Links between melanoma germline risk loci, driver genes and comorbidities: insight from a tissue-specific multi-omic analysis.

Genome-wide association studies (GWAS) have associated 76 loci with the risk of developing melanoma. However, understanding the molecular basis of such associations has remained a challenge because most of these loci are in non-coding regions of the genome. Here, we integrated data on epigenomic markers, three-dimensional (3D) genome organization, and expression quantitative trait loci (eQTL) from melanoma-relevant tissues and cell types to gain novel insights into the mechanisms underlying melanoma risk. This integrative approach revealed a total of 151 target genes, both near and far away from the risk loci in linear sequence, with known and novel roles in the etiology of melanoma. Using protein-protein interaction networks, we identified proteins that interact-directly or indirectly-with the products of the target genes. The interacting proteins were enriched for known melanoma driver genes. Further integration of these target genes into tissue-specific gene regulatory networks revealed patterns of gene regulation that connect melanoma to its comorbidities. Our study provides novel insights into the biological implications of genetic variants associated with melanoma risk.

Identification of 27 allele-specific regulatory variants in Parkinson's disease using a massively parallel reporter assay.

Genome wide association studies (GWAS) have identified a number of genomic loci that are associated with Parkinson's disease (PD) risk. However, the majority of these variants lie in non-coding regions, and thus the mechanisms by which they influence disease development, and/or potential subtypes, remain largely elusive. To address this, we used a massively parallel reporter assay (MPRA) to screen the regulatory function of 5254 variants that have a known or putative connection to PD. We identified 138 loci with enhancer activity, of which 27 exhibited allele-specific regulatory activity in HEK293 cells. The identified regulatory variant(s) typically did not match the original tag variant within the PD associated locus, supporting the need for deeper exploration of these loci. The existence of allele specific transcriptional impacts within HEK293 cells, confirms that at least a subset of the PD associated regions mark functional gene regulatory elements. Future functional studies that confirm the putative targets of the empirically verified regulatory variants will be crucial for gaining a greater understanding of how gene regulatory network(s) modulate PD risk.

Resting EEG correlates of neurodevelopment in a socioeconomically and linguistically diverse sample of toddlers: Wave 1 of the Kia Timata Pai best start New Zealand study.

Development of communication and self-regulation skills is fundamental to psychosocial maturation in childhood. The Kia Timata Pai Best Start (KTP) longitudinal study aims to promote these skills through interventions delivered at early childcare centers across New Zealand. In addition to evaluating effects of the interventions on behavioral and cognitive outcomes, the study utilizes electroencephalography (EEG) to characterize cortical development in a subsample of participating children. Here, we present results of the baseline resting EEG assessment with 193 children aged 15 to 33 months. We identified EEG correlates of individual differences in demographics, communication abilities, and temperament. We obtained communication and behavior ratings from multiple informants, and we applied contemporary analytic methods to the EEG data. Periodic spectral power adjusted for aperiodic activity was most closely associated with demographic, language, and behavioral measures. As in previous studies, gamma power was positively associated with verbal language. Alpha power was positively associated with effortful control. Nonverbal and verbal language measures showed distinct associations with EEG indices, as did the three temperament domains. Our results identified a number of candidate EEG measurements for use as longitudinal markers of optimal cortical development and response to interventions in the KTP cohort.

Spatially constrained gene regulation identifies key genetic contributions of preeclampsia, hypertension, and proteinuria†.

Preeclampsia (PE) is a relatively common but severe pregnancy disorder (with very limited effective treatments) characterized by hypertension (HTN) and usually proteinuria (PRO) or other organ damage. Genome-wide association studies (GWAS) of PE, HTN, and PRO have mostly identified risk loci single nucleotide polymorphisms (SNPs) located in noncoding genomic regions, likely impacting the regulation of distal gene expression. The latest GWAS associated (P < 1 × 10-6) SNPs to PE (n = 25), HTN (n = 1926), and PRO (n = 170). Our algorithmic analysis (CoDeS3D) used chromatin connection data (Hi-C) derived from 70 cell lines followed by analysis of two expression quantitative trail loci (eQTL) cohorts: GTEx (838 donors, 54 tissues, totaling 15 253 samples) and DICE (91 donors, 13 blood tissue types). We identified spatially constrained eQTLs which implicate gene targets in PE (n = 16), HTN (n = 3561), and PRO (n = 335). By overlapping these target genes and their molecular pathways (protein-protein interaction networks), we identified shared functional impacts between PE and HTN, which are significantly enriched for regulatory interactions which target genes intolerant to loss-of-function mutations. While the disease-associated SNP loci mostly do not overlap, the regulatory signals (target genes and pathways) overlap, informing on PE risk mechanisms. This demonstrates a model in which genetic predisposition to HTN and PRO lays a molecular groundwork toward risk for PE pathogenesis. This overlap at the gene regulatory network level identifies possible shared therapeutic targets for future study.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics.

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

Interpretation of the role of germline and somatic non-coding mutations in cancer: expression and chromatin conformation informed analysis.

BACKGROUND: There has been extensive scrutiny of cancer driving mutations within the exome (especially amino acid altering mutations) as these are more likely to have a clear impact on protein functions, and thus on cell biology. However, this has come at the neglect of systematic identification of regulatory (non-coding) variants, which have recently been identified as putative somatic drivers and key germline risk factors for cancer development. Comprehensive understanding of non-coding mutations requires understanding their role in the disruption of regulatory elements, which then disrupt key biological functions such as gene expression. MAIN BODY: We describe how advancements in sequencing technologies have led to the identification of a large number of non-coding mutations with uncharacterized biological significance. We summarize the strategies that have been developed to interpret and prioritize the biological mechanisms impacted by non-coding mutations, focusing on recent annotation of cancer non-coding variants utilizing chromatin states, eQTLs, and chromatin conformation data. CONCLUSION: We believe that a better understanding of how to apply different regulatory data types into the study of non-coding mutations will enhance the discovery of novel mechanisms driving cancer.

Genetic variation as a long-distance modulator of RAD21 expression in humans.

Somatic mutations and changes in expression of RAD21 are common in many types of cancer. Moreover, sub-optimal levels of RAD21 expression in early development can result in cohesinopathies. Altered RAD21 levels can result directly from mutations in the RAD21 gene. However, whether DNA variants outside of the RAD21 gene could control its expression and thereby contribute to cancer and developmental disease is unknown. In this study, we searched for genomic variants that modify RAD21expression to determine their potential to contribute to development or cancer by RAD21 dysregulation. We searched 42,953,834 genomic variants for a spatial-eQTL association with the transcription of RAD21. We identified 123 significant associations (FDR < 0.05), which are local (cis) or long-distance (trans) regulators of RAD21 expression. The 123 variants co-regulate a further seven genes (AARD, AKAP11, GRID1, KCNIP4, RCN1, TRIOBP, and USP32), enriched for having Sp2 transcription factor binding sites in their promoter regions. The Sp2 transcription factor and six of the seven genes had previously been associated with cancer onset, progression, and metastasis. Our results suggest that genome-wide variation in non-coding regions impacts on RAD21 transcript levels in addition to other genes, which then could impact on oncogenesis and the process of ubiquitination. This identification of distant co-regulation of oncogenes represents a strategy for discovery of novel genetic regions influencing cancer onset and a potential for diagnostics.

Establishing gene regulatory networks from Parkinson's disease risk loci.

The latest meta-analysis of genome-wide association studies identified 90 independent variants across 78 genomic regions associated with Parkinson's disease, yet the mechanisms by which these variants influence the development of the disease remains largely elusive. To establish the functional gene regulatory networks associated with Parkinson's disease risk variants, we utilized an approach combining spatial (chromosomal conformation capture) and functional (expression quantitative trait loci) data. We identified 518 genes subject to regulation by 76 Parkinson's variants across 49 tissues, whicih encompass 36 peripheral and 13 CNS tissues. Notably, one-third of these genes were regulated via trans-acting mechanisms (distal; risk locus-gene separated by >1 Mb, or on different chromosomes). Of particular interest is the identification of a novel trans-expression quantitative trait loci-gene connection between rs10847864 and SYNJ1 in the adult brain cortex, highlighting a convergence between familial studies and Parkinson's disease genome-wide association studies loci for SYNJ1 (PARK20) for the first time. Furthermore, we identified 16 neurodevelopment-specific expression quantitative trait loci-gene regulatory connections within the foetal cortex, consistent with hypotheses suggesting a neurodevelopmental involvement in the pathogenesis of Parkinson's disease. Through utilizing Louvain clustering we extracted nine significant and highly intraconnected clusters within the entire gene regulatory network. The nine clusters are enriched for specific biological processes and pathways, some of which have not previously been associated with Parkinson's disease. Together, our results not only contribute to an overall understanding of the mechanisms and impact of specific combinations of Parkinson's disease variants, but also highlight the potential impact gene regulatory networks may have when elucidating aetiological subtypes of Parkinson's disease.

Assigning function to SNPs: Considerations when interpreting genetic variation.

Assigning function to single nucleotide polymorphisms (SNPs) to understand the mechanisms that link genetic and phenotypic variation and disease is an area of intensive research that is necessary to contribute to the continuing development of precision medicine. However, despite the apparent simplicity that is captured in the name SNP - 'single nucleotide' changes are not easy to functionally characterize. This complexity arises from multiple features of the genome including the fact that function is development and environment specific. As such, we are often fooled by our terminology and underlying assumptions that there is a single function for a SNP. Here we discuss some of what is known about SNPs, their functions and how we can go about characterizing them.

Unravelling the Shared Genetic Mechanisms Underlying 18 Autoimmune Diseases Using a Systems Approach.

Autoimmune diseases (AiDs) are complex heterogeneous diseases characterized by hyperactive immune responses against self. Genome-wide association studies have identified thousands of single nucleotide polymorphisms (SNPs) associated with several AiDs. While these studies have identified a handful of pleiotropic loci that confer risk to multiple AiDs, they lack the power to detect shared genetic factors residing outside of these loci. Here, we integrated chromatin contact, expression quantitative trait loci and protein-protein interaction (PPI) data to identify genes that are regulated by both pleiotropic and non-pleiotropic SNPs. The PPI analysis revealed complex interactions between the shared and disease-specific genes. Furthermore, pathway enrichment analysis demonstrated that the shared genes co-occur with disease-specific genes within the same biological pathways. In conclusion, our results are consistent with the hypothesis that genetic risk loci associated with multiple AiDs converge on a core set of biological processes that potentially contribute to the emergence of polyautoimmunity.

Identifying the lungs as a susceptible site for allele-specific regulatory changes associated with type 1 diabetes risk.

Type 1 diabetes (T1D) etiology is complex. We developed a machine learning approach that ranked the tissue-specific transcription regulatory effects for T1D SNPs and estimated their relative contributions to conversion to T1D by integrating case and control genotypes (Wellcome Trust Case Control Consortium and UK Biobank) with tissue-specific expression quantitative trait loci (eQTL) data. Here we show an eQTL (rs6679677) associated with changes to AP4B1-AS1 transcript levels in lung tissue makes the largest gene regulatory contribution to the risk of T1D development. Luciferase reporter assays confirmed allele-specific enhancer activity for the rs6679677 tagged locus in lung epithelial cells (i.e. A549 cells; C > A reduces expression, p = 0.005). Our results identify tissue-specific eQTLs for SNPs associated with T1D. The strongest tissue-specific eQTL effects were in the lung and may help explain associations between respiratory infections and risk of islet autoantibody seroconversion in young children.

Transcriptional Regulation of RUNX1: An Informatics Analysis.

The RUNX1/AML1 gene encodes a developmental transcription factor that is an important regulator of haematopoiesis in vertebrates. Genetic disruptions to the RUNX1 gene are frequently associated with acute myeloid leukaemia. Gene regulatory elements (REs), such as enhancers located in non-coding DNA, are likely to be important for Runx1 transcription. Non-coding elements that modulate Runx1 expression have been investigated over several decades, but how and when these REs function remains poorly understood. Here we used bioinformatic methods and functional data to characterise the regulatory landscape of vertebrate Runx1. We identified REs that are conserved between human and mouse, many of which produce enhancer RNAs in diverse tissues. Genome-wide association studies detected single nucleotide polymorphisms in REs, some of which correlate with gene expression quantitative trait loci in tissues in which the RE is active. Our analyses also suggest that REs can be variant in haematological malignancies. In summary, our analysis identifies features of the RUNX1 regulatory landscape that are likely to be important for the regulation of this gene in normal and malignant haematopoiesis.

Strain engraftment competition and functional augmentation in a multi-donor fecal microbiota transplantation trial for obesity.

BACKGROUND: Donor selection is an important factor influencing the engraftment and efficacy of fecal microbiota transplantation (FMT) for complex conditions associated with microbial dysbiosis. However, the degree, variation, and stability of strain engraftment have not yet been assessed in the context of multiple donors. METHODS: We conducted a double-blinded randomized control trial of FMT in 87 adolescents with obesity. Participants were randomized to receive multi-donor FMT (capsules containing the fecal microbiota of four sex-matched lean donors) or placebo (saline capsules). Following a bowel cleanse, participants ingested a total of 28 capsules over two consecutive days. Capsules from individual donors and participant stool samples collected at baseline, 6, 12, and 26 weeks post-treatment were analyzed by shotgun metagenomic sequencing allowing us to track bacterial strain engraftment and its functional implications on recipients' gut microbiomes. RESULTS: Multi-donor FMT sustainably altered the structure and the function of the gut microbiome. In what was effectively a microbiome competition experiment, we discovered that two donor microbiomes (one female, one male) dominated strain engraftment and were characterized by high microbial diversity and a high Prevotella to Bacteroides (P/B) ratio. Engrafted strains led to enterotype-level shifts in community composition and provided genes that altered the metabolic potential of the community. Despite our attempts to standardize FMT dose and origin, FMT recipients varied widely in their engraftment of donor strains. CONCLUSION: Our study provides evidence for the existence of FMT super-donors whose microbiomes are highly effective at engrafting in the recipient gut. Dominant engrafting male and female donor microbiomes harbored diverse microbial species and genes and were characterized by a high P/B ratio. Yet, the high variability of strain engraftment among FMT recipients suggests the host environment also plays a critical role in mediating FMT receptivity. TRIAL REGISTRATION: The Gut Bugs trial was registered with the Australian New Zealand Clinical Trials Registry ( ACTRN12615001351505 ). TRIAL PROTOCOL: The trial protocol is available at https://bmjopen.bmj.com/content/9/4/e026174 . Video Abstract.

Low tolerance for transcriptional variation at cohesin genes is accompanied by functional links to disease-relevant pathways.

BACKGROUND: The cohesin complex plays an essential role in genome organisation and cell division. A full complement of the cohesin complex and its regulators is important for normal development, since heterozygous mutations in genes encoding these components can be sufficient to produce a disease phenotype. The implication that genes encoding the cohesin subunits or cohesin regulators must be tightly controlled and resistant to variability in expression has not yet been formally tested. METHODS: Here, we identify spatial-regulatory connections with potential to regulate expression of cohesin loci (Mitotic: SMC1A, SMC3, STAG1, STAG2, RAD21/RAD21-AS; Meiotic: SMC1B, STAG3, REC8, RAD21L1), cohesin-ring support genes (NIPBL, MAU2, WAPL, PDS5A, PDS5B) and CTCF, including linking their expression to that of other genes. We searched the genome-wide association studies (GWAS) catalogue for SNPs mapped or attributed to cohesin genes by GWAS (GWAS-attributed) and the GTEx catalogue for SNPs mapped to cohesin genes by cis-regulatory variants in one or more of 44 tissues across the human body (expression quantitative trail locus-attributed). RESULTS: Connections that centre on the cohesin ring subunits provide evidence of coordinated regulation that has little tolerance for perturbation. We used the CoDeS3D SNP-gene attribution methodology to identify transcriptional changes across a set of genes coregulated with the cohesin loci that include biological pathways such as extracellular matrix production and proteasome-mediated protein degradation. Remarkably, many of the genes that are coregulated with cohesin loci are themselves intolerant to loss-of-function. CONCLUSIONS: The results highlight the importance of robust regulation of cohesin genes and implicate novel pathways that may be important in the human cohesinopathy disorders.

Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity.

Parkinson's disease (PD) is a complex neurodegenerative disease with a range of causes and clinical presentations. Over 76 genetic loci (comprising 90 SNPs) have been associated with PD by the most recent GWAS meta-analysis. Most of these PD-associated variants are located in non-coding regions of the genome and it is difficult to understand what they are doing and how they contribute to the aetiology of PD. We hypothesised that PD-associated genetic variants modulate disease risk through tissue-specific expression quantitative trait loci (eQTL) effects. We developed and validated a machine learning approach that integrated tissue-specific eQTL data on known PD-associated genetic variants with PD case and control genotypes from the Wellcome Trust Case Control Consortium. In so doing, our analysis ranked the tissue-specific transcription effects for PD-associated genetic variants and estimated their relative contributions to PD risk. We identified roles for SNPs that are connected with INPP5P, CNTN1, GBA and SNCA in PD. Ranking the variants and tissue-specific eQTL effects contributing most to the machine learning model suggested a key role in the risk of developing PD for two variants (rs7617877 and rs6808178) and eQTL associated transcriptional changes of EAF1-AS1 within the heart atrial appendage. Similarly, effects associated with eQTLs located within the Brain Cerebellum were also recognized to confer major PD risk. These findings were replicated in two additional, independent cohorts (the UK Biobank, and NeuroX) and thus warrant further mechanistic investigations to determine if these transcriptional changes could act as early contributors to PD risk and disease development.

A systematic review of asthma case definitions in 67 birth cohort studies.

BACKGROUND: Birth cohort studies are a valuable source of information about potential risk factors for childhood asthma. To better understand similarities and variations in findings between birth cohort studies, the methodologies used to measure asthma require consideration. OBJECTIVE: To review and appraise the definitions of "asthma" used in birth cohort studies. METHODS: A literature search, conducted in December 2017 in the MEDLINE database and birth cohort repositories, identified 1721 citations published since 1990. Information extracted included: study name, year of publication, sample size, sample age, prevalence of asthma (%), study region, source of information about asthma, measured outcome, and asthma case definition. A meta-analysis evaluated whether asthma prevalence in cohorts from Europe and North America varied by the studies' definition of asthma and by their data sources. RESULTS: The final review included 67 birth cohorts, of which 48 (72%) were from Europe, 14 (21%) from North America, 3 (5%) from Oceania, 1 (1%) from Asia and 1 (1%) from South America. We identified three measured outcomes: "asthma ever", "current asthma", and "asthma" without further specification. Definitions of "asthma ever" were primarily based upon an affirmative parental response to the question whether the child had ever been diagnosed with asthma by a physician. The most frequently used definition of "current asthma" was "asthma ever" and either asthma symptoms or asthma medications in the last 12 months. This definition of "current asthma" was used in 16 cohorts. There was no statistically significant difference in the pooled asthma prevalence in European and North American cohorts that used questionnaire alone versus other data sources to classify asthma. CONCLUSION: There is substantial heterogeneity in childhood asthma definitions in birth cohort studies. Standardisation of asthma case definitions will improve the comparability and utility of future cohort studies and enable meta-analyses.

Effects of Fecal Microbiome Transfer in Adolescents With Obesity: The Gut Bugs Randomized Controlled Trial.

Importance: Treatment of pediatric obesity is challenging. Preclinical studies in mice indicated that weight and metabolism can be altered by gut microbiome manipulation. Objective: To assess efficacy of fecal microbiome transfer (FMT) to treat adolescent obesity and improve metabolism. Design, Setting, and Participants: This randomized, double-masked, placebo-controlled trial (October 2017-March 2019) with a 26-week follow-up was conducted among adolescents aged 14 to 18 years with a body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 30 or more in Auckland, New Zealand. A total of 87 individuals took part-565 individuals responded to advertisements, 328 were ineligible, and 150 declined participation. Clinical data were analyzed from September 2019 to May 2020. Interventions: Single course of oral encapsulated fecal microbiome from 4 healthy lean donors of the same sex or saline placebo. Main Outcomes and Measures: Primary outcome was BMI standard deviation score at 6 weeks using intention-to-treat analysis. Secondary outcomes included body composition, cardiometabolic parameters, well-being, and gut microbiome composition. Results: Eighty-seven participants (59% female adolescents, mean [SD] age 17.2 [1.4] years) were randomized 1:1, in groups stratified by sex, to FMT (42 participants) or placebo (45 participants). There was no effect of FMT on BMI standard deviation score at 6 weeks (adjusted mean difference [aMD] -0.026; 95% CI -0.074, 0.022). Reductions in android-to-gynoid-fat ratio in the FMT vs placebo group were observed at 6, 12, and 26 weeks, with aMDs of -0.021 (95% CI, -0.041 to -0.001), -0.023 (95% CI, -0.043 to -0.003), and -0.029 (95% CI, -0.049 to -0.008), respectively. There were no observed effects on insulin sensitivity, liver function, lipid profile, inflammatory markers, blood pressure, total body fat percentage, gut health, and health-related quality of life. Gut microbiome profiling revealed a shift in community composition among the FMT group, maintained up to 12 weeks. In post-hoc exploratory analyses among participants with metabolic syndrome at baseline, FMT led to greater resolution of this condition (18 to 4) compared with placebo (13 to 10) by 26 weeks (adjusted odds ratio, 0.06; 95% CI, 0.01-0.45; P = .007). There were no serious adverse events recorded throughout the trial. Conclusions and Relevance: In this randomized clinical trial of adolescents with obesite, there was no effect of FMT on weight loss in adolescents with obesity, although a reduction in abdominal adiposity was observed. Post-hoc analyses indicated a resolution of undiagnosed metabolic syndrome with FMT among those with this condition. Further trials are needed to confirm these results and identify organisms and mechanisms responsible for mediating the observed benefits. Trial Registration: Australian New Zealand Clinical Trials Registry Identifier: ACTRN12615001351505.

High prevalence of undiagnosed comorbidities among adolescents with obesity.

Metabolic diseases are increasing among adolescents with obesity. Although the reported prevalence of metabolic syndrome is approximately 30% worldwide, its prevalence is largely unknown among New Zealand adolescents. Therefore, we assessed the health of adolescents with obesity (BMI ≥ 30 kg/m2) enrolled in a randomised clinical trial (Gut Bugs Trial), to identify the prevalence of undiagnosed comorbidities. Assessments included anthropometry, 24-h ambulatory blood pressure monitoring, and insulin sensitivity. We report on baseline data (pre-randomisation) on 87 participants (14-18 years; 59% females), with mean BMI 36.9 ± 5.3 kg/m2 (BMI SDS 3.33 ± 0.79). Approximately 40% of participants had undiagnosed metabolic syndrome, which was twice as common among males. Half (53%) had pre-diabetes and 92% a reduction in insulin sensitivity. Moreover, 31% had pre-hypertension/hypertension, 69% dyslipidaemia, and 25% abnormal liver function. Participants with class III obesity had a greater risk of metabolic syndrome than those with classes I/II [relative risk 1.99 (95% CI 1.19, 3.34)]. Risks for pre-hypertension/hypertension and inflammation were also greater among those with class III obesity. We identified a high prevalence of undiagnosed comorbidities among adolescents with obesity in New Zealand. As adolescent obesity tracks into adulthood, early interventions are needed to prevent progression to overt cardiometabolic diseases.

Reconstructing the blood metabolome and genotype using long-range chromatin interactions.

BACKGROUND: -Maintenance of tight controls on circulating blood metabolites is crucial to normal, healthy tissue and organismal function. A number of single nucleotide polymorphisms (SNPs) have been associated with changes in the levels of blood metabolites. However, the impacts of the metabolite-associated SNPs are largely unknown because they fall within non-coding regions of the genome. OBJECTIVE: -We aimed to identify genes and tissues that are linked to changes in circulating blood metabolites by characterizing genome-wide spatial regulatory interactions involving blood metabolite-associated SNPs. METHOD: -We systematically integrated chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology, drug interaction, and literature-supported connections to deconvolute the genetic regulatory influences of 145 blood metabolite-associated SNPs. FINDINGS: -We identified 577 genes that are regulated by 130 distal and proximal metabolite-associated SNPs across 48 different human tissues. The affected genes are enriched in categories that include metabolism, enzymes, plasma proteins, disease development, and potential drug targets. Our results suggest that regulatory interactions in other tissues contribute to the modulation of blood metabolites. CONCLUSIONS: -The spatial SNP-gene-metabolite associations identified in this study expand on the list of genes and tissues that are influenced by metabolic-associated SNPs and improves our understanding of the molecular mechanisms underlying pathologic blood metabolite levels.

Differences in Compositions of Gut Bacterial Populations and Bacteriophages in 5-11 Year-Olds Born Preterm Compared to Full Term.

Preterm infants are exposed to major perinatal, post-natal, and early infancy events that could impact on the gut microbiome. These events include infection, steroid and antibiotic exposure, parenteral nutrition, necrotizing enterocolitis, and stress. Studies have shown that there are differences in the gut microbiome during the early months of life in preterm infants. We hypothesized that differences in the gut microbial composition and metabolites in children born very preterm persist into mid-childhood. Participants were healthy prepubertal children aged 5-11 years who were born very preterm (≤32 weeks of gestation; n = 51) or at term (37-41 weeks; n = 50). We recorded the gestational age, birth weight, mode of feeding, mode of birth, age, sex, and the current height and weight of our cohort. We performed a multi'omics [i.e., 16S rRNA amplicon and shotgun metagenomic sequencing, SPME-GCMS (solid-phase microextraction followed by gas chromatography-mass spectrometry)] analysis to investigate the structure and function of the fecal microbiome (as a proxy of the gut microbiota) in our cross-sectional cohort. Children born very preterm were younger (7.8 vs. 8.3 years; p = 0.034), shorter [height-standard deviation score (SDS) 0.31 vs. 0.92; p = 0.0006) and leaner [BMI (body mass index) SDS -0.20 vs. 0.29; p < 0.0001] than the term group. Children born very preterm had higher fecal calprotectin levels, decreased fecal phage richness, lower plasma arginine, lower fecal branched-chain amino acids and higher fecal volatile (i.e., 3-methyl-butanoic acid, butyrolactone, butanoic acid and pentanoic acid) profiles. The bacterial microbiomes did not differ between preterm and term groups. We speculate that the observed very preterm-specific changes were established in early infancy and may impact on the capacity of the very preterm children to respond to environmental changes.