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Robustness is a prominent feature of most biological systems. Most previous related studies have been focused on homogeneous molecular networks. Here we propose a comprehensive framework for understanding how the interactions between genes, proteins and metabolites contribute to the determinants of robustness in a heterogeneous biological network. We integrate heterogeneous sources of data to construct a multilayer interaction network composed of a gene regulatory layer, a protein–protein interaction layer, and a metabolic layer. We design a simulated perturbation process to characterize the contribution of each gene to the overall system’s robustness, and find that influential genes are enriched in essential and cancer genes. We show that the proposed mechanism predicts a higher vulnerability of the metabolic layer to perturbations applied to genes associated with metabolic diseases. Furthermore, we find that the real network is comparably or more robust than expected in multiple random realizations. Finally, we analytically derive the expected robustness of multilayer biological networks starting from the degree distributions within and between layers. These results provide insights into the non-trivial dynamics occurring in the cell after a genetic perturbation is applied, confirming the importance of including the coupling between different layers of interaction in models of complex biological systems. Robustness is a prominent feature of most biological systems, but most of the current efforts have been focused on studying homogeneous molecular networks. Here the authors propose a comprehensive framework for understanding how the interactions between genes, proteins, and metabolites contribute to the determinants of robustness.

Significance We provide a comprehensive catalog of novel genetic variants influencing gene expression and metabolic phenotypes in human pancreatic islets. The data also show that the path from genetic variation (SNP) to gene expression is more complex than hitherto often assumed, and that we need to consider that genetic variation can also influence function of a gene by influencing exon usage or splice isoforms (sQTL), allelic imbalance, RNA editing, and expression of noncoding RNAs, which in turn can influence expression of target genes. Genetic variation can modulate gene expression, and thereby phenotypic variation and susceptibility to complex diseases such as type 2 diabetes (T2D). Here we harnessed the potential of DNA and RNA sequencing in human pancreatic islets from 89 deceased donors to identify genes of potential importance in the pathogenesis of T2D. We present a catalog of genetic variants regulating gene expression (eQTL) and exon use (sQTL), including many long noncoding RNAs, which are enriched in known T2D-associated loci. Of 35 eQTL genes, whose expression differed between normoglycemic and hyperglycemic individuals, siRNA of tetraspanin 33 (TSPAN33), 5′-nucleotidase, ecto (NT5E), transmembrane emp24 protein transport domain containing 6 (TMED6), and p21 protein activated kinase 7 (PAK7) in INS1 cells resulted in reduced glucose-stimulated insulin secretion. In addition, we provide a genome-wide catalog of allelic expression imbalance, which is also enriched in known T2D-associated loci. Notably, allelic imbalance in paternally expressed gene 3 (PEG3) was associated with its promoter methylation and T2D status. Finally, RNA editing events were less common in islets than previously suggested in other tissues. Taken together, this study provides new insights into the complexity of gene regulation in human pancreatic islets and better understanding of how genetic variation can influence glucose metabolism.

Aquaglyceroporin 7 (AQP7) facilitates glycerol flux across the plasma membrane with a critical physiological role linked to metabolism, obesity, and associated diseases. Here, we present the single-particle cryo-EM structure of AQP7 determined at 2.55 Å resolution adopting two adhering tetramers, stabilized by extracellularly exposed loops, in a configuration like that of the well-characterized interaction of AQP0 tetramers. The central pore, in-between the four monomers, displays well-defined densities restricted by two leucine filters. Gas chromatography mass spectrometry (GC/MS) results show that the AQP7 sample contains glycerol 3-phosphate (Gro3P), which is compatible with the identified features in the central pore. AQP7 is shown to be highly expressed in human pancreatic α- and β- cells suggesting that the identified AQP7 octamer assembly, in addition to its function as glycerol channel, may serve as junction proteins within the endocrine pancreas. Glycerol flux across the plasma membrane is critical to metabolism and linked to disease. Here, authors present the cryo-EM structure of the glycerol channel AQP7 composed of two adhering tetramers and displaying well-defined densities in the central pore.

Type 1 diabetes (T1D) is an autoimmune disease that results in the destruction of insulin producing pancreatic β-cells. One of the genes associated with T1D is TYK2 , which encodes a Janus kinase with critical roles in type-Ι interferon (IFN-Ι) mediated intracellular signalling. To study the role of TYK2 in β-cell development and response to IFNα, we generated TYK2 knockout human iPSCs and directed them into the pancreatic endocrine lineage. Here we show that loss of TYK2 compromises the emergence of endocrine precursors by regulating KRAS expression, while mature stem cell-islets (SC-islets) function is not affected. In the SC-islets, the loss or inhibition of TYK2 prevents IFNα-induced antigen processing and presentation, including MHC Class Ι and Class ΙΙ expression, enhancing their survival against CD8 + T-cell cytotoxicity. These results identify an unsuspected role for TYK2 in β-cell development and support TYK2 inhibition in adult β-cells as a potent therapeutic target to halt T1D progression. The TYK2 gene is associated with development of type 1 diabetes. Here the authors show that TYK2 regulates β-cell development, but at the same time TYK2 inhibition in the islets prevents IFNα responses and enhances their survival against CD8 +  T-cell cytotoxicity; representing a potent therapeutic target to halt T1D progression.

Genetic variants involved in vitamin D metabolism have been associated with diabetes and related syndromes/diseases. We wanted to investigate possible associations of polymorphisms in genes involved in vitamin D metabolism with indices of insulin resistance and insulin secretion, and also with development of diabetes after gestational diabetes mellitus (GDM). We have studied 376 women with previous GDM. Eight single nucleotide polymorphisms (SNPs) in the genes for vitamin D receptor (VDR) [rs731236, rs7975232, rs10735810, and rs1544410], vitamin D binding protein (DBP) [rs7041 and rs4588], and cytochrome P450 family 27 subfamily B member 1 (CYP27B1) [rs10877012 and rs4646536] were genotyped by TaqMan Allelic Discrimination Assay using the Quantstudio 7 Flex system. A 75-g oral glucose tolerance test (OGTT) was performed 1-2 years postpartum. The homeostasis model assessment of insulin resistance (HOMA-IR) and the disposition index [(insulinogenic index: I30/G30)/HOMA-IR] were used to calculate insulin resistance and insulin secretion, respectively. Serum samples for determination of 25(OH)D3 were collected at the time of the OGTT. Manifestation of diabetes was followed up to five years postpartum. After adjustment for BMI, age, and ethnicity, the A-allele of the VDR rs1544410 polymorphism was found to be associated with increased disposition index (difference per allele = 3.56, 95% CI: 0.4567-6.674; p = 0.03). The A-allele of the DBP rs7041 polymorphism was found to be associated with 25(OH)D3 levels (difference [in nmol/L] per allele = -5.478, 95% CI: -8.315 to -2.641; p = 0.0002), as was the T-allele of the DBP rs4588 polymorphism (OR = -6.319, 95% CI: -9.466 to -3.171; p = 0.0001). None of the SNPs were significantly associated with HOMA-IR or postpartum diabetes. This study provides evidence that the rs1544410 polymorphism of the VDR gene may be associated with increased insulin secretion in women after pregnancy complicated by GDM. Further studies in other populations are needed to confirm the results.

Background This study investigated whether single nucleotide polymorphisms (SNPs) reported by previous genome-wide association studies (GWAS) to be associated with impaired insulin secretion, insulin resistance, and/or type 2 diabetes are associated with disposition index, the homeostasis model assessment of insulin resistance (HOMA-IR), and/or development of diabetes following a pregnancy complicated by gestational diabetes mellitus (GDM). Methods Seventy-two SNPs were genotyped in 374 women with previous GDM from Southern Sweden. An oral glucose tolerance test was performed 1–2 years postpartum, although data on the diagnosis of diabetes were accessible up to 5 years postpartum. HOMA-IR and disposition index were used to measure insulin resistance and secretion, respectively. Results The risk A-allele in the rs11708067 polymorphism of the adenylate cyclase 5 gene ( ADCY5 ) was associated with decreased disposition index (beta = − 0.90, SE 0.38, p  = 0.019). This polymorphism was an expression quantitative trait loci (eQTL) in islets for both ADCY5 and its antisense transcript. The risk C-allele in the rs2943641 polymorphism, near the insulin receptor substrate 1 gene ( IRS1 ), showed a trend towards association with increased HOMA-IR (beta = 0.36, SE 0.18, p  = 0.050), and the T-allele of the rs4607103 polymorphism, near the ADAM metallopeptidase with thrombospondin type 1 motif 9 gene ( ADAMTS9 ), was associated with postpartum diabetes (OR = 2.12, SE 0.22, p  = 0.00055). The genetic risk score (GRS) of the top four SNPs tested for association with the disposition index using equal weights was associated with the disposition index (beta = − 0.31, SE = 0.29, p  = 0.00096). In addition, the GRS of the four SNPs studied for association with HOMA-IR using equal weights showed an association with HOMA-IR (beta = 1.13, SE = 0.48, p  = 9.72874e−11). All analyses were adjusted for age, body mass index, and ethnicity. Conclusions This study demonstrated the genetic susceptibility of women with a history of GDM to impaired insulin secretion and sensitivity and, ultimately, to diabetes development.

Background Few studies have explored the association between DNA methylation and physical activity. The aim of this study was to evaluate the association of objectively measured hours of sedentary behavior (SB) and moderate physical activity (MPA) with DNA methylation. We further aimed to explore the association between SB or MPA related CpG sites and cardiometabolic traits, gene expression, and genetic variation. Results For discovery, we performed cross sectional analyses in pregnant women from the Epigenetics in pregnancy (EPIPREG) sample with both DNA methylation (Illumina MethylationEPIC BeadChip) and objectively measured physical activity data (SenseWear™ Pro 3 armband) (European = 244, South Asian = 109). For EWAS of SB and MPA, two main models were designed: model (1) a linear mixed model adjusted for age, smoking, blood cell composition, including ancestry as random intercept, and model (2) which was additionally adjusted for the total number of steps per day. In model 1, we did not identify any CpG sites associated with neither SB nor MPA. In model 2, SB was positively associated (false discovery rate, FDR < 0.05) with two CpG sites within the VSX1 gene. Both CpG sites were positively associated with BMI and were associated with several genetic variants in cis. MPA was associated with 122 significant CpG sites at FDR < 0.05 (model 2). We further analyzed the ten most statistically significant MPA related CpG sites and found that they presented opposite associations with sedentary behavior and BMI. We were not able to replicate the SB and MPA-related CpG sites in the Avon Longitudinal Study of Parents and Children (ALSPAC). ALSPAC had available objectively measured physical activity data from Actigraph (without steps/day available) and leucocyte DNA methylation data collected during adolescence ( n  = 408, European). Conclusion This study suggests associations of objectively measured SB and MPA with maternal DNA methylation in peripheral blood leukocytes, that needs to be confirmed in larger samples of similar study design.

Pregnancy is a valuable model to study the association between DNA methylation and several cardiometabolic traits, due to its direct potential to influence mother’s and child’s health. Epigenetics in Pregnancy (EPIPREG) is a population-based sample with the aim to study associations between DNA-methylation in pregnancy and cardiometabolic traits in South Asian and European pregnant women and their offspring. This cohort profile paper aims to present our sample with genetic and epigenetic data and invite researchers with similar cohorts to collaborative projects, such as replication of ours or their results and meta-analysis. In EPIPREG we have quantified epigenome-wide DNA methylation in maternal peripheral blood leukocytes in gestational week 28±1 in Europeans (n = 312) and South Asians (n = 168) that participated in the population-based cohort STORK Groruddalen, in Norway. DNA methylation was measured with Infinium MethylationEPIC BeadChip (850k sites), with technical validation of four CpG sites using bisulphite pyrosequencing in a subset (n = 30). The sample is well characterized with few missing data on e.g. genotype, universal screening for gestational diabetes, objectively measured physical activity, bioelectrical impedance, anthropometrics, biochemical measurements, and a biobank with maternal serum and plasma, urine, placenta tissue. In the offspring, we have repeated ultrasounds during pregnancy, cord blood, and anthropometrics up to 4 years of age. We have quantified DNA methylation in peripheral blood leukocytes in nearly all eligible women from the STORK Groruddalen study, to minimize the risk of selection bias. Genetic principal components distinctly separated Europeans and South Asian women, which fully corresponded with the self-reported ethnicity. Technical validation of 4 CpG sites from the methylation bead chip showed good agreement with bisulfite pyrosequencing. We plan to study associations between DNA methylation and cardiometabolic traits and outcomes.

Background Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age. Results We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa ( n  = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO ( n  = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 ( n  = 15), GSE115278 ( n  = 108), GSE132203 ( n  = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort ( n  = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set. Conclusions Our ABECs predicted adults’ chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.