Vibrational Spectroscopic Map, Vibrational Spectroscopy, and Intermolecular Interaction

© 2020 American Chemical Society. Vibrational spectroscopy is an essential tool in chemical analyses, biological assays, and studies of functional materials. Over the past decade, various coherent nonlinear vibrational spectroscopic techniques have been developed and enabled researchers to study time-correlations of the fluctuating frequencies that are directly related to solute-solvent dynamics, dynamical changes in molecular conformations and local electrostatic environments, chemical and biochemical reactions, protein structural dynamics and functions, characteristic processes of functional materials, and so on. In order to gain incisive and quantitative information on the local electrostatic environment, molecular conformation, protein structure and interprotein contacts, ligand binding kinetics, and electric and optical properties of functional materials, a variety of vibrational probes have been developed and site-specifically incorporated into molecular, biological, and material systems for time-resolved vibrational spectroscopic investigation. However, still, an all-encompassing theory that describes the vibrational solvatochromism, electrochromism, and dynamic fluctuation of vibrational frequencies has not been completely established mainly due to the intrinsic complexity of intermolecular interactions in condensed phases. In particular, the amount of data obtained from the linear and nonlinear vibrational spectroscopic experiments has been rapidly increasing, but the lack of a quantitative method to interpret these measurements has been one major obstacle in broadening the applications of these methods. Among various theoretical models, one of the most successful approaches is a semiempirical model generally referred to as the vibrational spectroscopic map that is based on a rigorous theory of intermolecular interactions. Recently, genetic algorithm, neural network, and machine learning approaches have been applied to the development of vibrational solvatochromism theory. In this review, we provide comprehensive descriptions of the theoretical foundation and various examples showing its extraordinary successes in the interpretations of experimental observations. In addition, a brief introduction to a newly created repository Web site (http://frequencymap.org) for vibrational spectroscopic maps is presented. We anticipate that a combination of the vibrational frequency map approach and state-of-the-art multidimensional vibrational spectroscopy will be one of the most fruitful ways to study the structure and dynamics of chemical, biological, and functional molecular systems in the future

Epigenome-wide meta-analysis of blood DNA methylation in newborns and children identifies numerous loci related to gestational age

Background Preterm birth and shorter duration of pregnancy are associated with increased morbidity in neonatal and later life. As the epigenome is known to have an important role during fetal development, we investigated associations between gestational age and blood DNA methylation in children. Methods We performed meta-analysis of Illumina's HumanMethylation450-array associations between gestational age and cord blood DNA methylation in 3648 newborns from 17 cohorts without common pregnancy complications, induced delivery or caesarean section. We also explored associations of gestational age with DNA methylation measured at 4-18 years in additional pediatric cohorts. Follow-up analyses of DNA methylation and gene expression correlations were performed in cord blood. DNA methylation profiles were also explored in tissues relevant for gestational age health effects: fetal brain and lung. Results We identified 8899 CpGs in cord blood that were associated with gestational age (range 27-42 weeks), at Bonferroni significance, P <1.06 x 10(- 7), of which 3343 were novel. These were annotated to 4966 genes. After restricting findings to at least three significant adjacent CpGs, we identified 1276 CpGs annotated to 325 genes. Results were generally consistent when analyses were restricted to term births. Cord blood findings tended not to persist into childhood and adolescence. Pathway analyses identified enrichment for biological processes critical to embryonic development. Follow-up of identified genes showed correlations between gestational age and DNA methylation levels in fetal brain and lung tissue, as well as correlation with expression levels. Conclusions We identified numerous CpGs differentially methylated in relation to gestational age at birth that appear to reflect fetal developmental processes across tissues. These findings may contribute to understanding mechanisms linking gestational age to health effects.Peer reviewe

Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude

This is the final version. Available from BMC via the DOI in this record. Individual cohort-level data can be obtained from the respective cohort (see Additional file 1: Table S1 and Additional file 2 for cohort details).BACKGROUND: Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear. METHODS: We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1-11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points. RESULTS: We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values < 0.05) at two CpGs at birth (winter-born) and four in the childhood (summer-born) analyses when compared to children born in autumn. Furthermore, we identified twenty-six differentially methylated regions (DMR) at birth (winter-born: 8, spring-born: 15, summer-born: 3) and thirty-two in childhood (winter-born: 12, spring and summer: 10 each) meta-analyses with few overlapping DMRs between the birth seasons or the two time points. The DMRs were associated with genes of known functions in tumorigenesis, psychiatric/neurological disorders, inflammation, or immunity, amongst others. Latitude-stratified meta-analyses [higher (≥ 50°N), lower (< 50°N, northern hemisphere only)] revealed differences in associations between birth season and DNAm by birth latitude. DMR analysis implicated genes with previously reported links to schizophrenia (LAX1), skin disorders (PSORS1C, LTB4R), and airway inflammation including asthma (LTB4R), present only at birth in the higher latitudes (≥ 50°N). CONCLUSIONS: In this large epigenome-wide meta-analysis study, we provide evidence for (i) associations between DNAm and season of birth that are unique for the seasons of the year (temporal effect) and (ii) latitude-dependent variations in the seasonal associations (spatial effect). DNAm could play a role in the molecular mechanisms underlying the effect of birth season on adult health outcomes.Wellcome TrustBiotechnology and Biological Sciences Research Council (BBSRC)Biotechnology and Biological Sciences Research Council (BBSRC)European Union’s Horizon 2020Economic and Social Research Council (ESRC)Medical Research Council (MRC)Medical Research Council (MRC)European UnionSwedish foundation for strategic research (SSF)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)Environmental Protection Agency (EPA)National Cancer Institute Cancer CenterNational Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)Environmental Protection Agency (EPA)Environmental Protection Agency (EPA)European UnionEuropean UnionEuropean UnionEuropean UnionEuropean Union’s Horizon 2020European Research Council (ERC)German Ministry of Education and ResearchNational Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)Autism SpeaksNational Institutes of Health (NIH)National Institutes of Health (NIH)European UnionEuropean UnionEuropean UnionEuropean UnionEuropean UnionEuropean UnionEuropean UnionEuropean UnionEuropean UnionEuropean Research Council (ERC)Flemisch Scientific Research CouncilFlemisch Scientific Research CouncilFlemisch Scientific Research CouncilEuropean UnionFonds de recherche du Québec - Santé (FRQS)Canadian Institute of Health Research (CIHR)Canadian Institute of Health Research (CIHR)Netherlands Organisation for Scientific Research (NWO)National Institute of Child and Human DevelopmentEuropean Union’s Horizon 2020European Union’s Horizon 2020European Union’s Horizon 2020ZonMwZonMwMedical Research Council Integrative Epidemiology Unit (University of Bristol)Netherlands Heart FoundationNetherlands Heart FoundationNetherlands Organisation for Scientific Research (NWO)European UnionNational Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)Spanish Ministry of ScienceNational Institute for Health and Care Research (NIHR)Wellcome TrustNorwegian Ministry of Health and the Ministry of Education and ResearchNorwegian Ministry of Health and the Ministry of Education and ResearchNorwegian Ministry of Health and the Ministry of Education and ResearchLithuanian Agency for Science Innovation and TechnologySpanish Ministry of HealthSpanish Ministry of HealthSpanish Ministry of HealthSpanish Ministry of HealthSpanish Ministry of HealthInstituto de Salud Carlos IIIInstituto de Salud Carlos IIIEuropean Research Council (ERC)CDMRP/Department of DefenseNIGMSNational Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Asthma Campaign, UKNational Institutes of Health (NIH)Medical Research Council (MRC)National Institutes of Health (NIH)Norwegian Research CouncilNational Institute of Environmental Health SciencesResearch Council of NorwayNational Institute of Environmental Health SciencesNational Institute of Environmental Health SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Environmental Health SciencesNational Institute of Environmental Health SciencesSwedish Research CouncilSwedish Initiative for research on Microdata in the Social And Medical Sciences (SIMSAM)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)National Institutes of Health (NIH)Medical Research Council Integrative Epidemiology Unit (University of Bristol)Medical Research Council Integrative Epidemiology Unit (University of Bristol)Medical Research Council Integrative Epidemiology Unit (University of Bristol)Swedish Heart-Lung FoundationUniversity of MunichFoundation for Medical Research (FRM)National Agency for ResearchNational Institute for Research in Public HealthFrench Ministry of HealthFrench Ministry of ResearchInserm Bone and Joint Diseases National Research (PRO-A) and Human Nutrition National Research ProgramsParis–Sud UniversityNestléFrench National Institute for Population Health SurveillanceFrench National Institute for Health EducationFrench Agency for Environmental Health SafetyMutuelle Générale de l’Education NationaleFrench National Agency for Food SecurityFrench-speaking association for the study of diabetes and metabolismItalian National Centre for Disease Prevention and ControlItalian Ministry of HealthGreek Ministry of HealthFlemish Government (Department of Economy, Science and Innovations, Agency for Care and Health and Department of Environment)The Research Foundation-FlandersFlemish Institute for Technological ResearchDiabète QuébecErasmus University RotterdamNetherlands Organization for Health Research and Development and the Ministry of Health, Welfare and SportErasmus MCDanish National Research FoundationDanish Regional CommitteesNovo Nordisk FoundationLundbeck FoundationHelmholtz Center for Environmental ResearchGerman Cancer Research CentreAcademy of FinlandEraNetEVOUniversity of Helsinki Research FundsSigne and Ane Gyllenberg foundationEmil Aaltonen FoundationFinnish Medical FoundationJane and Aatos Erkko FoundationJuho Vainio foundationYrjö Jahnsson foundationJalmari and Rauha Ahokas foundationPaivikki and Sakari Sohlberg FoundationSigrid Juselius FoundationSir Jules Thorn Charitable TrustSwedish Asthma and Allergy Association's Research FoundationStiftelsen Frimurare Barnhuset Stockhol

Epigenome-wide meta-analysis of blood DNA methylation in newborns and children identifies numerous loci related to gestational age

Background Preterm birth and shorter duration of pregnancy are associated with increased morbidity in neonatal and later life. As the epigenome is known to have an important role during fetal development, we investigated associations between gestational age and blood DNA methylation in children. Methods We performed meta-analysis of Illumina's HumanMethylation450-array associations between gestational age and cord blood DNA methylation in 3648 newborns from 17 cohorts without common pregnancy complications, induced delivery or caesarean section. We also explored associations of gestational age with DNA methylation measured at 4-18 years in additional pediatric cohorts. Follow-up analyses of DNA methylation and gene expression correlations were performed in cord blood. DNA methylation profiles were also explored in tissues relevant for gestational age health effects: fetal brain and lung. Results We identified 8899 CpGs in cord blood that were associated with gestational age (range 27-42 weeks), at Bonferroni significance, P < 1.06 x 10(- 7), of which 3343 were novel. These were annotated to 4966 genes. After restricting findings to at least three significant adjacent CpGs, we identified 1276 CpGs annotated to 325 genes. Results were generally consistent when analyses were restricted to term births. Cord blood findings tended not to persist into childhood and adolescence. Pathway analyses identified enrichment for biological processes critical to embryonic development. Follow-up of identified genes showed correlations between gestational age and DNA methylation levels in fetal brain and lung tissue, as well as correlation with expression levels. Conclusions We identified numerous CpGs differentially methylated in relation to gestational age at birth that appear to reflect fetal developmental processes across tissues. These findings may contribute to understanding mechanisms linking gestational age to health effects