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Pan, Gang
Publications (10 of 11) Show all publications
Cavalli, M., Baltzer, N., Umer, H. M., Grau, J., Lemnian, I., Pan, G., . . . Wadelius, C. (2019). Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases. Scientific Reports, 9, Article ID 2695.
Open this publication in new window or tab >>Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases
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2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 2695Article in journal (Refereed) Published
Abstract [en]

Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2019
National Category
Medical Genetics
Identifiers
urn:nbn:se:uu:diva-379258 (URN)10.1038/s41598-019-39633-0 (DOI)000459571100059 ()30804403 (PubMedID)
Funder
Swedish Research Council, 78081Swedish National Infrastructure for Computing (SNIC)EXODIAB - Excellence of Diabetes Research in SwedenSwedish Diabetes AssociationErnfors FoundationSwedish Cancer Society, 160518German Research Foundation (DFG), GR-3526/1German Research Foundation (DFG), GR-3526/2
Available from: 2019-03-15 Created: 2019-03-15 Last updated: 2019-10-07Bibliographically approved
Karlsson, T., Rask-Andersen, M., Pan, G., Höglund, J., Wadelius, C., Ek, W. E. & Johansson, Å. (2019). Contribution of genetics to visceral adiposity and its relation to cardiovascular and metabolic disease.. Nature Medicine, 25(9), 1390-1395
Open this publication in new window or tab >>Contribution of genetics to visceral adiposity and its relation to cardiovascular and metabolic disease.
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2019 (English)In: Nature Medicine, ISSN 1078-8956, E-ISSN 1546-170X, Vol. 25, no 9, p. 1390-1395Article in journal (Refereed) Published
Abstract [en]

Visceral adipose tissue (VAT)-fat stored around the internal organs-has been suggested as an independent risk factor for cardiovascular and metabolic disease1-3, as well as all-cause, cardiovascular-specific and cancer-specific mortality4,5. Yet, the contribution of genetics to VAT, as well as its disease-related effects, are largely unexplored due to the requirement for advanced imaging technologies to accurately measure VAT. Here, we develop sex-stratified, nonlinear prediction models (coefficient of determination = 0.76; typical 95% confidence interval (CI) = 0.74-0.78) for VAT mass using the UK Biobank cohort. We performed a genome-wide association study for predicted VAT mass and identified 102 novel visceral adiposity loci. Predicted VAT mass was associated with increased risk of hypertension, heart attack/angina, type 2 diabetes and hyperlipidemia, and Mendelian randomization analysis showed visceral fat to be a causal risk factor for all four diseases. In particular, a large difference in causal effect between the sexes was found for type 2 diabetes, with an odds ratio of 7.34 (95% CI = 4.48-12.0) in females and an odds ratio of 2.50 (95% CI = 1.98-3.14) in males. Our findings bolster the role of visceral adiposity as a potentially independent risk factor, in particular for type 2 diabetes in Caucasian females. Independent validation in other cohorts is necessary to determine whether the findings can translate to other ethnicities, or outside the UK.

National Category
Medical Genetics
Identifiers
urn:nbn:se:uu:diva-392977 (URN)10.1038/s41591-019-0563-7 (DOI)000484832800021 ()31501611 (PubMedID)
Funder
Swedish National Infrastructure for Computing (SNIC), b2016021Swedish National Infrastructure for Computing (SNIC), sens2017538Swedish Society for Medical Research (SSMF)Swedish Research Council, 2015-03327Göran Gustafsson Foundation for Research in Natural Sciences and MedicineÅke Wiberg Foundation, M16-0210Swedish Heart Lung Foundation, 20170484Swedish Diabetes AssociationScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Available from: 2019-09-12 Created: 2019-09-12 Last updated: 2019-11-20Bibliographically approved
Diamanti, K., Cavalli, M., Pan, G., Pereira, M. J., Kumar, C., Skrtic, S., . . . Wadelius, C. (2019). Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes. Scientific Reports, 9, Article ID 9653.
Open this publication in new window or tab >>Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes
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2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 9653Article in journal (Refereed) Published
Abstract [en]

Type 2 diabetes (T2D) mellitus is a complex metabolic disease commonly caused by insulin resistance in several tissues. We performed a matched two-dimensional metabolic screening in tissue samples from 43 multi-organ donors. The intra-individual analysis was assessed across five key metabolic tissues (serum, visceral adipose tissue, liver, pancreatic islets and skeletal muscle), and the inter-individual across three different groups reflecting T2D progression. We identified 92 metabolites differing significantly between non-diabetes and T2D subjects. In diabetes cases, carnitines were significantly higher in liver, while lysophosphatidylcholines were significantly lower in muscle and serum. We tracked the primary tissue of origin for multiple metabolites whose alterations were reflected in serum. An investigation of three major stages spanning from controls, to pre-diabetes and to overt T2D indicated that a subset of lysophosphatidylcholines was significantly lower in the muscle of pre-diabetes subjects. Moreover, glycodeoxycholic acid was significantly higher in liver of pre-diabetes subjects while additional increase in T2D was insignificant. We confirmed many previously reported findings and substantially expanded on them with altered markers for early and overt T2D. Overall, the analysis of this unique dataset can increase the understanding of the metabolic interplay between organs in the development of T2D.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2019
National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:uu:diva-391017 (URN)10.1038/s41598-019-45906-5 (DOI)000474222900010 ()31273253 (PubMedID)
Funder
AstraZenecaSwedish Research Council FormaseSSENCE - An eScience CollaborationSwedish Diabetes AssociationErnfors Foundation
Available from: 2019-08-21 Created: 2019-08-21 Last updated: 2019-09-22Bibliographically approved
Cavalli, M., Baltzer, N., Pan, G., Walls, J. R., Garbulowska, K. S., Kumar, C., . . . Wadelius, C. (2019). Studies of liver tissue identify functional gene regulatory elements associated to gene expression, type 2 diabetes, and other metabolic diseases. HUMAN GENOMICS, 13, Article ID 20.
Open this publication in new window or tab >>Studies of liver tissue identify functional gene regulatory elements associated to gene expression, type 2 diabetes, and other metabolic diseases
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2019 (English)In: HUMAN GENOMICS, ISSN 1473-9542, Vol. 13, article id 20Article in journal (Refereed) Published
Abstract [en]

Background:

Genome-wide association studies (GWAS) of diseases and traits have found associations to gene regions but not the functional SNP or the gene mediating the effect. Difference in gene regulatory signals can be detected using chromatin immunoprecipitation and next-gen sequencing (ChIP-seq) of transcription factors or histone modifications by aligning reads to known polymorphisms in individual genomes. The aim was to identify such regulatory elements in the human liver to understand the genetics behind type 2 diabetes and metabolic diseases.

Methods:

The genome of liver tissue was sequenced using 10X Genomics technology to call polymorphic positions. Using ChIP-seq for two histone modifications, H3K4me3 and H3K27ac, and the transcription factor CTCF, and our established bioinformatics pipeline, we detected sites with significant difference in signal between the alleles.

Results:

We detected 2329 allele-specific SNPs (AS-SNPs) including 25 associated to GWAS SNPs linked to liver biology, e.g., 4 AS-SNPs at two type 2 diabetes loci. Two hundred ninety-two AS-SNPs were associated to liver gene expression in GTEx, and 134 AS-SNPs were located on 166 candidate functional motifs and most of them in EGR1-binding sites.

Conclusions:

This study provides a valuable collection of candidate liver regulatory elements for further experimental validation.

Keywords
ChIP-seq, T2D, Regulatory SNPs
National Category
Medical Genetics Bioinformatics and Systems Biology
Identifiers
urn:nbn:se:uu:diva-383513 (URN)10.1186/s40246-019-0204-8 (DOI)000466335200001 ()31036066 (PubMedID)
Available from: 2019-05-16 Created: 2019-05-16 Last updated: 2019-10-07Bibliographically approved
Cavalli, M., Pan, G., Nord, H., Wallén Arzt, E., Wallerman, O. & Wadelius, C. (2017). Genetic prevention of hepatitis C virus-induced liver fibrosis by allele-specific downregulation of MERTK. Hepatology Research, 47(8), 826-830
Open this publication in new window or tab >>Genetic prevention of hepatitis C virus-induced liver fibrosis by allele-specific downregulation of MERTK
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2017 (English)In: Hepatology Research, ISSN 1386-6346, E-ISSN 1872-034X, Vol. 47, no 8, p. 826-830Article in journal (Refereed) Published
Abstract [en]

AIM: Infection by hepatitis C virus (HCV) can result in the development of liver fibrosis and may eventually progress into cirrhosis and hepatocellular carcinoma. However, the molecular mechanisms for this process are not fully known. Several genome-wide association studies have been carried out to pinpoint causative variants in HCV-infected patient cohorts, but these variants are usually not the functional ones. The aim of this study was to identify the regulatory single nucleotide polymorphism associated with the risk of HCV-induced liver fibrosis and elucidate its molecular mechanism.

METHODS: We utilized a bioinformatics approach to identify a non-coding regulatory variant, located in an intron of the MERTK gene, based on differential transcription factor binding between the alleles. We validated the results using expression reporter assays and electrophoresis mobility shift assays.

RESULTS: Chromatin immunoprecipitation sequencing indicated that transcription factor(s) bind stronger to the A allele of rs6726639. Electrophoresis mobility shift assays supported these findings and suggested that the transcription factor is interferon regulatory factor 1 (IRF1). Luciferase report assays showed lower enhancer activity from the A allele and that IRF1 may act as a repressor.

CONCLUSIONS: Treatment of hepatitis C with interferon-α results in increased IRF1 levels and our data suggest that this leads to an allele-specific downregulation of MERTK mediated by an allelic effect on the regulatory element containing the functional rs6726639. This variant also shows the hallmarks for being the driver of the genome-wide association studies for reduced risk of liver fibrosis and non-alcoholic fatty liver disease at MERTK.

Keywords
MERTK, hepatitis C virus, liver fibrosis, single nucleotide polymorphism
National Category
Basic Medicine
Identifiers
urn:nbn:se:uu:diva-318340 (URN)10.1111/hepr.12810 (DOI)000404794000012 ()27577861 (PubMedID)
Funder
Swedish Cancer Society, 15 0878Swedish Research Council, A0350501Swedish Diabetes Association, 2015-064
Available from: 2017-03-24 Created: 2017-03-24 Last updated: 2018-01-13Bibliographically approved
Pan, G., Ameur, A., Enroth, S., Bysani, M., Nord, H., Cavalli, M., . . . Wadelius, C. (2017). PATZ1 down-regulates FADS1 by binding to rs174557 and is opposed by SP1/SREBP1c. Nucleic Acids Research, 45(5), 2408-2422
Open this publication in new window or tab >>PATZ1 down-regulates FADS1 by binding to rs174557 and is opposed by SP1/SREBP1c
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2017 (English)In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 45, no 5, p. 2408-2422Article in journal (Refereed) Published
Abstract [en]

The FADS1 and FADS2 genes in the FADS cluster encode the rate-limiting enzymes in the synthesis of long-chain polyunsaturated fatty acids (LC-PUFAs). Genetic variation in this region has been associated with a large number of diseases and traits many of them correlated to differences in metabolism of PUFAs. However, the causative variants leading to these associations have not been identified. Here we find that the multiallelic rs174557 located in an AluYe5 element in intron 1 of FADS1 is functional and lies within a PATZ1 binding site. The derived allele of rs174557, which is the common variant in most populations, diminishes binding of PATZ1, a transcription factor conferring allele-specific downregulation of FADS1 The PATZ1 binding site overlaps with a SP1 site. The competitive binding between the suppressive PATZ1 and the activating complex of SP1 and SREBP1c determines the enhancer activity of this region, which regulates expression of FADS1.

National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:uu:diva-317999 (URN)10.1093/nar/gkw1186 (DOI)000397286600024 ()27932482 (PubMedID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceSwedish Research Council, 521-2010-3505 6212011-6052 521-2012-2884Swedish Diabetes AssociationSwedish Cancer Society, 15 0878
Available from: 2017-03-23 Created: 2017-03-23 Last updated: 2017-04-18Bibliographically approved
Cavalli, M., Pan, G., Nord, H., Arzt, E. W., Wallerman, O. & Wadelius, C. (2016). Allele-specific transcription factor binding in liver and cervix cells unveils many likely drivers of GWAS signals. Genomics, 107(6), 248-254
Open this publication in new window or tab >>Allele-specific transcription factor binding in liver and cervix cells unveils many likely drivers of GWAS signals
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2016 (English)In: Genomics, ISSN 0888-7543, E-ISSN 1089-8646, Vol. 107, no 6, p. 248-254Article in journal (Refereed) Published
Abstract [en]

Genome-wide association studies (GWAS) point to regions with associated genetic variants but rarely to a specific gene and therefore detailed knowledge regarding the genes contributing to complex traits and diseases remains elusive. The functional role of GWAS-SNPs is also affected by linkage disequilibrium with many variants on the same haplotype and sometimes in the same regulatory element almost equally likely to mediate the effect. Using ChIP-seq data on many transcription factors, we pinpointed genetic variants in HepG2 and HeLa-S3 cell lines which show a genome-wide significant difference in binding between alleles. We identified a collection of 3713 candidate functional regulatory variants many of which are likely drivers of GWAS signals or genetic difference in expression. A recent study investigated many variants before finding the functional ones at the GALNT2 locus, which we found in our genome-wide screen in HepG2. This illustrates the efficiency of our approach.

Keywords
Allele-specific regulation, Association to GWAS/eQTLs, Functional variants
National Category
Medical Genetics
Identifiers
urn:nbn:se:uu:diva-299903 (URN)10.1016/j.ygeno.2016.04.006 (DOI)000378623700004 ()27126307 (PubMedID)
Funder
Swedish Research Council, 2010-3505Swedish Diabetes Association, 2015-064
Available from: 2016-07-29 Created: 2016-07-29 Last updated: 2018-01-10Bibliographically approved
Cavalli, M., Pan, G., Nord, H., Wallerman, O., Arzt, E. W., Berggren, O., . . . Wadelius, C. (2016). Allele-specific transcription factor binding to common and rare variants associated with disease and gene expression. Human Genetics, 135(5), 485-497
Open this publication in new window or tab >>Allele-specific transcription factor binding to common and rare variants associated with disease and gene expression
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2016 (English)In: Human Genetics, ISSN 0340-6717, E-ISSN 1432-1203, Vol. 135, no 5, p. 485-497Article in journal (Refereed) Published
Abstract [en]

Genome-wide association studies (GWAS) have identified a large number of disease-associated SNPs, but in few cases the functional variant and the gene it controls have been identified. To systematically identify candidate regulatory variants, we sequenced ENCODE cell lines and used public ChIP-seq data to look for transcription factors binding preferentially to one allele. We found 9962 candidate regulatory SNPs, of which 16 % were rare and showed evidence of larger functional effect than common ones. Functionally rare variants may explain divergent GWAS results between populations and are candidates for a partial explanation of the missing heritability. The majority of allele-specific variants (96 %) were specific to a cell type. Furthermore, by examining GWAS loci we found >400 allele-specific candidate SNPs, 141 of which were highly relevant in our cell types. Functionally validated SNPs support identification of an SNP in SYNGR1 which may expose to the risk of rheumatoid arthritis and primary biliary cirrhosis, as well as an SNP in the last intron of COG6 exposing to the risk of psoriasis. We propose that by repeating the ChIP-seq experiments of 20 selected transcription factors in three to ten people, the most common polymorphisms can be interrogated for allele-specific binding. Our strategy may help to remove the current bottleneck in functional annotation of the genome.

National Category
Medical Genetics
Identifiers
urn:nbn:se:uu:diva-297809 (URN)10.1007/s00439-016-1654-x (DOI)000374459200004 ()26993500 (PubMedID)
Funder
Swedish National Infrastructure for Computing (SNIC), b2010003Swedish National Infrastructure for Computing (SNIC), b2011107Swedish Research Council, 541-2013-8161Swedish Diabetes AssociationKnut and Alice Wallenberg Foundation
Available from: 2016-06-28 Created: 2016-06-28 Last updated: 2018-01-10Bibliographically approved
Cavalli, M., Pan, G., Nord, H. & Wadelius, C. (2016). Looking beyond GWAS: allele-specific transcription factor binding drives the association of GALNT2 to HDL-C plasma levels. Lipids in Health and Disease, 15, Article ID 18.
Open this publication in new window or tab >>Looking beyond GWAS: allele-specific transcription factor binding drives the association of GALNT2 to HDL-C plasma levels
2016 (English)In: Lipids in Health and Disease, ISSN 1476-511X, E-ISSN 1476-511X, Vol. 15, article id 18Article in journal (Refereed) Published
Abstract [en]

Background: Plasma levels of high-density lipoprotein cholesterol (HDL-C) have been associated to cardiovascular disease. The high heritability of HDL-C plasma levels has been an incentive for several genome wide association studies (GWASs) which identified, among others, variants in the first intron of the GALNT2 gene strongly associated to HDL-C levels. However, the lead GWAS SNP associated to HDL-C levels in this genomic region, rs4846914, is located outside of transcription factor (TF) binding sites defined by chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) experiments in the ENCODE project and is therefore unlikely to be functional. In this study we apply a bioinformatics approach which rely on the premise that ChIP-seq reads can identify allele specific binding of a TF at cell specific regulatory elements harboring allele specific SNPs (AS-SNPs). EMSA and luciferase assays were used to validate the allele specific binding and to test the enhancer activity of the regulatory element harboring the AS-SNP rs4846913 as well as the neighboring rs2144300 which are in high LD with rs4846914. Findings: Using luciferase assays we found that rs4846913 and the neighboring rs2144300 displayed allele specific enhancer activity. We propose that an inhibitor binds preferentially to the rs4846913-C allele with an inhibitory boost from the synergistic binding of other TFs at the neighboring SNP rs2144300. These events influence the transcription level of GALNT2. Conclusions: The results suggest that rs4846913 and rs2144300 drive the association to HDL-C plasma levels through an inhibitory regulation of GALNT2 rather than the reported lead GWAS SNP rs4846914.

Keywords
AS-SNPs, GWAS, HDL-C, GALNT2
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy) Nutrition and Dietetics
Identifiers
urn:nbn:se:uu:diva-279591 (URN)10.1186/s12944-016-0183-x (DOI)000369362800001 ()26817450 (PubMedID)
Funder
Swedish Research CouncilSwedish Diabetes Association
Available from: 2016-03-02 Created: 2016-03-02 Last updated: 2017-11-30Bibliographically approved
Diamanti, K., Visvanathar, R., Pereira, M. J., Cavalli, M., Pan, G., Kumar, C., . . . Komorowski, J.Integration of whole-body PET/MRI with non-targeted metabolomics provides new insights into insulin sensitivity of various tissues.
Open this publication in new window or tab >>Integration of whole-body PET/MRI with non-targeted metabolomics provides new insights into insulin sensitivity of various tissues
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Background: Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific alterations is challenging and requires a multi-omics approach. In this study, we aimed at discovering associations of metabolites from subcutaneous adipose tissue (SAT) and plasma with the volume, the fat fraction (FF) and the insulin sensitivity (Ki) of specific tissues using [18F]FDG PET/MRI.

Materials and Methods: In a cohort of 42 subjects with different levels of glucose tolerance (normal, prediabetes and T2D) matched for age and body-mass-index (BMI) we calculated associations between parameters of whole-body FDG PET/MRI during clamp and non-targeted metabolomics profiling for SAT and blood plasma. We also used a rule-based classifier to identify a large collection of prevalent patterns of co-dependent metabolites that characterize non-diabetes (ND) and T2D.

Results: The plasma metabolomics profiling revealed that hepatic fat content was positively associated with tyrosine, and negatively associated with lysoPC(P-16:0). Ki in visceral adipose tissue (VAT) and SAT, was positively associated with several species of lysophospholipids while the opposite applied to branched-chain amino acids (BCAA) and their intermediates. The adipose tissue metabolomics revealed a positive association between non-esterified fatty acids and, VAT and liver Ki. On the contrary, bile acids and carnitines in adipose tissue were inversely associated with VAT Ki. Finally, we presented a transparent machine-learning model that predicted ND or T2D in “unseen” data with an accuracy of 78%.

Conclusions: Novel associations of several metabolites from SAT and plasma with the FF, volume and insulin senstivity of various tissues throughout the body were discovered using PET/MRI and a new integrative multi-omics approach. A promising computational model that predicted ND and T2D with high certainty, suggested novel non-linear interdependencies of metabolites.

Keywords
type 2 diabetes; metabolomics; imiomics; PET/MRI; insulin resistance;
National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:uu:diva-393429 (URN)
Available from: 2019-09-21 Created: 2019-09-21 Last updated: 2019-09-22
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