| 41. |
- Lee, Yunsung, et al.
(författare)
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Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array
- 2020
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- 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 Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC).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.
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| 42. |
- Lessmark, Anna, et al.
(författare)
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Lipid-Associated Variants near ANGPTL3 and LPL Show Parent-of-Origin Specific Effects on Blood Lipid Levels and Obesity
- 2022
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Ingår i: Genes. - : MDPI AG. - 2073-4425. ; 13:1, s. 1-15
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Tidskriftsartikel (refereegranskat)abstract
- Parent-of-origin effects (POE) and sex-specific parental effects have been reported for plasma lipid levels, and a strong relationship exists between dyslipidemia and obesity. We aim to explore whether genetic variants previously reported to have an association to lipid traits also show POE on blood lipid levels and obesity. Families from the Botnia cohort and the Hungarian Transdanubian Biobank (HTB) were genotyped for 12 SNPs, parental origin of alleles were inferred, and generalized estimating equations were modeled to assess parental-specific associations with lipid traits and obesity. POE were observed for the variants at the TMEM57, DOCK7/ANGPTL3, LPL, and APOA on lipid traits, the latter replicated in HTB. Sex-specific parental effects were also observed; variants at ANGPTL3/DOCK7 showed POE on lipid traits and obesity in daughters only, while those at LPL and TMEM57 showed POE on lipid traits in sons. Variants at LPL and DOCK7/ANGPTL3 showed POE on obesity-related traits in Botnia and HTB, and POE effects on obesity were seen to a higher degree in daughters. This highlights the need to include analysis of POEs in genetic studies of complex traits.
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| 43. |
- Linares-Pineda, Teresa M, et al.
(författare)
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DNA methylation risk score for type 2 diabetes is associated with gestational diabetes
- 2024
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Ingår i: Cardiovascular Diabetology. - 1475-2840. ; 23
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) share many pathophysiological factors including genetics, but whether epigenetic marks are shared is unknown. We aimed to test whether a DNA methylation risk score (MRS) for T2DM was associated with GDM across ancestry and GDM criteria.METHODS: In two independent pregnancy cohorts, EPIPREG (n = 480) and EPIDG (n = 32), DNA methylation in peripheral blood leukocytes was measured at a gestational age of 28 ± 2. We constructed an MRS in EPIPREG and EPIDG based on CpG hits from a published epigenome-wide association study (EWAS) of T2DM.RESULTS: With mixed models logistic regression of EPIPREG and EPIDG, MRS for T2DM was associated with GDM: odd ratio (OR)[95% CI]: 1.3 [1.1-1.8], P = 0.002 for the unadjusted model, and 1.4 [1.1-1.7], P = 0.00014 for a model adjusted by age, pre-pregnant BMI, family history of diabetes and smoking status. Also, we found 6 CpGs through a meta-analysis (cg14020176, cg22650271, cg14870271, cg27243685, cg06378491, cg25130381) associated with GDM, and some of their methylation quantitative loci (mQTLs) were related to T2DM and GDM.CONCLUSION: For the first time, we show that DNA methylation marks for T2DM are also associated with GDM, suggesting shared epigenetic mechanisms between GDM and T2DM.
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| 44. |
- Liu, Xueming, et al.
(författare)
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Robustness and lethality in multilayer biological molecular networks
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 45. |
- Lyssenko, Valeriya, et al.
(författare)
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Genetics of type 2 diabetes : It matters from which parent we inherit the risk
- 2015
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Ingår i: Review of Diabetic Studies. - 1613-6071. ; 12:3-4, s. 233-242
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Forskningsöversikt (refereegranskat)abstract
- Type 2 diabetes (T2D) results from a co-occurrence of genes and environmental factors. There are more than 120 genetic loci suggested to be associated with T2D, or with glucose and insulin levels in European and multi-ethnic populations. Risk of T2D is higher in the offspring if the mother rather than the father has T2D. Genetically, this can be associated with a unique parent-of-origin (PoO) transmission of risk alleles, and it relates to genetic programming during the intrauterine period, resulting in the inability to increase insulin secretion in response to increased demands imposed by insulin resistance later in life. Such PoO transmission is seen for variants in the KLF14, KCNQ1, GRB10, TCF7L2, THADA, and PEG3 genes. Here we describe T2D susceptibility genes associated with defects in insulin secretion, and thereby risk of overt T2D. This review emphasizes the need to consider distorted parental transmission of risk alleles by exploring the genetic risk of T2D.
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| 46. |
- Mafessoni, Fabrizio, et al.
(författare)
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Turning vice into virtue : Using Batch-Effects to Detect Errors in Large Genomic Datasets
- 2018
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Ingår i: Genome Biology and Evolution. - : Oxford University Press (OUP). - 1759-6653. ; 10:10, s. 2697-2708
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Tidskriftsartikel (refereegranskat)abstract
- It is often unavoidable to combine data from different sequencing centers or sequencing platforms when compiling datasets with a large number of individuals. However, the different data are likely to contain specific systematic errors that will appear as SNPs. Here, we devise a method to detect systematic errors in combined datasetIs. To measure quality differences between individual genomes, we study pairs of variants that reside on different chromosomes and co-occur in individuals. The abundance of these pairs of variants in different genomes is then used to detect systematic errors due to batch effects. Applying our method to the 1000 Genomes dataset, we find that coding regions are enriched for errors, where about 1% of the higher-frequency variants are predicted to be erroneous, whereas errors outside of coding regions are much rarer (<0.001%).As expected, predicted errors are found less often than other variants in a dataset that was generated with a different sequencing technology, indicating that many of the candidates are indeed errors. However, predicted 1000 Genomes errors are also found in other large datasets; our observation is thus not specific to the 1000 Genomes dataset. Our results show that batch effects can be turned into a virtue by using the resulting variation in large scale datasets to detect systematic errors.
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| 47. |
- Mansour Aly, Dina, et al.
(författare)
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Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes
- 2021
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 53, s. 1534-1542
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Tidskriftsartikel (refereegranskat)abstract
- Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits. The severe insulin-resistant subtype was uniquely associated with GRS for fasting insulin but not with variants in the TCF7L2 locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near LRMDA was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.
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| 48. |
- Martin, Alicia R, et al.
(författare)
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Haplotype Sharing Provides Insights into Fine-Scale Population History and Disease in Finland
- 2018
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 102:5, s. 760-775
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Tidskriftsartikel (refereegranskat)abstract
- Finland provides unique opportunities to investigate population and medical genomics because of its adoption of unified national electronic health records, detailed historical and birth records, and serial population bottlenecks. We assembled a comprehensive view of recent population history (≤100 generations), the timespan during which most rare-disease-causing alleles arose, by comparing pairwise haplotype sharing from 43,254 Finns to that of 16,060 Swedes, Estonians, Russians, and Hungarians from geographically and linguistically adjacent countries with different population histories. We find much more extensive sharing in Finns, with at least one ≥ 5 cM tract on average between pairs of unrelated individuals. By coupling haplotype sharing with fine-scale birth records from more than 25,000 individuals, we find that although haplotype sharing broadly decays with geographical distance, there are pockets of excess haplotype sharing; individuals from northeast Finland typically share several-fold more of their genome in identity-by-descent segments than individuals from southwest regions. We estimate recent effective population-size changes through time across regions of Finland, and we find that there was more continuous gene flow as Finns migrated from southwest to northeast between the early- and late-settlement regions than was dichotomously described previously. Lastly, we show that haplotype sharing is locally enriched by an order of magnitude among pairs of individuals sharing rare alleles and especially among pairs sharing rare disease-causing variants. Our work provides a general framework for using haplotype sharing to reconstruct an integrative view of recent population history and gain insight into the evolutionary origins of rare variants contributing to disease.
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| 49. |
- Moen, Gunn Helen, et al.
(författare)
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Epigenetic modifications and gestational diabetes : A Systematic review of published literature
- 2017
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Ingår i: European Journal of Endocrinology. - 0804-4643. ; 176:5, s. 247-267
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Forskningsöversikt (refereegranskat)abstract
- Objective: To summarize the current knowledge on epigenetic alterations in mother and offspring subjected to gestational diabetes (GDM) and indicate future topics for research. Design: Systematic review. Methods: We performed extensive searches in PubMed, EMBASE and Google scholar, using a combination of the search terms: GDM, gestational diabetes, epigenetic(s), methylation, histone modification, histone methylation, histone acetylation, microRNA and miRNA. Studies that compared women diagnosed with GDM and healthy controls were included. Two authors independently scanned the abstracts, and all included papers were read by at least two authors. The searches were completed on October 31st, 2016. Results: We identified 236 articles, of which 43 were considered relevant for this systematic review. Studies published showed that epigenetic alterations could be found in both mothers with GDM and their offspring. However, differences in methodology, diagnostic criteria for GDM and populations studied, together with a limited number of published studies and small sample sizes, preclude clear conclusions about the role of epigenetic modifications in transmitting risk from GDM mothers to their offspring. Conclusion: The current research literature suggests that GDM may have impact on epigenetic modifications in the mother and offspring. However, larger studies that include multiple cohorts of GDM patients and their offspring are needed.
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| 50. |
- Moen, Gunn Helen, et al.
(författare)
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Genetic determinants of glucose levels in pregnancy : Genetic risk scores analysis and GWAS in the Norwegian STORK cohort
- 2018
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Ingår i: European Journal of Endocrinology. - 0804-4643. ; 179:6, s. 363-372
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Hyperglycaemia during pregnancy increases the risk of adverse health outcomes in mother and child, but the genetic aetiology is scarcely studied. Our aims were to (1) assess the overlapping genetic aetiology between the pregnant and non-pregnant population and (2) assess the importance of genome-wide polygenic contributions to glucose traits during pregnancy, by exploring whether genetic risk scores (GRSs) for fasting glucose (FG), 2-h glucose (2hG), type 2 diabetes (T2D) and BMI in non-pregnant individuals were associated with glucose measures in pregnant women. Methods: We genotyped 529 Norwegian pregnant women and constructed GRS from known genome-wide significant variants and SNPs weakly associated (p>5×10−8) with FG, 2hG, BMI and T2D from external genome-wide association studies (GWAS) and examined the association between these scores and glucose measures at gestational weeks 14-16 and 30-32. We also performed GWAS of FG, 2hG and shape information from the glucose curve during an oral glucose tolerance test (OGTT). Results: GRSFG explained similar variance during pregnancy as in the non-pregnant population (~5%). GRSBMI and GRST2D explained up to 1.3% of the variation in the glucose traits in pregnancy. If we included variants more weakly associated with these traits, GRS2hG and GRST2D explained up to 2.4% of the variation in the glucose traits in pregnancy, highlighting the importance of polygenic contributions. Conclusions: Our results suggest overlap in the genetic aetiology of FG in pregnant and non-pregnant individuals. This was less apparent with 2hG, suggesting potential differences in postprandial glucose metabolism inside and outside of pregnancy.
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