose challenges in translating blood metabolic profiles to organ-specific pathophysiological changes, and require further downstream analysis of the metabolites., Objectives: As part of this project, we aim to develop and optimize an efficient extraction protocol for the analysis of kidney tissue metabolites representative of key primate metabolic pathways., Methods: Kidney cortex and medulla tissues of a baboon were homogenized and extracted using eight different extraction protocols including methanol/water, dichloromethane/methanol, pure methanol, pure water, water/methanol/chloroform, methanol/chloroform, methanol/acetonitrile/water, and acetonitrile/isopropanol/water. The extracts were analyzed by a two-dimensional gas chromatography time-of-flight mass-spectrometer (2D GC-ToF-MS) platform after methoximation and silylation., Results: Our analysis quantified 110 shared metabolites in kidney cortex and medulla tissues from hundreds of metabolites found among the eight different solvent extractions spanning low to high polarities. The results revealed that medulla is metabolically richer compared to the cortex. Dichloromethane and methanol mixture (3:1) yielded highest number of metabolites across both the tissue types. Depending on the metabolites of interest, tissue type, and the biological question, different solvents can be used to extract specific groups of metabolites., Conclusion: This investigation provides insights into selection of extraction solvents for detection of classes of metabolites in renal cortex and medulla, which is fundamentally important for identification of prognostic and diagnostic metabolic kidney biomarkers for future therapeutic applications.

Rodent and nonhuman primate studies indicate that developmental programming by reduced perinatal nutrition negatively impacts life course cardio-metabolic health. We have developed a baboon model in which we feed control mothers (CON) ad libitum while nutrient restricted mothers are fed 70% of ad libitum global feed in pregnancy and lactation. Offspring of nutrient restricted mothers are intrauterine growth restricted (IUGR) at term. By 3.5 years IUGR baboons showed signs of insulin resistance, indicating a pre-diabetic phenotype, in contrast to healthy CON offspring. We hypothesized that a novel breath analysis approach would provide markers of the altered cardio-metabolic state in a non-invasive manner. Here we assess whether exhaled breath volatile organic compounds (VOCs) collected from this unique cohort of juvenile baboons with documented cardio-metabolic dysfunction resulting from in utero programming can be detected from their breath signatures. Breath was collected from male and female CON and IUGR baboons at 4.8 ± 0.2 years (human equivalent ∼13 years). Breath VOCs were quantified using a two-dimensional gas chromatography mass spectrometer. Two-way ANOVA, on 76 biologically relevant VOCs identified 27 VOCs (p < 0.05) with altered abundances between groups (sex, birthweight, and sex x birthweight). The 27 VOCs included 2-pentanone, 2-octanone, 2,2,7,7-tetramethyloctane and 3-methyl-1-heptene, which have not previously been associated with cardio-metabolic disease. Unsupervised principal component analysis of these VOCs could discriminate the four clusters defining males, females, CON and IUGR. This study, which is the first to assess quantifiable breath signatures associated with cardio-metabolic programing for any model of IUGR, demonstrates the translational value of this unique model to identify metabolites of programmed cardio-metabolic dysfunction in breath signatures. Future studies are required to validate the translatability of these findings to humans.

Background: Sensorineural hearing loss (SNHL) is a common form of hearing loss that can be inherited or triggered by environmental insults; auditory neuropathy spectrum disorder (ANSD) is a SNHL subtype with unique diagnostic criteria. The genetic factors associated with these impairments are vast and diverse, but causal genetic factors are rarely characterized., Methods: A family dyad, both cochlear implant recipients, presented with a hearing history of bilateral, progressive SNHL, and ANSD. Whole-exome sequencing was performed to identify coding sequence variants shared by both family members, and screened against genes relevant to hearing loss and variants known to be associated with SNHL and ANSD., Results: Both family members are successful cochlear implant users, demonstrating effective auditory nerve stimulation with their devices. Genetic analyses revealed a mutation (rs35725509) in the TMTC2 gene, which has been reported previously as a likely genetic cause of SNHL in another family of Northern European descent., Conclusion: This study represents the first confirmation of the rs35725509 variant in an independent family as a likely cause for the complex hearing loss phenotype (SNHL and ANSD) observed in this family dyad., (© 2018 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.)

Background: Metabolic diseases such as obesity and diabetes are associated with changes in high-density lipoprotein (HDL) particles, including changes in particle size and protein composition, often resulting in abnormal function. Recent studies suggested that patients with non-alcoholic fatty liver disease (NAFLD), including individuals with non-alcoholic steatohepatitis (NASH), have smaller HDL particles when compared to individuals without liver pathologies. However, no studies have investigated potential changes in HDL particle protein composition in patients with NAFLD, in addition to changes related to obesity, to explore putative functional changes of HDL which may increase the risk of cardiovascular complications., Methods: From a cohort of morbidly obese females who were diagnosed with simple steatosis (SS), NASH, or normal liver histology, we selected five matched individuals from each condition for a preliminary pilot HDL proteome analysis. HDL particles were enriched using size-exclusion chromatography, and the proteome of the resulting fraction was analyzed by liquid chromatography tandem mass spectrometry. Differences in the proteomes between the three conditions (normal, SS, NASH) were assessed using label-free quantitative analysis. Gene ontology term analysis was performed to assess the potential impact of proteomic changes on specific functions of HDL particles., Results: Of the 95 proteins identified, 12 proteins showed nominally significant differences between the three conditions. Gene ontology term analysis revealed that severity of the liver pathology may significantly impact the anti-thrombotic functions of HDL particles, as suggested by changes in the abundance of HDL-associated proteins such as antithrombin III and plasminogen., Conclusions: The pilot data from this study suggest that changes in the HDL proteome may impact the functionality of HDL particles in NAFLD and NASH patients. These proteome changes may alter cardio-protective properties of HDL, potentially contributing to the increased cardiovascular disease risk in affected individuals. Further validation of these protein changes by orthogonal approaches is key to confirming the role of alterations in the HDL proteome in NAFLD and NASH. This will help elucidate the mechanistic effects of the altered HDL proteome on cardioprotective properties of HDL particles.

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the United States. Human epidemiological studies provide challenges for understanding mechanisms that regulate initiation and progression of CVD due to variation in lifestyle, diet, and other environmental factors. Studies describing metabolic and physiologic aspects of CVD, and those investigating genetic and epigenetic mechanisms influencing CVD initiation and progression, have been conducted in multiple Old World nonhuman primate (NHP) species. Major advantages of NHPs as models for understanding CVD are their genetic, metabolic, and physiologic similarities with humans, and the ability to control diet, environment, and breeding. These NHP species are also genetically and phenotypically heterogeneous, providing opportunities to study gene by environment interactions that are not feasible in inbred animal models. Each Old World NHP species included in this review brings unique strengths as models to better understand human CVD. All develop CVD without genetic manipulation providing multiple models to discover genetic variants that influence CVD risk. In addition, as each of these NHP species age, their age-related comorbidities such as dyslipidemia and diabetes are accelerated proportionally 3 to 4 times faster than in humans.In this review, we discuss current CVD-related research in NHPs focusing on selected aspects of CVD for which nonprimate model organism studies have left gaps in our understanding of human disease. We include studies on current knowledge of genetics, epigenetics, calorie restriction, maternal calorie restriction and offspring health, maternal obesity and offspring health, nonalcoholic steatohepatitis and steatosis, Chagas disease, microbiome, stem cells, and prevention of CVD., (© The Author(s) 2017. Published by Oxford University Press on behalf of the National Academy of Sciences. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Shotgun proteomics utilizes a database search strategy to compare detected mass spectra to a library of theoretical spectra derived from reference genome information. As such, the robustness of proteomics results is contingent upon the completeness and accuracy of the gene annotation in the reference genome. For animal models of disease where genomic annotation is incomplete, such as non-human primates, proteogenomic methods can improve the detection of proteins by incorporating transcriptional data from RNA-Seq to improve proteomics search databases used for peptide spectral matching. Customized search databases derived from RNA-Seq data are capable of identifying unannotated genetic and splice variants while simultaneously reducing the number of comparisons to only those transcripts actively expressed in the tissue., Results: We collected RNA-Seq and proteomic data from 10 vervet monkey liver samples and used the RNA-Seq data to curate sample-specific search databases which were analyzed in the program Morpheus. We compared these results against those from a search database generated from the reference vervet genome. A total of 284 previously unannotated splice junctions were predicted by the RNA-Seq data, 92 of which were confirmed by peptide spectral matches. More than half (53/92) of these unannotated splice variants had orthologs in other non-human primates, suggesting that failure to match these peptides in the reference analyses likely arose from incomplete gene model information. The sample-specific databases also identified 101 unique peptides containing single amino acid substitutions which were missed by the reference database. Because the sample-specific searches were restricted to actively expressed transcripts, the search databases were smaller, more computationally efficient, and identified more peptides at the empirically derived 1 % false discovery rate., Conclusion: Proteogenomic approaches are ideally suited to facilitate the discovery and annotation of proteins in less widely studies animal models such as non-human primates. We expect that these approaches will help to improve existing genome annotations of non-human primate species such as vervet.

The centromere is the chromosomal locus where the kinetochore forms and is critical for ensuring proper segregation of sister chromatids during cell division. A substantial amount of effort has been devoted to understanding the characteristic features and roles of the centromere, yet some fundamental aspects of the centromere, such as the complete list of elements that define it, remain obscure. It is well-known that human centromeres include a highly repetitive class of DNA known as alpha satellite, or alphoid, DNA. We present here the first DNA-centric examination of human protein-alpha satellite interactions, employing an approach known as HyCCAPP (hybridization capture of chromatin-associated proteins for proteomics) to identify the protein components of alphoid chromatin in a human cell line. Using HyCCAPP, cross-linked alpha satellite chromatin was isolated from cell lysate, and captured proteins were analyzed via mass spectrometry. After being compared to proteins identified in control pulldown experiments, 90 proteins were identified as enriched at alphoid DNA. This list included many known centromere-binding proteins in addition to multiple novel alpha satellite-binding proteins, such as LRIF1, a heterochromatin-associated protein. The ability of HyCCAPP to reveal both known as well as novel alphoid DNA-interacting proteins highlights the validity and utility of this approach.

Background: Although dichotomous criteria for the metabolic syndrome (MetS) appear heritable, it is not known whether MetS severity as assessed by a continuous MetS score is heritable and whether this varies by race., Methods and Results: We used SOLAR (Sequential Oligogenic Linkage Analysis Routines) to evaluate heritability of Adult Treatment Panel-III MetS and a sex- and race-specific MetS severity Z score among 3 large familial cohorts: the JHS (Jackson Heart Study, 1404 black participants), TOPS (Take Off Pounds Sensibly, 1947 white participants), and PLRS (Princeton Lipid Research Study, 229 black and 527 white participants). Heritability estimates were larger for Adult Treatment Panel-III MetS among black compared with white cohort members (JHS 0.48; 95% confidence interval [CI], 0.28-0.68 and PLRS blacks 0.93 [95% CI, 0.73-1.13] versus TOPS 0.21 [95% CI, -0.18 to 0.60] and PLRS whites 0.27 [95% CI, -0.04 to 0.58]). The difference by race narrowed when assessing heritability of the MetS severity score (JHS 0.52 [95% CI, 0.38, 0.66] and PLRS blacks 0.64 [95% CI, 0.13-1.15] versus TOPS 0.23 [95% CI, 0.15-0.31] and PLRS whites 0.60 [95% CI, 0.33-0.87]). There was a high degree of genetic and phenotypic correlation between MetS severity and the individual components of MetS among all groups, although the genetic correlations failed to reach statistical significance among PLRS blacks. Meta-analyses revealed a combined heritability estimate for Adult Treatment Panel-III MetS of 0.24 (95% CI, 0.11-0.36) and for the MetS severity score of 0.50 (95% CI, -0.05 to 0.99)., Conclusions: MetS severity seems highly heritable among whites and blacks. This continuous MetS severity Z score may provide a more useful means of characterizing phenotypic MetS in genetic studies by minimizing racial differences., (© 2017 American Heart Association, Inc.)

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10 -8 ; false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.

Importance: Sensorineural hearing loss (SNHL) is commonly caused by conditions that affect cochlear structures or the auditory nerve, and the genes identified as causing SNHL to date only explain a fraction of the overall genetic risk for this debilitating disorder. It is likely that other genes and mutations also cause SNHL., Objective: To identify a candidate gene that causes bilateral, symmetric, progressive SNHL in a large multigeneration family of Northern European descent., Design, Setting, and Participants: In this prospective genotype and phenotype study performed from January 1, 2006, through April 1, 2016, a 6-generation family of Northern European descent with 19 individuals having reported early-onset hearing loss suggestive of an autosomal dominant inheritance were studied at a tertiary academic medical center. In addition, 179 unrelated adult individuals with SNHL and 186 adult individuals reporting nondeafness were examined., Main Outcomes and Measures: Sensorineural hearing loss., Results: Nine family members (5 women [55.6%]) provided clinical audiometric and medical records that documented hearing loss. The hearing loss is characterized as bilateral, symmetric, progressive SNHL that reached severe to profound loss in childhood. Audiometric configurations demonstrated a characteristic dip at 1000 to 2000 Hz. All affected family members wear hearing aids or have undergone cochlear implantation. Exome sequencing and linkage and association analyses identified a fully penetrant sequence variant (rs35725509) on chromosome 12q21 (logarithm of odds, 3.3) in the TMTC2 gene region that segregates with SNHL in this family. This gene explains the SNHL occurrence in this family. The variant is also associated with SNHL in a cohort of 363 unrelated individuals (179 patients with confirmed SNHL and 184 controls, P = 7 × 10-4)., Conclusions and Relevance: A previously uncharacterized gene, TMTC2, has been identified as a candidate for causing progressive SNHL in humans. This finding identifies a novel locus that causes autosomal dominant SNHL and therefore a more detailed understanding of the genetic basis of SNHL. Because TMTC2 has not been previously reported to regulate auditory function, the discovery reveals a potentially new, uncharacterized mechanism of hearing loss.

Currently available methods for interrogating DNA-protein interactions at individual genomic loci have significant limitations, and make it difficult to work with unmodified cells or examine single-copy regions without specific antibodies. In this study, we describe a physiological application of the Hybridization Capture of Chromatin-Associated Proteins for Proteomics (HyCCAPP) methodology we have developed. Both novel and known locus-specific DNA-protein interactions were identified at the ENO2 and GAL1 promoter regions of Saccharomyces cerevisiae, and revealed subgroups of proteins present in significantly different levels at the loci in cells grown on glucose versus galactose as the carbon source. Results were validated using chromatin immunoprecipitation. Overall, our analysis demonstrates that HyCCAPP is an effective and flexible technology that does not require specific antibodies nor prior knowledge of locally occurring DNA-protein interactions and can now be used to identify changes in protein interactions at target regions in the genome in response to physiological challenges., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Polycystic ovary syndrome (PCOS) is a common, highly heritable complex disorder of unknown aetiology characterized by hyperandrogenism, chronic anovulation and defects in glucose homeostasis. Increased luteinizing hormone relative to follicle-stimulating hormone secretion, insulin resistance and developmental exposure to androgens are hypothesized to play a causal role in PCOS. Here we map common genetic susceptibility loci in European ancestry women for the National Institutes of Health PCOS phenotype, which confers the highest risk for metabolic morbidities, as well as reproductive hormone levels. Three loci reach genome-wide significance in the case-control meta-analysis, two novel loci mapping to chr 8p23.1 [Corrected] and chr 11p14.1, and a chr 9q22.32 locus previously found in Chinese PCOS. The same chr 11p14.1 SNP, rs11031006, in the region of the follicle-stimulating hormone B polypeptide (FSHB) gene strongly associates with PCOS diagnosis and luteinizing hormone levels. These findings implicate neuroendocrine changes in disease pathogenesis.

DNA-protein interactions play critical roles in the control of genome expression and other fundamental processes. An essential element in understanding how these systems function is to identify their molecular components. We present here a novel strategy, Hybridization Capture of Chromatin Associated Proteins for Proteomics (HyCCAPP), to identify proteins that are interacting with any given region of the genome. This technology identifies and quantifies the proteins that are specifically interacting with a genomic region of interest by sequence-specific hybridization capture of the target region from in vivo cross-linked chromatin, followed by mass spectrometric identification and quantification of associated proteins. We demonstrate the utility of HyCCAPP by identifying proteins associated with three multicopy and one single-copy loci in yeast. In each case, a locus-specific pattern of target-associated proteins was revealed. The binding of previously unknown proteins was confirmed by ChIP in 11 of 17 cases. The identification of many previously known proteins at each locus provides strong support for the ability of HyCCAPP to correctly identify DNA-associated proteins in a sequence-specific manner, while the discovery of previously unknown proteins provides new biological insights into transcriptional and regulatory processes at the target locus.

DNA-protein interactions are central to gene expression and chromatin regulation and have become one of the main focus areas of the ENCODE consortium. Advances in mass spectrometry and associated technologies have facilitated studies of these interactions, revealing many novel DNA-interacting proteins and histone posttranslational modifications. Proteins interacting at a single locus or at multiple loci have been targeted in these recent studies, each requiring a separate analytical strategy for isolation and analysis of DNA-protein interactions. The enrichment of target chromatin fractions occurs via a number of methods including immunoprecipitation, affinity purification, and hybridization, with the shared goal of using proteomics approaches as the final readout. The result of this is a number of exciting new tools, with distinct strengths and limitations that can enable highly robust and novel chromatin studies when applied appropriately. The present review compares and contrasts these methods to help the reader distinguish the advantages of each approach., (Copyright © 2014 the American Physiological Society.)

The Human Genome Project was expected to individualize medicine by rapidly advancing knowledge of common complex disease through discovery of disease-causing genetic variants. However, this has proved challenging. Although linkage analysis has identified replicated chromosomal regions, subsequent detection of causal variants for complex traits has been limited. One explanation for this difficulty is that utilization of association to follow up linkage is problematic given that linkage and association are not required to co-occur. Indeed, co-occurrence is likely to occur only in special circumstances, such as Mendelian inheritance, but cannot be universally expected. To overcome this problem, we propose a novel method, the Variant Impact On Linkage Effect Test (VIOLET), which differs from other quantitative methods in that it is designed to follow up linkage by identifying variants that influence the variance explained by a quantitative trait locus. VIOLET's performance was compared with measured genotype and combined linkage association in two data sets with quantitative traits. Using simulated data, VIOLET had high power to detect the causal variant and reduced false positives compared with standard methods. Using real data, VIOLET identified a single variant, which explained 24% of linkage; this variant exhibited only nominal association (P=0.04) using measured genotype and was not identified by combined linkage association. These results demonstrate that VIOLET is highly specific while retaining low false-negative results. In summary, VIOLET overcomes a barrier to gene discovery and thus may be broadly applicable to identify underlying genetic etiology for traits exhibiting linkage.

Background: Next generation sequencing and advances in genomic enrichment technologies have enabled the discovery of the full spectrum of variants from common to rare alleles in the human population. The application of such technologies can be limited by the amount of DNA available. Whole genome amplification (WGA) can overcome such limitations. Here we investigate applicability of using WGA by comparing SNP and INDEL variant calls from a single genomic/WGA sample pair from two capture separate experiments: a 50 Mbp whole exome capture and a custom capture array of 4 Mbp region on chr12., Results: Our results comparing variant calls derived from genomic and WGA DNA show that the majority of variant SNP and INDEL calls are common to both callsets, both at the site and genotype level and suggest that allele bias plays a minimal role when using WGA DNA in re-sequencing studies., Conclusions: Although the results of this study are based on a limited sample size, they suggest that using WGA DNA allows the discovery of the vast majority of variants, and achieves high concordance metrics, when comparing to genomic DNA calls.

Background: Metabolic syndrome (MetS) is an aberration associated with increased risk for cancer and inflammation. Adiponectin, an adipocyte-produced abundant protein hormone, has countering effect on the diabetogenic and atherogenic components of MetS. Plasma levels of adiponectin are negatively correlated with onset of cancer and cancer patient mortality. We previously performed microsatellite linkage analyses using adiponectin as a surrogate marker and revealed two QTLs on chr5 (5p14) and chr14 (14q13)., Methods: Using individuals from 85 extended families that contributed to the linkage and who were measured for 42 clinical and biologic MetS phenotypes, we tested QTL-based SNP associations, peripheral white blood cell (PWBC) gene expression, and the effects of cis-acting SNPs on gene expression to discover genomic elements that could affect the pathophysiology and complications of MetS., Results: Adiponectin levels were found to be highly intercorrelated phenotypically with the majority of MetS traits. QTL-specific haplotype-tagging SNPs associated with MetS phenotypes were annotated to 14 genes whose function could influence MetS biology as well as oncogenesis or inflammation. These were mechanistically categorized into four groups: cell-cell adhesion and mobility, signal transduction, transcription and protein sorting. Four genes were highly prioritized: cadherin 18 (CDH18), myosin X (MYO10), anchor protein 6 of AMPK (AKAP6), and neuronal PAS domain protein 3 (NPAS3). PWBC expression was detectable only for the following genes with multi-organ or with multi-function properties: NPAS3, MARCH6, MYO10 and FBXL7. Strong evidence of cis-effects on the expression of MYO10 in PWBC was found with SNPs clustered near the gene's transcription start site. MYO10 expression in PWBC was marginally correlated with body composition (p = 0.065) and adipokine levels in the periphery (p = 0.064). Variants of genes AKAP6, NPAS3, MARCH6 and FBXL7 have been previously reported to be associated with insulin resistance, inflammatory markers or adiposity studies using genome-wide approaches whereas associations of CDH18 and MYO10 with MetS traits have not been reported before., Conclusions: Adiponectin QTLs-based SNP association and mRNA expression identified genes that could mediate the association between MetS and cancer or inflammation.

Background: Fatty acid-binding proteins (FABPs) play regulatory roles at the nexus of lipid metabolism and signaling. Dyslipidemia in clinical manifestation frequently co-occurs with obesity, insulin resistance and hypertension in the Metabolic Syndrome (MetS). Animal studies have suggested FABPs play regulatory roles in expressing MetS phenotypes. In our family cohort of Northern European descent, transcript levels in peripheral white blood cells (PWBCs) of a key FABPs, FABP3, is correlated with the MetS leading components. However, evidence supporting the functions of FABPs in humans using genetic approaches has been scarce, suggesting FABPs may be under epigenetic regulation. The objective of this study was to test the hypothesis that CpG methylation status of a key regulator of lipid homeostasis, FABP3, is a quantitative trait associated with status of MetS phenotypes in humans., Methods: We used a mass-spec based quantitative method, EpiTYPER®, to profile a CpG island that extends from the promoter to the first exon of the FABP3 gene in our family-based cohort of Northern European descent (n=517). We then conducted statistical analysis of the quantitative relationship of CpG methylation and MetS measures following the variance-component association model. Heritability of each methylation and the effect of age and sex on CpG methylation were also assessed in our families., Results: We find that methylation levels of individual CpG units and the regional average are heritable and significantly influenced by age and sex. Regional methylation was strongly associated with plasma total cholesterol (p=0.00028) and suggestively associated with LDL-cholesterol (p=0.00495). Methylation at individual units was significantly associated with insulin sensitivity, lipid particle sizing and diastolic blood pressure (p<0.0028, corrected for multiple testing for each trait). Peripheral white blood cell (PWBC) expression of FABP3 in a separate group of subjects (n=128) negatively correlated with adverse profiles of metabolism (βWHR=-0.72; βLDL-c=-0.53) while positively correlated with plasma adiponectin (β=0.24). Further, we show that differential methylation of FABP3 affects binding activity with nuclear proteins from heart tissue. This region that we found under methylation regulation overlaps with a region actively modified by histone codes in the newly available ENCODE data., Conclusions: Our findings suggest that DNA methylation of FABP3 strongly influences MetS, and this may have important implications for cardiovascular disease.

Changes in mitochondrial bioenergetics have been proposed to be critical for triggering and effecting anesthetic-induced preconditioning (APC) against cardiac ischemia and reperfusion injury. The objective of this study was to analyze changes in mitochondrial protein levels and link those changes to potential functional changes. A (18)O-labeling method was applied for relative comparison of cardiac mitochondrial samples from control and isoflurane exposed rats before and after ischemia and reperfusion. Wistar rats were exposed to isoflurane for 30 min (APC) or did not receive the anesthetic (control). Rats were subjected to 30 min coronary occlusion and 15 min reperfusion without (ischemia) or after APC (ischemia + APC). The following comparisons were made: control vs. APC, control vs. ischemia, and APC vs. ischemia + APC. Proteins were analyzed by liquid chromatography-mass spectrometry. A total of 98 proteins currently annotated as mitochondrial proteins in the UniProt database were positively identified from three replicate experiments. Most of the changes during APC and ischemia occur in complexes of the electron transport chain. Overall, fewer changes in ETC complexes were found when comparing APC with APC + ischemia than when comparing control and ischemia. This corresponds to the preservation of bioenergetics due to APC after ischemia and reperfusion as indicated by preserved ATP level and generation. APC itself induced changes in complex I, but those changes were not correlated with activity changes in mitochondria after APC. Thus, a proteomic mass spectral approach does not only assess quantitative changes without prior knowledge of proteins, but also allows insight into the mechanisms of ischemia and reperfusion injury and APC.

Copy number variation (CNV), generated through duplication or deletion events that affect one or more loci, is widespread in the human genomes and is often associated with functional consequences that may include changes in gene expression levels or fusion of genes. Genome-wide association studies indicate that some disease phenotypes and physiological pathways might be impacted by CNV in a small number of characterized genomic regions. However, the pervasiveness and full impact of such variation remains unclear. Suitable analytic methods are needed to thoroughly mine human genomes for genomic structural variation, and to explore the interplay between observed CNV and disease phenotypes, but many medical researchers are unfamiliar with the features and nuances of recently developed technologies for detecting CNV. In this article, we evaluate a suite of commonly used and recently developed approaches to uncovering genome-wide CNVs and discuss the relative merits of each.