Toward a road map for global -omics: a primer on -omic technologies

Gene-environment interactions that influence CVD, lipid traits, obesity, diabetes, and hypertension appear to be able to influence gene therapy

Most mind boggling diseases are accepted to be impacted by both genetic and environmental elements. As of late, there has been a flood in the improvement of different methodologies, concentrate on plans, and measurable and logical techniques to examine gene-environment cooperations (G × Es) in enormous scope studies including human populaces. The many-sided exchange between genetic elements and environmental openings has long charmed the consideration of clinicians and researchers looking to grasp the complicated starting points of diseases. While single variables can add to disease, the blend of genetic variations and environmental openings frequently decides disease risk. The fundamental point of this paper is to talk about the Gene-Environment Associations That Impact CVD, Lipid Characteristics, Obesity, Diabetes, and Hypertension Have all the earmarks of being Ready to Impact Gene Therapy. This survey paper investigates the meaning of gene-environment collaborations (G × E) in disease advancement. The intricacy of genetic and environmental communications in disease causation is explained, underlining the multifactorial idea of many circumstances. The job of gene-environment cooperations in cardiovascular disease, lipid digestion, diabetes, obesity, and hypertension is investigated. This audit fixates on Gene by Environment (G × E) collaborations, investigating their importance in disease etiology.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Application of Advanced Technologies-Nanotechnology, Genomics Technology, and 3D Printing Technology-In Precision Anesthesia: A Comprehensive Narrative Review

There has been increasing interest and rapid developments in precision medicine, which is a new medical concept and model based on individualized medicine with the joint application of genomics, bioinformatics engineering, and big data science. By applying numerous emerging medical frontier technologies, precision medicine could allow individualized and precise treatment for specific diseases and patients. This article reviews the application and progress of advanced technologies in the anesthesiology field, in which nanotechnology and genomics can provide more personalized anesthesia protocols, while 3D printing can yield more patient-friendly anesthesia supplies and technical training materials to improve the accuracy and efficiency of decision-making in anesthesiology. The objective of this manuscript is to analyze the recent scientific evidence on the application of nanotechnology in anesthesiology. It specifically focuses on nanomedicine, precision medicine, and clinical anesthesia. In addition, it also includes genomics and 3D printing. By studying the current research and advancements in these advanced technologies, this review aims to provide a deeper understanding of the potential impact of these advanced technologies on improving anesthesia techniques, personalized pain management, and advancing precision medicine in the field of anesthesia.

Amino Acid-Related Metabolic Signature in Obese Children and Adolescents

The growing interest in metabolomics has spread to the search for suitable predictive biomarkers for complications related to the emerging issue of pediatric obesity and its related cardiovascular risk and metabolic alteration. Indeed, several studies have investigated the association between metabolic disorders and amino acids, in particular branched-chain amino acids (BCAAs). We have performed a revision of the literature to assess the role of BCAAs in children and adolescents' metabolism, focusing on the molecular pathways involved. We searched on Pubmed/Medline, including articles published until February 2022. The results have shown that plasmatic levels of BCAAs are impaired already in obese children and adolescents. The relationship between BCAAs, obesity and the related metabolic disorders is explained on one side by the activation of the mTORC1 complex-that may promote insulin resistance-and on the other, by the accumulation of toxic metabolites, which may lead to mitochondrial dysfunction, stress kinase activation and damage of pancreatic cells. These compounds may help in the precocious identification of many complications of pediatric obesity. However, further studies are still needed to better assess if BCAAs may be used to screen these conditions and if any other metabolomic compound may be useful to achieve this goal.

Measuring Clinical, Biological, and Behavioral Variables to Elucidate Trajectories of Patient (Reported) Outcomes: The PROFILES Registry

To take cancer survivorship research to the next level, it's important to gain insight in trajectories of changing patient (reported) outcomes and impaired recovery after cancer. This is needed as the number of survivors is increasing and a large proportion is confronted with changing health after treatment. Mechanistic research can facilitate the development of personalized risk-stratified follow-up care and tailored interventions to promote healthy cancer survivorship. We describe how these trajectories can be studied by taking the recently extended Dutch population-based PROFILES (Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship) registry as an example. PROFILES combines longitudinal assessment of patient-reported outcomes with novel, ambulatory and objective measures (e.g., activity trackers; blood draws; hair samples; online food diaries; online cognitive tests; weighing scales; online symptoms assessment), and cancer registry and pharmacy databases. Furthermore, we discuss methods to optimize the use of a multidomain data collection like return of individual results to participants which may not only improve patient empowerment but also long-term cohort retention. Also, advanced statistical methods are needed to handle high-dimensional longitudinal data (with missing values) and provide insight into trajectories of changing patient (reported) outcomes after cancer. Our coded data can be used by academic researchers around the world. Registries like PROFILES, that go beyond boundaries of disciplines and institutions, will contribute to better predictions of who will experience changes and why. This is needed to prevent and mitigate long-term and late effects of cancer (treatment) and to identify new interventions to promote health.

Nutritional Treatment in Crohn's Disease

Crohn's disease (CD) is a chronic inflammatory bowel disease (IBD) which can affect any part of the whole gastrointestinal tract (from mouth to anus). Malnutrition affects 65-75% of CD patients, and it is now well acknowledged that diet is of paramount importance in the management of the disease. In this review, we would like to highlight the most recent findings in the field of nutrition for the treatment of CD. Our analysis will cover a wide range of topics, from the well-established diets to the new nutritional theories, along with the recent progress in emerging research fields, such as nutrigenomics.

A Systematic Framework for Collecting Site-Specific Sampling and Survey Data to Support Analyses of Health Impacts from Land-Based Pollution in Low- and Middle-Income Countries

The rise of small-scale and localized economic activities in low- and middle-income countries (LMICs) has led to increased exposures to contaminants associated with these processes and the potential for resulting adverse health effects in exposed communities. Risk assessment is the process of building models to predict the probability of adverse outcomes based on concentration-response functions and exposure scenarios for individual contaminants, while epidemiology uses statistical methods to explore associations between potential exposures and observed health outcomes. Neither approach by itself is practical or sufficient for evaluating the magnitude of exposures and health impacts associated with land-based pollution in LMICs. Here we propose a more pragmatic framework for designing representative studies, including uniform sampling guidelines and household surveys, that draws from both methodologies to better support community health impact analyses associated with land-based pollution sources in LMICs. Our primary goal is to explicitly link environmental contamination from land-based pollution associated with specific localized economic activities to community exposures and health outcomes at the household level. The proposed framework was applied to the following three types of industries that are now widespread in many LMICs: artisanal scale gold mining (ASGM), used lead-acid battery recycling (ULAB), and small tanning facilities. For each activity, we develop a generalized conceptual site model (CSM) that describes qualitative linkages from chemical releases or discharges, environmental fate and transport mechanisms, exposure pathways and routes, populations at risk, and health outcomes. This upfront information, which is often overlooked, is essential for delineating the contaminant zone of influence in a community and identifying relevant households for study. We also recommend cost-effective methods for use in LMICs related to environmental sampling, biological monitoring, survey questionnaires, and health outcome measurements at contaminated and unexposed reference sites. Future study designs based on this framework will facilitate consistent, comparable, and standardized community exposure, risk, and health impact assessments for land-based pollution in LMICs. The results of these studies can also support economic burden analyses and risk management decision-making around site cleanup, risk mitigation, and public health education.

Metabolomics data complemented drug use information in epidemiological databases: pilot study of potential kidney donors

OBJECTIVE

The objective of this study was to investigate whether clinical metabolomics, which is increasingly applied in population-based and epidemiological studies, can be used to provide analytical evidence of exposures, and whether such information can be useful to strengthen and/or complement corresponding clinical database entries, taking drug use as an example.

STUDY DESIGN AND SETTING

Liquid chromatography-mass spectrometry (LC-MS) metabolomics analyses were performed on urine from 100 randomly-selected control subjects (50% females) from the TransplantLines Food and Nutrition Biobank and Cohort Study (NCT identifier 'NCT02811835'), and drugs were identified through spectral library searching and targeted signal extraction.

RESULTS

In 83 subjects for whom drug use information was available, 22 expected and 26 unexpected prescription-only drugs were identified, while 28 expected prescription-only drugs remained undetected. In addition, 7 prescription-only drugs were found in 17 subjects for whom drug use information was unavailable, and 58 over-the-counter drugs were identified in all 100 subjects.

CONCLUSION

Molecular evidence for many drugs could be retrieved from LC-MS metabolomics data, which could be useful to complement and strengthen epidemiological databases given that considerable discrepancies were found between analytically-identified drugs and drugs listed in the available clinical database.

Differential Lipidomic Characteristics of Children Born to Women with Polycystic Ovary Syndrome

OBJECTIVE

To describe the lipidomic characteristics of offspring born to polycystic ovary syndrome (PCOS) women (PCOS-off) and assess the associations between differential lipids and clinical phenotypes.

METHODS

Ultra performance liquid chromatography and mass spectrometry were performed on plasma samples from 70 PCOS-off and 71 healthy controls. The associations of differential metabolites with clinical phenotypes were examined by multiple linear regression.

RESULTS

Forty-four metabolites were significantly altered in PCOS-off, including 8 increased and 36 decreased. After stratification according to sex, 44 metabolites (13 increased and 31 decreased) were expressed differently in girls born to PCOS women (PCOS-g), most of which were glycerolipids. Furthermore, 46 metabolites (9 increased and 35 decreased) were expressed differently in boys born to PCOS women (PCOS-b), most of which were glycerophospholipids. Significant associations of metabolites with weight Z-score and high density lipoprotein cholesterol were found in PCOS-off. Triglycerides, low density lipoprotein cholesterol, and thyroid-stimulating hormone were separately correlated with some lipids in PCOS-g and PCOS-b.

CONCLUSIONS

PCOS-off showed specific lipid profile alterations. The abnormal level of glycerophospholipids and sphingomyelin indicated the risk of glucose metabolism and cardiovascular diseases in PCOS-off. Some lipids, such as phosphatidylcholines, lysophosphatidylcholine and sphingomyelin, may be the potential markers. The results broadened our understanding of PCOS-offs' cardiometabolic status and emphasized more specific and detailed monitoring and management in this population.

Personalized Nutrition and -Omics

With change in global concern toward food quality over food quantity, consumer concern and choice of healthy food has become a matter of prime importance. It gave rise to concept of “personalized or precision nutrition”. The theory behind personalization of nutrition is supported by multiple factors including advances in food analytics, nutrition based diseases and public health programs, increasing use of information technology in nutrition science, concept of gene-diet interaction and growing consumer capacity or concern by better and healthy foods. The advances in “omics” tools and related analytical techniques have resulted into tremendous scope of their application in nutrition science. As a consequence, a better understanding of underlying interaction between diet and individual is expected with addressing of key challenges for successful implementation of this science. In this chapter, the above aspects are discussed to get an insight into driving factors for increasing concern in personalized nutrition.

Genes and environments, development and time

A now substantial body of science implicates a dynamic interplay between genetic and environmental variation in the development of individual differences in behavior and health. Such outcomes are affected by molecular, often epigenetic, processes involving gene-environment (G-E) interplay that can influence gene expression. Early environments with exposures to poverty, chronic adversities, and acutely stressful events have been linked to maladaptive development and compromised health and behavior. Genetic differences can impart either enhanced or blunted susceptibility to the effects of such pathogenic environments. However, largely missing from present discourse regarding G-E interplay is the role of time, a "third factor" guiding the emergence of complex developmental endpoints across different scales of time. Trajectories of development increasingly appear best accounted for by a complex, dynamic interchange among the highly linked elements of genes, contexts, and time at multiple scales, including neurobiological (minutes to milliseconds), genomic (hours to minutes), developmental (years and months), and evolutionary (centuries and millennia) time. This special issue of PNAS thus explores time and timing among G-E transactions: The importance of timing and timescales in plasticity and critical periods of brain development; epigenetics and the molecular underpinnings of biologically embedded experience; the encoding of experience across time and biological levels of organization; and gene-regulatory networks in behavior and development and their linkages to neuronal networks. Taken together, the collection of papers offers perspectives on how G-E interplay operates contingently within and against a backdrop of time and timescales.

Citizens' Attitudes, Knowledge, and Educational Needs in the Field of Omics Sciences: A Systematic Literature Review

Background: The huge development of omics sciences is changing the classical medical approach and making new technologies available. In this context, education of citizens is essential to allow appropriate decisions about their own health. Hence, we aimed to summarize existing literature regarding citizens' knowledge, attitudes, and educational needs on omics sciences. Methods: We performed a systematic literature review (SLR) using Pubmed, ISI Web of Science, and Embase databases. The eligibility criteria for inclusion in this review required that the studies investigated knowledge, attitudes, or educational needs regarding omics sciences among the general population. Results: We included 54 studies, published between 2006 and 2020. Most of the included studies (72%) investigated citizens' knowledge, half of them (56%) attitudes, and 20% educational needs in the field of omics sciences, while 52% investigated attitudes and perceptions about genetic and/or omics tests. Most studies (64%) reported a limited knowledge level among citizens, even though most (59%) reported participants understood the benefits of the use of omics sciences into medicine. As for omics tests, a controversial opinion toward their use into practice was reported among citizens. Most of the studies (82%) investigating citizens' educational needs highlighted a clear gap to be filled. Conclusions: Our SLR summarizes current knowledge on citizens' literacy, attitudes, and educational needs on omics science, underlining the need for strengthening public engagement on this topic. Further research is needed, however, to identify appropriate methods and models to achieve such an improvement.

Genetic drivers of cerebral blood flow dysfunction in TBI: a speculative synthesis

Cerebral autoregulatory dysfunction after traumatic brain injury (TBI) is strongly linked to poor global outcome in patients at 6 months after injury. However, our understanding of the drivers of this dysfunction is limited. Genetic variation among individuals within a population gives rise to single-nucleotide polymorphisms (SNPs) that have the potential to influence a given patient's cerebrovascular response to an injury. Associations have been reported between a variety of genetic polymorphisms and global outcome in patients with TBI, but few studies have explored the association between genetic variants and cerebrovascular function after injury. In this Review, we explore polymorphisms that might play an important part in cerebral autoregulatory capacity after TBI. We outline a variety of SNPs, their biological substrates and their potential role in mediating cerebrovascular reactivity. A number of candidate polymorphisms exist in genes that are involved in myogenic, endothelial, metabolic and neurogenic vascular responses to injury. Furthermore, polymorphisms in genes involved in inflammation, the central autonomic response and cortical spreading depression might drive cerebrovascular reactivity. Identification of candidate genes involved in cerebral autoregulation after TBI provides a platform and rationale for further prospective investigation of the link between genetic polymorphisms and autoregulatory function.

Using phenome-wide association studies to examine the effect of environmental exposures on human health

The field of environmental epidemiology has been using "-omics" technologies, including the exposome, metabolome, and methylome, to understand the potential effects and biological pathways of a number of environmental pollutants. However, the majority of studies have focused on a single disease or phenotype, and have not systematically considered patterns of multimorbidity and whether environmental pollutants have pleiotropic effects. These questions could be addressed by examining the relation between environmental exposures and the phenome - the patterns and profiles of human health that individuals experience from birth to death. By conducting Phenome Wide Association Studies (PheWAS), we can generate new hypotheses about new or poorly understood exposures, identify novel associations for established toxicants, and better understand biological pathways affected by environmental pollutants. In this article, we provide a conceptual framework for conducting PheWAS in environmental epidemiology and summarize some of the advantages and challenges to using the PheWAS to study environmental pollutant exposures. Ultimately, by adding the PheWAS to our "-omics" toolbox, we could substantially improve our understanding of the potential health effects of environmental pollutants.

Genetic Influences on Patient-Oriented Outcomes in Traumatic Brain Injury: A Living Systematic Review of Non-Apolipoprotein E Single-Nucleotide Polymorphisms

There is a growing literature on the impact of genetic variation on outcome in traumatic brain injury (TBI). Whereas a substantial proportion of these publications have focused on the apolipoprotein E (APOE) gene, several have explored the influence of other polymorphisms. We undertook a systematic review of the impact of single-nucleotide polymorphisms (SNPs) in non–apolipoprotein E (non-APOE) genes associated with patient outcomes in adult TBI). We searched EMBASE, MEDLINE, CINAHL, and gray literature from inception to the beginning of August 2017 for studies of genetic variance in relation to patient outcomes in adult TBI. Sixty-eight articles were deemed eligible for inclusion into the systematic review. The SNPs described were in the following categories: neurotransmitter (NT) in 23, cytokine in nine, brain-derived neurotrophic factor (BDNF) in 12, mitochondrial genes in three, and miscellaneous SNPs in 21. All studies were based on small patient cohorts and suffered from potential bias. A range of SNPs associated with genes coding for monoamine NTs, BDNF, cytokines, and mitochondrial proteins have been reported to be associated with variation in global, neuropsychiatric, and behavioral outcomes. An analysis of the tissue, cellular, and subcellular location of the genes that harbored the SNPs studied showed that they could be clustered into blood–brain barrier associated, neuroprotective/regulatory, and neuropsychiatric/degenerative groups. Several small studies report that various NT, cytokine, and BDNF-related SNPs are associated with variations in global outcome at 6–12 months post-TBI. The association of these SNPs with neuropsychiatric and behavioral outcomes is less clear. A definitive assessment of role and effect size of genetic variation in these genes on outcome remains uncertain, but could be clarified by an adequately powered genome-wide association study with appropriate recording of outcomes.

Proteome and transcriptome analyses reveal key molecular differences between quality parameters of commercial-ripe and tree-ripe fig (Ficus carica L.)

BACKGROUND

Fig fruit are highly perishable at the tree-ripe (TR) stage. Commercial-ripe (CR) fruit, which are harvested before the TR stage for their postharvest transportability and shelf-life advantage, are inferior to TR fruit in size, color and sugar content. The succulent urn-shaped receptacle, serving as the protective structure and edible part of the fruit, determines fruit quality. Quantitative iTRAQ and RNA-Seq were performed to reveal the differential proteomic and transcriptomic traits of the receptacle at the two harvest stages.

RESULTS

We identified 1226 proteins, of which 84 differentially abundant proteins (DAPs) were recruited by criteria of abundance fold-change (FC) ≥1.3 and p < 0.05 in the TR/CR receptacle proteomic analysis. In addition, 2087 differentially expressed genes (DEGs) were screened by ≥2-fold expression change: 1274 were upregulated and 813 were downregulated in the TR vs. CR transcriptomic analysis. Ficin was the most abundant soluble protein in the fig receptacle. Sucrose synthase, sucrose-phosphate synthase and hexokinase were all actively upregulated at both the protein and transcriptional levels. Endoglucanase, expansin, beta-galactosidase, pectin esterase and aquaporins were upregulated from the CR to TR stage at the protein level. In hormonal synthesis and signaling pathways, high protein and transcriptional levels of aminocyclopropane-1-carboxylate oxidase were identified, together with a few diversely expressed ethylene-response factors, indicating the potential leading role of ethylene in the ripening process of fig receptacle, which has been recently reported as a non-climacteric tissue.

CONCLUSIONS

We present the first delineation of intra- and inter-omic changes in the expression of specific proteins and genes of TR vs. CR fig receptacle, providing valuable candidates for further study of fruit-quality formation control and fig cultivar innovation to accommodate market demand.

KUNO-Kids birth cohort study: rationale, design, and cohort description

Background

Birth cohort studies can contribute substantially to the understanding of health and disease — in childhood and over the life course. The KUNO-Kids birth cohort study was established to investigate various aspects of child health, using novel omics technologies in a systems medicine approach.

Results

After 3 years of recruitment, 2515 infants and their families have joined the study. Parents with higher education are overrepresented as in many other birth cohorts and are more likely to complete follow-up assessments via self-report questionnaires. The vast majority of participants consented to clinical examinations of their child and to the non-invasive collection of diverse biosamples, which were processed specifically for their integrated use in omics technology covering genomics, epigenomics, transcriptomics, metabolomics, and microbiome analyses of the skin, oral cavity, and stool.

Conclusions

The data and diverse biomaterial collected in the KUNO-Kids birth cohort study will provide extensive opportunities for investigating child health and its determinants in a holistic approach. The combination of a broad range of research questions in one study will allow for a cost-effective use of biomaterial and omics results and for a comprehensive analysis of biological and social determinants of health and disease. Aiming for low attrition and ensuring participants’ long-term commitment will be crucial to fully exploit the potential of the study.

Advances in Understanding the Molecular Basis of the Mediterranean Diet Effect

Increasingly, studies showing the protective effects of the Mediterranean diet (MedDiet) on different diseases (cardiovascular, diabetes, some cancers, and even total mortality and aging indicators) are being published. The scientific evidence level for each outcome is variable, and new studies are needed to better understand the molecular mechanisms whereby the MedDiet may exercise its effects. Here, we present recent advances in understanding the molecular basis of MedDiet effects, mainly focusing on cardiovascular diseases but also discussing other related diseases. There is heterogeneity in defining the MedDiet, and it can, owing to its complexity, be considered as an exposome with thousands of nutrients and phytochemicals. We review MedDiet composition and assessment as well as the latest advances in the genomic, epigenomic (DNA methylation, histone modifications, microRNAs, and other emerging regulators), transcriptomic (selected genes and whole transcriptome), and metabolomic and metagenomic aspects of the MedDiet effects (as a whole and for its most typical food components). We also present a critical review of the limitations of the studies undertaken and propose new analyses and greater bioinformatic integration to better understand the most important molecular mechanisms whereby the MedDiet as a whole, or its main food components, may exercise their protective effects.

Invited review: Reproductive and genomic technologies to optimize breeding strategies for genetic progress in dairy cattle

Abstract. Dairy cattle breeders have exploited technological advances that have emerged in the past in regards to reproduction and genomics. The implementation of such technologies in routine breeding programs has permitted genetic gains in traditional milk production traits as well as, more recently, in low-heritability traits like health and fertility. As demand for dairy products increases, it is important for dairy breeders to optimize the use of available technologies and to consider the many emerging technologies that are currently being investigated in various fields. Here we review a number of technologies that have helped shape dairy breeding programs in the past and present, along with those potentially forthcoming. These tools have materialized in the areas of reproduction, genotyping and sequencing, genetic modification, and epigenetics. Although many of these technologies bring encouraging opportunities for genetic improvement of dairy cattle populations, their applications and benefits need to be weighed with their impacts on economics, genetic diversity, and society.

The Effects of Moderate Whole Grain Consumption on Fasting Glucose and Lipids, Gastrointestinal Symptoms, and Microbiota

This study was designed to determine if providing wheat, corn, and rice as whole (WG) or refined grains (RG) under free-living conditions will change parameters of health over a six-week intervention in healthy, habitual non-WG consumers. Measurements of body composition, fecal microbiota, fasting blood glucose, total cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL), and triglycerides were made at baseline and post intervention. Subjects were given adequate servings of either WG or RG products based on their caloric need and asked to keep records of grain consumption, bowel movements, and GI symptoms weekly. After six weeks, subjects repeated baseline testing. Significant decreases in total, LDL, and non-HDL cholesterol were seen after the WG treatments but were not observed in the RG treatment. During Week 6, bowel movement frequency increased with increased WG consumption. No significant differences in microbiota were seen between baseline and post intervention, although, abundance of order Erysipelotrichales increased in RG subjects who ate more than 50% of the RG market basket products. Increasing consumption of WGs can alter parameters of health, but more research is needed to better elucidate the relationship between the amount consumed and the health-related outcome.

Precision medicine in circadian rhythm sleep-wake disorders: current state and future perspectives

In circadian rhythm sleep-wake disorders precision medicine is less developed than in other medical disciplines mainly because homeostatic sleep and circadian timing have a very complex phenotype with multiple genetic regulation mechanisms. However, biomarkers, phenotyping and psychosocial characteristics are increasingly used. Devices for polysomnography, actigraphy and sleep-tracking applications in mobile phones and other consumer devices with eHealth technologies are increasingly used. Also sleep-related questionnaires and the assessment of co-morbidities influencing sleep in circadian rhythm sleep-wake disorders are major contributors to precision sleep medicine. To further strengthen the (pharmaco-)genetic and biomarker pillar, technology needs to be evolved further. Routinely measuring treatment results using patient-reported outcome measures and clinical neurophysiological instruments will boost precision sleep medicine.

Cord Blood Metabolome Is Highly Associated with Birth Weight, but Less Predictive for Later Weight Development

BACKGROUND/AIMS

Fetal metabolism may be changed by the exposure to maternal factors, and the route to obesity may already set in utero. Cord blood metabolites might predict growth patterns and later obesity. We aimed to characterize associations of cord blood with birth weight, postnatal weight gain, and BMI in adolescence.

METHODS

Over 700 cord blood samples were collected from infants participating in the German birth cohort study LISAplus. Glycerophospholipid fatty acids (GPL-FA), polar lipids, non-esterified fatty acids (NEFA), and amino acids were analyzed with a targeted, liquid chromatography-tandem mass spectrometry based metabolomics platform. Cord blood metabolites were related to growth factors by linear regression models adjusted for confounding variables.

RESULTS

Cord blood metabolites were highly associated with birth weight. Lysophosphatidylcholines C16:1, C18:1, C20:3, C18:2, C20:4, C14:0, C16:0, C18:3, GPL-FA C20:3n-9, and GPL-FA C22:5n-6 were positively related to birth weight, while higher cord blood concentrations of NEFA C22:6, NEFA C20:5, GPL-FA C18:3n-3, and PCe C38:0 were associated with lower birth weight. Postnatal weight gain and BMI z-scores in adolescents were not significantly associated with cord blood metabolites after adjustment for multiple testing.

CONCLUSION

Potential long-term programming effects of the intrauterine environment and metabolism on later health cannot be predicted with profiling of the cord blood metabolome.

Molecular mechanisms underlying COPD-muscle dysfunction unveiled through a systems medicine approach

MOTIVATION

Skeletal muscle dysfunction is a systemic effect in one-third of patients with chronic obstructive pulmonary disease (COPD), characterized by high reactive-oxygen-species (ROS) production and abnormal endurance training-induced adaptive changes. However, the role of ROS in COPD remains unclear, not least because of the lack of appropriate tools to study multifactorial diseases.

RESULTS

We describe a discrete model-driven method combining mechanistic and probabilistic approaches to decipher the role of ROS on the activity state of skeletal muscle regulatory network, assessed before and after an 8-week endurance training program in COPD patients and healthy subjects. In COPD, our computational analysis indicates abnormal training-induced regulatory responses leading to defective tissue remodeling and abnormal energy metabolism. Moreover, we identified tnf, insr, inha and myc as key regulators of abnormal training-induced adaptations in COPD. The tnf-insr pair was identified as a promising target for therapeutic interventions. Our work sheds new light on skeletal muscle dysfunction in COPD, opening new avenues for cost-effective therapies. It overcomes limitations of previous computational approaches showing high potential for the study of other multi-factorial diseases such as diabetes or cancer.

CONTACT

jroca@clinic.ub.es or martacascante@ub.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Advances in Integrating Traditional and Omic Biomarkers When Analyzing the Effects of the Mediterranean Diet Intervention in Cardiovascular Prevention

Intervention with Mediterranean diet (MedDiet) has provided a high level of evidence in primary prevention of cardiovascular events. Besides enhancing protection from classical risk factors, an improvement has also been described in a number of non-classical ones. Benefits have been reported on biomarkers of oxidation, inflammation, cellular adhesion, adipokine production, and pro-thrombotic state. Although the benefits of the MedDiet have been attributed to its richness in antioxidants, the mechanisms by which it exercises its beneficial effects are not well known. It is thought that the integration of omics including genomics, transcriptomics, epigenomics, and metabolomics, into studies analyzing nutrition and cardiovascular diseases will provide new clues regarding these mechanisms. However, omics integration is still in its infancy. Currently, some single-omics analyses have provided valuable data, mostly in the field of genomics. Thus, several gene-diet interactions in determining both intermediate (plasma lipids, etc.) and final cardiovascular phenotypes (stroke, myocardial infarction, etc.) have been reported. However, few studies have analyzed changes in gene expression and, moreover very few have focused on epigenomic or metabolomic biomarkers related to the MedDiet. Nevertheless, these preliminary results can help to better understand the inter-individual differences in cardiovascular risk and dietary response for further applications in personalized nutrition.

Proposals for enhanced health risk assessment and stratification in an integrated care scenario

OBJECTIVES

Population-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario.

SETTINGS

The five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL).

PARTICIPANTS

Responsible teams for regional data management in the five ACT regions.

PRIMARY AND SECONDARY OUTCOME MEASURES

We characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction.

RESULTS

There was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment.

CONCLUSIONS

The results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation.

Tyrosine Is Associated with Insulin Resistance in Longitudinal Metabolomic Profiling of Obese Children

In obese children, hyperinsulinaemia induces adverse metabolic consequences related to the risk of cardiovascular and other disorders. Branched-chain amino acids (BCAA) and acylcarnitines (Carn), involved in amino acid (AA) degradation, were linked to obesity-associated insulin resistance, but these associations yet have not been studied longitudinally in obese children. We studied 80 obese children before and after a one-year lifestyle intervention programme inducing substantial weight loss >0.5 BMI standard deviation scores in 40 children and no weight loss in another 40 children. At baseline and after the 1-year intervention, we assessed insulin resistance (HOMA index), fasting glucose, HbA1c, 2 h glucose in an oral glucose tolerance test, AA, and Carn. BMI adjusted metabolite levels were associated with clinical markers at baseline and after intervention, and changes with the intervention period were evaluated. Only tyrosine was significantly associated with HOMA (p < 0.05) at baseline and end and with change during the intervention (p < 0.05). In contrast, ratios depicting BCAA metabolism were negatively associated with HOMA at baseline (p < 0.05), but not in the longitudinal profiling. Stratified analysis revealed that the children with substantial weight loss drove this association. We conclude that tyrosine alterations in association with insulin resistance precede alteration in BCAA metabolism. This trial is registered with ClinicalTrials.gov Identifier NCT00435734.

From Systems Understanding to Personalized Medicine: Lessons and Recommendations Based on a Multidisciplinary and Translational Analysis of COPD

Systems medicine, using and adapting methods and approaches as developed within systems biology, promises to be essential in ongoing efforts of realizing and implementing personalized medicine in clinical practice and research. Here we review and critically assess these opportunities and challenges using our work on COPD as a case study. We find that there are significant unresolved biomedical challenges in how to unravel complex multifactorial components in disease initiation and progression producing different clinical phenotypes. Yet, while such a systems understanding of COPD is necessary, there are other auxiliary challenges that need to be addressed in concert with a systems analysis of COPD. These include information and communication technology (ICT)-related issues such as data harmonization, systematic handling of knowledge, computational modeling, and importantly their translation and support of clinical practice. For example, clinical decision-support systems need a seamless integration with new models and knowledge as systems analysis of COPD continues to develop. Our experience with clinical implementation of systems medicine targeting COPD highlights the need for a change of management including design of appropriate business models and adoption of ICT providing and supporting organizational interoperability among professional teams across healthcare tiers, working around the patient. In conclusion, in our hands the scope and efforts of systems medicine need to concurrently consider these aspects of clinical implementation, which inherently drives the selection of the most relevant and urgent issues and methods that need further development in a systems analysis of disease.

Planning for the Future of Epidemiology in the Era of Big Data and Precision Medicine

We live in the era of genomics and big data. Evaluating the impact on health of large-scale biological, social, and environmental data is an emerging challenge in the field of epidemiology. In the past 3 years, major discussions and plans for the future of epidemiology, including with several recommendations for actions to transform the field, have been launched by 2 institutes within the National Institutes of Health. In the present commentary, I briefly explore the themes of these recommendations and their effects on leadership, resources, cohort infrastructure, and training. Ongoing engagement within the epidemiology community is needed to determine how to shape the evolution of the field and what truly matters for changing population health. We also need to assess how to leverage existing epidemiology resources and develop new studies to improve human health. Readers are invited to examine these recommendations, consider others that might be important, and join in the conversation about the future of epidemiology.

Predicting Later Study Withdrawal in Participants Active in a Longitudinal Birth Cohort Study for 1 Year: The TEDDY Study

OBJECTIVE

To identify predictors of later study withdrawal among participants active in The Environmental Determinants of Diabetes in the Young (TEDDY) for 1 year. 

METHODS

Multiple logistic regression was used to discriminate 3,042 children active in TEDDY for the first 3 years from 432 children who withdrew in Years 2 or 3. Predictor variables were tested in blocks-demographic, maternal lifestyle behaviors, stress and child illness, maternal reactions to child's increased diabetes risk, in-study behaviors-and a final best model developed. 

RESULTS

Few demographic factors predicted study withdrawal. Maternal lifestyle behaviors, accuracy of the mother's risk perception, and in-study behaviors were more important. Frequent child illnesses were associated with greater study retention. 

CONCLUSIONS

Demographic measures are insufficient predictors of later study withdrawal among those active in a study for at least 1 year; behavioral/psychological factors offer improved prediction and guidance for the development of retention strategies.

Systematic synergy modeling: understanding drug synergy from a systems biology perspective

Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose–response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and “omic”-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations.

Nutritional Modulation of Gene Expression: Might This be of Benefit to Individuals with Crohn's Disease?

The incidence of inflammatory bowel diseases (IBD), including Crohn's disease (CD), is increasing worldwide, especially in young children and adolescents. Although hospitalized patients are usually provided with enteral or parenteral support, continuing care typically requires a trial-and-error approach to suppressing symptoms and maintaining disease remission. Current nutritional advice does not differ from general population guidelines. International collaborative studies have revealed 163 distinct genetic loci affecting susceptibility to IBD, in some of which host-microbe interactions can be seen to play an important role. The nature of these loci enables a rationale for predicting nutritional requirements that may not be evident through standard therapeutic approaches. Certain recognized nutrients, such as vitamin D and long-chain omega-3 polyunsaturated fatty acids, may be required at higher than anticipated levels. Various phytochemicals, not usually considered in the same class as classic nutrients, could play an important role. Prebiotics and probiotics may also be beneficial. Genomic approaches enable proof of principle of nutrient optimization rather than waiting for disease symptoms to appear and/or progress. We suggest a paradigm shift in diagnostic tools and nutritional therapy for CD, involving a systems biology approach for implementation.

What matters most: quantifying an epidemiology of consequence

Risk factor epidemiology has contributed to substantial public health success. In this essay, we argue, however, that the focus on risk factor epidemiology has led epidemiology to ever increasing focus on the estimation of precise causal effects of exposures on an outcome at the expense of engagement with the broader causal architecture that produces population health. To conduct an epidemiology of consequence, a systematic effort is needed to engage our science in a critical reflection both about how well and under what conditions or assumptions we can assess causal effects and also on what will truly matter most for changing population health. Such an approach changes the priorities and values of the discipline and requires reorientation of how we structure the questions we ask and the methods we use, as well as how we teach epidemiology to our emerging scholars.