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Schmitz D, Li Z, Lo Faro V, Rask-Andersen M, Ameur A, Rafati N, Johansson Å. Copy number variations and their effect on the plasma proteome. Genetics 2023; 225:iyad179. [PMID: 37793096 PMCID: PMC10697815 DOI: 10.1093/genetics/iyad179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 08/25/2023] [Accepted: 09/15/2023] [Indexed: 10/06/2023] Open
Abstract
Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.
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Affiliation(s)
- Daniel Schmitz
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Box 815, 751 08 Uppsala, Sweden
| | - Zhiwei Li
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Box 815, 751 08 Uppsala, Sweden
| | - Valeria Lo Faro
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Box 815, 751 08 Uppsala, Sweden
| | - Mathias Rask-Andersen
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Box 815, 751 08 Uppsala, Sweden
| | - Adam Ameur
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Box 815, 751 08 Uppsala, Sweden
| | - Nima Rafati
- Department of Medical Biochemistry and Microbiology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Box 582, 751 23 Uppsala, Sweden
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Box 815, 751 08 Uppsala, Sweden
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2
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Llobet MO, Johansson A, Gyllensten U, Allen M, Enroth S. Forensic prediction of sex, age, height, body mass index, hip-to-waist ratio, smoking status and lipid lowering drugs using epigenetic markers and plasma proteins. Forensic Sci Int Genet 2023; 65:102871. [PMID: 37054667 DOI: 10.1016/j.fsigen.2023.102871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 04/08/2023]
Abstract
The prediction of human characteristics from blood using molecular markers would be very helpful in forensic science. Such information can be particularly important in providing investigative leads in police casework from, for example, blood found at crime scenes in cases without a suspect. Here, we investigated the possibilities and limitations of predicting seven phenotypic traits (sex, age, height, body mass index [BMI], hip-to-waist [WTH] ratio, smoking status and lipid-lowering drug use) using either DNA methylation or plasma proteins separately or in combination. We developed a prediction pipeline starting with the prediction of sex followed by sex-specific, stepwise, individual age, sex-specific anthropometric traits and, finally, lifestyle-related traits. Our data revealed that age, sex and smoking status can be accurately predicted from DNA methylation alone, while the use of plasma proteins was highly accurate for prediction of the WTH ratio, and a combined analysis of the best predictions for BMI and lipid-lowering drug use. In unseen individuals, age was predicted with a standard error of 3.3 years for women and 6.5 years for men, while the accuracy in smoking prediction across both men and women was 0.86. In conclusion, we have developed a stepwise approach for the de-novo prediction of individual characteristics from plasma proteins and DNA methylation markers. These models are accurate and may provide valuable information and investigative leads in future forensic casework.
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Fujikawa T, Kobayashi M, Wagner S, Duarte K, Scherdel P, Heude B, Dupont V, Bozec E, Bresso E, Zannad F, Rossignol P, Girerd N. Associations of childhood adiposity with adult intima-media thickness and inflammation: a 20-year longitudinal population-based cohort. J Hypertens 2023; 41:402-410. [PMID: 36728849 DOI: 10.1097/hjh.0000000000003343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND The associations between childhood adiposity and adult increased carotid intima-media thickness (cIMT) have been well established, which might be corroborated by the association between adiposity in children and inflammation in adults. However, longitudinal data regarding biological pathways associated with childhood adiposity are lacking. METHODS The current study included participants from the STANISLAS cohort who had adiposity measurements at age 5-18 years [ N = 519, mean (SD) age, 13.0 (2.9) years; 46.4% male], and who were measured with cIMT, vascular-related and metabolic-related proteins at a median follow-up of 19 ± 2 years. BMI, waist-to-height ratio and waist circumference were converted to age-specific and sex-specific z -scores. RESULTS A minority of children were overweight/obese (16.2% overweight-BMI z -score >1; 1.3% obesity- z -score >2). Higher BMI, waist-height ratio and waist circumference in children were significantly associated with greater adult cIMT in univariable analysis, although not after adjusting for C-reactive protein. These associations were more pronounced in those with consistently high adiposity status from childhood to middle adulthood. Participants with higher adiposity during childhood (BMI or waist-height ratio) had higher levels of insulin-like growth factor-binding protein-1, protein-2, matrix metalloproteinase-3, osteopontin, hemoglobin and C-reactive protein in adulthood. Network analysis showed that IL-6, insulin-like growth factor-1 and fibronectin were the key proteins associated with childhood adiposity. CONCLUSION In a population-based cohort followed for 20 years, higher BMI or waist-to-height ratio in childhood was significantly associated with greater cIMT and enhanced levels of proteins reflective of inflammation, supporting the importance of inflammation as progressive atherosclerosis in childhood adiposity.
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Affiliation(s)
- Tomona Fujikawa
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
| | - Masatake Kobayashi
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
| | - Sandra Wagner
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
| | - Kevin Duarte
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
| | - Pauline Scherdel
- INSERM, UMR1153 Epidemiology and Biostatistics Sorbonne Paris Cité Center (CRESS), Early Determinants of the Child's Health and Development Team (ORCHAD), Paris
| | - Barbara Heude
- INSERM, UMR1153 Epidemiology and Biostatistics Sorbonne Paris Cité Center (CRESS), Early Determinants of the Child's Health and Development Team (ORCHAD), Paris
| | - Vincent Dupont
- Departement of Nephrology, Centre Hospitalier Universitaire de Reims
- French Clinical Research Infrastructure Network, Investigation Network Initiative - Cardiovascular and Renal Clinical Trialists (F-CRIN INI-CRCT), Reims, France
| | - Erwan Bozec
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
| | - Emmanuel Bresso
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
| | - Faiez Zannad
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
| | - Patrick Rossignol
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
| | - Nicolas Girerd
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, INSERM 1116, CHRU de Nancy
- F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, Nancy
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Emilsson V, Gudmundsson EF, Jonmundsson T, Jonsson BG, Twarog M, Gudmundsdottir V, Li Z, Finkel N, Poor S, Liu X, Esterberg R, Zhang Y, Jose S, Huang CL, Liao SM, Loureiro J, Zhang Q, Grosskreutz CL, Nguyen AA, Huang Q, Leehy B, Pitts R, Aspelund T, Lamb JR, Jonasson F, Launer LJ, Cotch MF, Jennings LL, Gudnason V, Walshe TE. A proteogenomic signature of age-related macular degeneration in blood. Nat Commun 2022; 13:3401. [PMID: 35697682 PMCID: PMC9192739 DOI: 10.1038/s41467-022-31085-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 06/01/2022] [Indexed: 12/28/2022] Open
Abstract
Age-related macular degeneration (AMD) is one of the most common causes of visual impairment in the elderly, with a complex and still poorly understood etiology. Whole-genome association studies have discovered 34 genomic regions associated with AMD. However, the genes and cognate proteins that mediate the risk, are largely unknown. In the current study, we integrate levels of 4782 human serum proteins with all genetic risk loci for AMD in a large population-based study of the elderly, revealing many proteins and pathways linked to the disease. Serum proteins are also found to reflect AMD severity independent of genetics and predict progression from early to advanced AMD after five years in this population. A two-sample Mendelian randomization study identifies several proteins that are causally related to the disease and are directionally consistent with the observational estimates. In this work, we present a robust and unique framework for elucidating the pathobiology of AMD. Age related macular degeneration is a common cause of visual impairment in the elderly, but the etiology is not fully understood. Here, the authors use genetic data, serum proteomics, and AMD phenotypic data from a large Icelandic cohort to discover proteins altered in, causally related to AMD or signifying progression of advanced AMD.
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Affiliation(s)
- Valur Emilsson
- Icelandic Heart Association, Holtasmari 1, IS-201, Kopavogur, Iceland. .,Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland.
| | | | | | | | - Michael Twarog
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Holtasmari 1, IS-201, Kopavogur, Iceland.,Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Zhiguang Li
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD, USA
| | - Nancy Finkel
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Stephen Poor
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Xin Liu
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Robert Esterberg
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Yiyun Zhang
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Sandra Jose
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Chia-Ling Huang
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Sha-Mei Liao
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Joseph Loureiro
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Qin Zhang
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Cynthia L Grosskreutz
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Andrew A Nguyen
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Qian Huang
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Barrett Leehy
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Rebecca Pitts
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Thor Aspelund
- Icelandic Heart Association, Holtasmari 1, IS-201, Kopavogur, Iceland
| | - John R Lamb
- Novartis Institutes for Biomedical Research, 10675 John Jay Hopkins Drive, San Diego, CA, 92121, USA
| | - Fridbert Jonasson
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland.,Department of Ophthalmology, University Hospital, Reykjavik, Iceland
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD, USA
| | - Mary Frances Cotch
- Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Holtasmari 1, IS-201, Kopavogur, Iceland.,Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Tony E Walshe
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA.
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Proteostasis Response to Protein Misfolding in Controlled Hypertension. Cells 2022; 11:cells11101686. [PMID: 35626723 PMCID: PMC9139827 DOI: 10.3390/cells11101686] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/14/2022] [Accepted: 05/16/2022] [Indexed: 12/04/2022] Open
Abstract
Hypertension is the most determinant risk factor for cardiovascular diseases. Early intervention and future therapies targeting hypertension mechanisms may improve the quality of life and clinical outcomes. Hypertension has a complex multifactorial aetiology and was recently associated with protein homeostasis (proteostasis). This work aimed to characterize proteostasis in easy-to-access plasma samples from 40 individuals, 20 with controlled hypertension and 20 age- and gender-matched normotensive individuals. Proteostasis was evaluated by quantifying the levels of protein aggregates through different techniques, including fluorescent probes, slot blot immunoassays and Fourier-transform infrared spectroscopy (FTIR). No significant between-group differences were observed in the absolute levels of various protein aggregates (Proteostat or Thioflavin T-stained aggregates; prefibrillar oligomers and fibrils) or total levels of proteostasis-related proteins (Ubiquitin and Clusterin). However, significant positive associations between Endothelin 1 and protein aggregation or proteostasis biomarkers (such as fibrils and ubiquitin) were only observed in the hypertension group. The same is true for the association between the proteins involved in quality control and protein aggregates. These results suggest that proteostasis mechanisms are actively engaged in hypertension as a coping mechanism to counteract its pathological effects in proteome stability, even when individuals are chronically medicated and presenting controlled blood pressure levels.
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Contribution of rare whole-genome sequencing variants to plasma protein levels and the missing heritability. Nat Commun 2022; 13:2532. [PMID: 35534486 PMCID: PMC9085767 DOI: 10.1038/s41467-022-30208-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 04/21/2022] [Indexed: 12/03/2022] Open
Abstract
Despite the success of genome-wide association studies, much of the genetic contribution to complex traits remains unexplained. Here, we analyse high coverage whole-genome sequencing data, to evaluate the contribution of rare genetic variants to 414 plasma proteins. The frequency distribution of genetic variants is skewed towards the rare spectrum, and damaging variants are more often rare. We estimate that less than 4.3% of the narrow-sense heritability is expected to be explained by rare variants in our cohort. Using a gene-based approach, we identify Cis-associations for 237 of the proteins, which is slightly more compared to a GWAS (N = 213), and we identify 34 associated loci in Trans. Several associations are driven by rare variants, which have larger effects, on average. We therefore conclude that rare variants could be of importance for precision medicine applications, but have a more limited contribution to the missing heritability of complex diseases. Despite the success of genome-wide association studies, much of the genetic contribution to complex traits remains unexplained. Here, the authors identify effects by rare variants on plasma proteins, and estimate the contribution of rare variants to the heritability.
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7
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Proteome-wide Mendelian randomization identifies causal links between blood proteins and severe COVID-19. PLoS Genet 2022; 18:e1010042. [PMID: 35239653 PMCID: PMC8893330 DOI: 10.1371/journal.pgen.1010042] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 01/18/2022] [Indexed: 12/30/2022] Open
Abstract
In November 2021, the COVID-19 pandemic death toll surpassed five million individuals. We applied Mendelian randomization including >3,000 blood proteins as exposures to identify potential biomarkers that may indicate risk for hospitalization or need for respiratory support or death due to COVID-19, respectively. After multiple testing correction, using genetic instruments and under the assumptions of Mendelian Randomization, our results were consistent with higher blood levels of five proteins GCNT4, CD207, RAB14, C1GALT1C1, and ABO being causally associated with an increased risk of hospitalization or respiratory support/death due to COVID-19 (ORs = 1.12-1.35). Higher levels of FAAH2 were solely associated with an increased risk of hospitalization (OR = 1.19). On the contrary, higher levels of SELL, SELE, and PECAM-1 decrease risk of hospitalization or need for respiratory support/death (ORs = 0.80-0.91). Higher levels of LCTL, SFTPD, KEL, and ATP2A3 were solely associated with a decreased risk of hospitalization (ORs = 0.86-0.93), whilst higher levels of ICAM-1 were solely associated with a decreased risk of respiratory support/death of COVID-19 (OR = 0.84). Our findings implicate blood group markers and binding proteins in both hospitalization and need for respiratory support/death. They, additionally, suggest that higher levels of endocannabinoid enzymes may increase the risk of hospitalization. Our research replicates findings of blood markers previously associated with COVID-19 and prioritises additional blood markers for risk prediction of severe forms of COVID-19. Furthermore, we pinpoint druggable targets potentially implicated in disease pathology.
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8
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Thomas CE, Dahl L, Byström S, Chen Y, Uhlén M, Mälarstig A, Czene K, Hall P, Schwenk JM, Gabrielson M. Circulating proteins reveal prior use of menopausal hormonal therapy and increased risk of breast cancer. Transl Oncol 2022; 17:101339. [PMID: 35033985 PMCID: PMC8760550 DOI: 10.1016/j.tranon.2022.101339] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/18/2021] [Accepted: 12/31/2021] [Indexed: 11/15/2022] Open
Abstract
Accessible risk predictors are crucial for improving the early detection and prognosis of breast cancer. Blood samples are widely available and contain proteins that provide important information about human health and disease, however, little is still known about the contribution of circulating proteins to breast cancer risk prediction. We profiled EDTA plasma samples collected before diagnosis from the Swedish KARMA breast cancer cohort to evaluate circulating proteins as molecular predictors. A data-driven analysis strategy was applied to the molecular phenotypes built on 700 circulating proteins to identify and annotate clusters of women. The unsupervised analysis of 183 future breast cancer cases and 366 age-matched controls revealed five stable clusters with distinct proteomic plasma profiles. Among these women, those in the most stable cluster (N = 19; mean Jaccard index: 0.70 ± 0.29) were significantly more likely to have used menopausal hormonal therapy (MHT), get a breast cancer diagnosis, and were older compared to the remaining clusters. The circulating proteins associated with this cluster (FDR < 0.001) represented physiological processes related to cell junctions (F11R, CLDN15, ITGAL), DNA repair (RBBP8), cell replication (TJP3), and included proteins found in female reproductive tissue (PTCH1, ZP4). Using a data-driven approach on plasma proteomics data revealed the potential long-lasting molecular effects of menopausal hormonal therapy (MHT) on the circulating proteome, even after women had ended their treatment. This provides valuable insights concerning proteomics efforts to identify molecular markers for breast cancer risk prediction.
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Affiliation(s)
- Cecilia E Thomas
- Science for Life Laboratory, Department of Protein Science School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Tomtebodavägen 23, Solna, Stockholm 171 65, Sweden
| | - Leo Dahl
- Science for Life Laboratory, Department of Protein Science School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Tomtebodavägen 23, Solna, Stockholm 171 65, Sweden
| | - Sanna Byström
- Science for Life Laboratory, Department of Protein Science School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Tomtebodavägen 23, Solna, Stockholm 171 65, Sweden
| | - Yan Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet Nobels väg 12A, Stockholm SE-171 77, Sweden; Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Mathias Uhlén
- Science for Life Laboratory, Department of Protein Science School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Tomtebodavägen 23, Solna, Stockholm 171 65, Sweden
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet Nobels väg 12A, Stockholm SE-171 77, Sweden; Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet Nobels väg 12A, Stockholm SE-171 77, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet Nobels väg 12A, Stockholm SE-171 77, Sweden; Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Jochen M Schwenk
- Science for Life Laboratory, Department of Protein Science School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Tomtebodavägen 23, Solna, Stockholm 171 65, Sweden.
| | - Marike Gabrielson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet Nobels väg 12A, Stockholm SE-171 77, Sweden.
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9
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Ek WE, Karlsson T, Höglund J, Rask-Andersen M, Johansson Å. Causal effects of inflammatory protein biomarkers on inflammatory diseases. SCIENCE ADVANCES 2021; 7:eabl4359. [PMID: 34878845 PMCID: PMC8654293 DOI: 10.1126/sciadv.abl4359] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Many circulating proteins are associated with the presence or severity of disease. However, whether these protein biomarkers are causal for disease development is usually unknown. We investigated the causal effect of 21 well-known or exploratory protein biomarkers of inflammation on 18 inflammatory diseases using two-sample Mendelian randomization. We identified six proteins to have causal effects on any of 11 inflammatory diseases (FDR < 0.05, corresponding to P < 1.4 × 10–3). IL-12B protects against psoriasis and psoriatic arthropathy, LAP-TGF-β-1 protects against osteoarthritis, TWEAK protects against asthma, VEGF-A protects against ulcerative colitis, and LT-α protects against both type 1 diabetes and rheumatoid arthritis. In contrast, IL-18R1 increases the risk of developing allergy, hay fever, and eczema. Most proteins showed protective effects against development of disease rather than increasing disease risk, which indicates that many disease-related biomarkers are expressed to protect from tissue damage. These proteins represent potential intervention points for disease prevention and treatment.
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10
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Kobayashi M, Ferreira MB, Costa RQ, Fonseca T, Oliveira JC, Marinho A, Carvalho HC, Girerd N, Rossignol P, Zannad F, Rodrigues P, Ferreira JP. Circulating Biomarkers and Cardiac Structure and Function in Rheumatoid Arthritis. Front Cardiovasc Med 2021; 8:754784. [PMID: 34869664 PMCID: PMC8636810 DOI: 10.3389/fcvm.2021.754784] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 10/13/2021] [Indexed: 12/13/2022] Open
Abstract
Background: Rheumatoid arthritis (RA) increases the risk for abnormalities of the cardiac structure and function, which may lead to heart failure (HF). Studying the association between circulating biomarkers and echocardiographic parameters is important to screen patients with RA with a higher risk of cardiac dysfunction. Aim: To study the association between circulating biomarkers and echocardiographic parameters in patients with RA. Methods: Echocardiography was performed in 355 patients with RA from RA Porto cohort and the associations between echocardiographic characteristics and 94 circulating biomarkers were assessed. These associations were also assessed in the Metabolic Road to Diastolic Heart Failure (MEDIA-DHF) [392 patients with HF with preserved ejection fraction (HFpEF)] and the Suivi Temporaire Annuel Non-Invasif de la Santé des Lorrains Assurés Sociaux (STANISLAS) (1,672 healthy population) cohorts. Results: In the RA Porto cohort, mean age was 58 ± 13 years, 23% were males and mean RA duration was 12 ± 10 years. After adjustment and multiple testing correction, left ventricular mass index (LVMi), left atrial volume index (LAVi), and E/e′ were independently associated with biomarkers reflecting inflammation [i.e., bone morphogenetic protein 9 (BMP9), pentraxin-related protein 3 (PTX3), tumor necrosis factor receptor superfamily member 11a (TNFRSF11A)], extracellular matrix remodeling [i.e., placental growth factor (PGF)], congestion [i.e., N-terminal pro-brain natriuretic peptide (NT-proBNP), adrenomedullin (ADM)], and myocardial injury (e.g., troponin). Greater LVMi [hazard ratio (HR) (95% CI) per 1 g/m2 = 1.03 (1.02–1.04), p < 0.001], LAVi [HR (95% CI) per 1 ml/m2 = 1.03 (1.01–1.06), p < 0.001], and E/e′ [HR (95% CI) per 1 = 1.08 (1.04–1.13), p < 0.001] were associated with higher rates of cardiovascular events. These associations were externally replicated in patients with HFpEF and asymptomatic individuals. Conclusion: Circulating biomarkers reflecting inflammation, extracellular matrix remodeling, congestion, and myocardial injury were associated with underlying alterations of cardiac structure and function. Biomarkers might be used for the screening of cardiac alterations in patients with RA.
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Affiliation(s)
- Masatake Kobayashi
- Université de Lorraine, INSERM, Centre d'Investigations Cliniques Plurithématique 1433, INSERM U1116, CHRU de Nancy and F-CRIN INI-CRCT, Nancy, France
| | - Maria Betânia Ferreira
- Unit of Multidisciplinary Research in Biomedicine, Porto, Portugal.,Instituto de Ciências Biomédicas Abel Salazar, School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal.,Hospital da Luz Arrábida, Porto, Portugal
| | - Rita Quelhas Costa
- Internal Medicine Department, Centro Hospitalar de Entre o Douro e Vouga, Aveiro, Portugal
| | - Tomás Fonseca
- Internal Medicine Department, Centro Hospitalar Universitário Do Porto, Porto, Portugal
| | - José Carlos Oliveira
- Clinical Chemistry Service, Centro Hospitalar Universitário Do Porto, Porto, Portugal
| | - António Marinho
- Instituto de Ciências Biomédicas Abel Salazar, School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal.,Internal Medicine Department, Centro Hospitalar Universitário Do Porto, Porto, Portugal
| | - Henrique Cyrne Carvalho
- Unit of Multidisciplinary Research in Biomedicine, Porto, Portugal.,Instituto de Ciências Biomédicas Abel Salazar, School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal.,Cardiology Department, Centro Hospitalar Universitário Do Porto, Porto, Portugal
| | - Nicolas Girerd
- Université de Lorraine, INSERM, Centre d'Investigations Cliniques Plurithématique 1433, INSERM U1116, CHRU de Nancy and F-CRIN INI-CRCT, Nancy, France
| | - Patrick Rossignol
- Université de Lorraine, INSERM, Centre d'Investigations Cliniques Plurithématique 1433, INSERM U1116, CHRU de Nancy and F-CRIN INI-CRCT, Nancy, France
| | - Faiez Zannad
- Université de Lorraine, INSERM, Centre d'Investigations Cliniques Plurithématique 1433, INSERM U1116, CHRU de Nancy and F-CRIN INI-CRCT, Nancy, France
| | - Patrícia Rodrigues
- Unit of Multidisciplinary Research in Biomedicine, Porto, Portugal.,Instituto de Ciências Biomédicas Abel Salazar, School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal.,Cardiology Department, Centro Hospitalar Universitário Do Porto, Porto, Portugal
| | - João Pedro Ferreira
- Université de Lorraine, INSERM, Centre d'Investigations Cliniques Plurithématique 1433, INSERM U1116, CHRU de Nancy and F-CRIN INI-CRCT, Nancy, France.,Department of Surgery and Physiology, Cardiovascular Research and Development Center, Faculty of Medicine of the University of Porto, Porto, Portugal
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11
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Höglund J, Karlsson T, Johansson T, Ek WE, Johansson Å. Characterization of the human ABO genotypes and their association to common inflammatory and cardiovascular diseases in the UK Biobank. Am J Hematol 2021; 96:1350-1362. [PMID: 34329492 DOI: 10.1002/ajh.26307] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/14/2021] [Accepted: 07/27/2021] [Indexed: 12/25/2022]
Abstract
The ABO gene contains three major alleles that encodes different antigens; A, B, and O, which determine an individual's blood group. Previous studies have primarily focused on identifying associations between ABO blood groups and diseases risk. Here, we sought to test for association between ABO genotypes (OO, OA, AA; OB, BB, and AB) and a large set of common inflammatory and cardiovascular diseases in UK Biobank as well as disease-related protein biomarkers in NSPHS. We first tested for association by conducting a likelihood ratio test, testing whether ABO contributed significantly to the risk for 24 diseases, and 438 plasma proteins. For phenotypes with FDR < 0.05, we tested for pair-wise differences between genetically determined ABO genotypes using logistic or linear regression. Our study confirmed previous findings of a strong association between ABO and cardiovascular disease, identified associations for both type 1 and type 2 diabetes, and provide additional evidence of significant differences between heterozygous and homozygous allele carriers for pulmonary embolism, deep vein thrombosis, but also for von Willebrand factor levels. Furthermore, the results indicated an additive effect between genotypes, even between the two most common A subgroups, A1 and A2. Additionally, we found that ABO contributed significantly to 39 plasma proteins, of which 23 have never been linked to the ABO locus before. These results show the need of incorporating ABO genotype information in the consultation and management of patients at risk, rather than classifying patients into blood groups.
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Affiliation(s)
- Julia Höglund
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory Uppsala University Uppsala Sweden
| | - Torgny Karlsson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory Uppsala University Uppsala Sweden
| | - Therese Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory Uppsala University Uppsala Sweden
- Centre for Women's Mental Health during the Reproductive Lifespan–WoMHeR Uppsala University Uppsala Sweden
| | - Weronica E. Ek
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory Uppsala University Uppsala Sweden
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory Uppsala University Uppsala Sweden
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12
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Kobayashi M, Huttin O, Magnusson M, Ferreira JP, Bozec E, Huby AC, Preud'homme G, Duarte K, Lamiral Z, Dalleau K, Bresso E, Smaïl-Tabbone M, Devignes MD, Nilsson PM, Leosdottir M, Boivin JM, Zannad F, Rossignol P, Girerd N. Machine Learning-Derived Echocardiographic Phenotypes Predict Heart Failure Incidence in Asymptomatic Individuals. JACC Cardiovasc Imaging 2021; 15:193-208. [PMID: 34538625 DOI: 10.1016/j.jcmg.2021.07.004] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 07/01/2021] [Accepted: 07/01/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVES This study sought to identify homogenous echocardiographic phenotypes in community-based cohorts and assess their association with outcomes. BACKGROUND Asymptomatic cardiac dysfunction leads to a high risk of long-term cardiovascular morbidity and mortality; however, better echocardiographic classification of asymptomatic individuals remains a challenge. METHODS Echocardiographic phenotypes were identified using K-means clustering in the first generation of the STANISLAS (Yearly non-invasive follow-up of Health status of Lorraine insured inhabitants) cohort (N = 827; mean age: 60 ± 5 years; men: 48%), and their associations with vascular function and circulating biomarkers were also assessed. These phenotypes were externally validated in the Malmö Preventive Project cohort (N = 1,394; mean age: 67 ± 6 years; men: 70%), and their associations with the composite of cardiovascular mortality (CVM) or heart failure hospitalization (HFH) were assessed as well. RESULTS Three echocardiographic phenotypes were identified as "mostly normal (MN)" (n = 334), "diastolic changes (D)" (n = 323), and "diastolic changes with structural remodeling (D/S)" (n = 170). The D and D/S phenotypes had similar ages, body mass indices, cardiovascular risk factors, vascular impairments, and diastolic function changes. The D phenotype consisted mainly of women and featured increased levels of inflammatory biomarkers, whereas the D/S phenotype, consisted predominantly of men, displayed the highest values of left ventricular mass, volume, and remodeling biomarkers. The phenotypes were predicted based on a simple algorithm including e', left ventricular mass and volume (e'VM algorithm). In the Malmö cohort, subgroups derived from e'VM algorithm were significantly associated with a higher risk of CVM and HFH (adjusted HR in the D phenotype = 1.87; 95% CI: 1.04 to 3.37; adjusted HR in the D/S phenotype = 3.02; 95% CI: 1.71 to 5.34). CONCLUSIONS Among asymptomatic, middle-aged individuals, echocardiographic data-driven classification based on the simple e'VM algorithm identified profiles with different long-term HF risk. (4th Visit at 17 Years of Cohort STANISLAS-Stanislas Ancillary Study ESCIF [STANISLASV4]; NCT01391442).
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Affiliation(s)
- Masatake Kobayashi
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Olivier Huttin
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Martin Magnusson
- Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Cardiology, Skåne University Hospital, Malmö, Sweden; Wallenberg Centre for Molecular Medicine, Lund University, Sweden
| | - João Pedro Ferreira
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Erwan Bozec
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Anne-Cecile Huby
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Gregoire Preud'homme
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Kevin Duarte
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Zohra Lamiral
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Kevin Dalleau
- Laboratoire lorrain de Recherche en Informatique et ses Applications, Unité Mixte de Recherche 7503, Université de Lorraine, Vandoeuvre-lès-Nancy, France
| | - Emmanuel Bresso
- Laboratoire lorrain de Recherche en Informatique et ses Applications, Unité Mixte de Recherche 7503, Université de Lorraine, Vandoeuvre-lès-Nancy, France
| | - Malika Smaïl-Tabbone
- French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France; Laboratoire lorrain de Recherche en Informatique et ses Applications, Unité Mixte de Recherche 7503, Université de Lorraine, Vandoeuvre-lès-Nancy, France
| | - Marie-Dominique Devignes
- French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France; Laboratoire lorrain de Recherche en Informatique et ses Applications, Unité Mixte de Recherche 7503, Université de Lorraine, Vandoeuvre-lès-Nancy, France
| | - Peter M Nilsson
- Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Internal Medicine, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Margret Leosdottir
- Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Cardiology, Skåne University Hospital, Malmö, Sweden
| | - Jean-Marc Boivin
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Faiez Zannad
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Patrick Rossignol
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France
| | - Nicolas Girerd
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine, Institut national de la santé et de la recherche médicale 1116, Centre Hospitalier Universitaire Régional de Nancy, France; French Clinical Research Infrastructure Network "Investigation" Network Initiative - Cardiovascular and Renal Clinical Trialists" Cardiovascular and Renal Clinical Trialists Network, France.
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13
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Dieden A, Malan L, Mels CM, Lammertyn L, Wentzel A, Nilsson PM, Gudmundsson P, Jujic A, Magnusson M. Exploring biomarkers associated with deteriorating vascular health using a targeted proteomics chip: The SABPA study. Medicine (Baltimore) 2021; 100:e25936. [PMID: 34011069 PMCID: PMC8137024 DOI: 10.1097/md.0000000000025936] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 04/16/2021] [Indexed: 01/05/2023] Open
Abstract
In this observational study, by the use of a multiplex proteomic platform, we aimed to explore associations between 92 targeted proteins involved in cardiovascular disease and/or inflammation, and phenotypes of deteriorating vascular health, with regards to ethnicity.Proteomic profiling (92 proteins) was carried out in 362 participants from the Sympathetic activity and Ambulatory Blood Pressure in Africans (SABPA) study of black and white African school teachers (mean age 44.7 ± 9.9 years, 51.9% women, 44.5% Black Africans, 9.9% with known cardiovascular disease). Three proteins with <15% of samples below detectable limits were excluded from analyses. Associations between multiple proteins and prevalence of hypertension as well as vascular health [Carotid intima-media thickness (cIMT) and pulse wave velocity (PWV)] measures were explored using Bonferroni-corrected regression models.Bonferroni-corrected significant associations between 89 proteins and vascular health markers were further adjusted for clinically relevant co-variates. Hypertension was associated with growth differentiation factor 15 (GDF-15) and C-X-C motif chemokine 16 (CXCL16). cIMT was associated with carboxypeptidase A1 (CPA1), C-C motif chemokine 15 (CCL15), chitinase-3-like protein 1 (CHI3L1), scavenger receptor cysteine-rich type 1 protein M130 (CD163) and osteoprotegerin, whereas PWV was associated with GDF15, E-selectin, CPA1, fatty acid-binding protein 4 (FABP4), CXCL16, carboxypeptidase B (CPB1), and tissue-type plasminogen activator. Upon entering ethnicity into the models, the associations between PWV and CPA1, CPB1, GDF-15, FABP4, CXCL16, and between cIMT and CCL-15, remained significant.Using a multiplex proteomic approach, we linked phenotypes of vascular health with several proteins. Novel associations were found between hypertension, PWV or cIMT and proteins linked to inflammatory response, chemotaxis, coagulation or proteolysis. Further, we could reveal whether the associations were ethnicity-dependent or not.
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Affiliation(s)
- Anna Dieden
- Department of Biomedical Science, Malmö University
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Biofilms- Research Centre for Biointerfaces, Malmö University, Sweden
| | | | - Catharina M.C. Mels
- Hypertension in Africa Research Team (HART)
- MRC Research Unit for Hypertension and Cardiovascular Disease, North-West University, Potchefstroom, South Africa
| | - Leandi Lammertyn
- Hypertension in Africa Research Team (HART)
- MRC Research Unit for Hypertension and Cardiovascular Disease, North-West University, Potchefstroom, South Africa
| | | | | | - Petri Gudmundsson
- Department of Biomedical Science, Malmö University
- Biofilms- Research Centre for Biointerfaces, Malmö University, Sweden
| | - Amra Jujic
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Cardiology, Skåne University Hospital, Malmö
| | - Martin Magnusson
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Hypertension in Africa Research Team (HART)
- Department of Cardiology, Skåne University Hospital, Malmö
- Wallenberg Center for Molecular Medicine, Lund University, Sweden
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14
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Broberg K, Svensson J, Grahn K, Assarsson E, Åberg M, Selander J, Enroth S. Evaluation of 92 cardiovascular proteins in dried blood spots collected under field-conditions: Off-the-shelf affinity-based multiplexed assays work well, allowing for simplified sample collection. Bioessays 2021; 43:e2000299. [PMID: 33586222 DOI: 10.1002/bies.202000299] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 01/10/2021] [Accepted: 01/20/2021] [Indexed: 11/11/2022]
Abstract
Workplace-collected blood spots deposited on filter paper were analysed with multiplexed affinity-based protein assays and found to be suitable for proteomics analysis. The protein extension assay (PEA) was used to characterize 92 proteins using 1.2 mm punches in repeated samples collected from 20 workers. Overall, 97.8% of the samples and 91.3% of the analysed proteins passed quality control. Both within and between spot correlations using six replicates from the same individual were above 0.99, suggesting that comparable levels are obtained from multiple punches from the same spot and from consecutive spots. Protein levels from dried blood and wet serum from the same individuals were compared and the majority of the analysed proteins were found to be significantly correlated. These results open up for simplified sample collection of blood in field conditions for proteomic analysis, but also highlight that not all proteins can be robustly measured from dried whole blood.
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Affiliation(s)
- Karin Broberg
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Johanna Svensson
- Department of Medical Sciences, Clinical Chemistry, Science for Life Laboratory (SciLifeLab) Uppsala, Uppsala University, Uppsala, Sweden
| | - Karin Grahn
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Eva Assarsson
- Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden
| | - Mikael Åberg
- Department of Medical Sciences, Clinical Chemistry, Science for Life Laboratory (SciLifeLab) Uppsala, Uppsala University, Uppsala, Sweden
| | - Jenny Selander
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Uppsala University, Uppsala, Sweden
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15
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Lamb JR, Jennings LL, Gudmundsdottir V, Gudnason V, Emilsson V. It's in Our Blood: A Glimpse of Personalized Medicine. Trends Mol Med 2021; 27:20-30. [PMID: 32988739 PMCID: PMC11082297 DOI: 10.1016/j.molmed.2020.09.003] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 08/05/2020] [Accepted: 09/02/2020] [Indexed: 01/24/2023]
Abstract
Recent advances in protein profiling technology has facilitated simultaneous measurement of thousands of proteins in large population studies, exposing the depth and complexity of the plasma and serum proteomes. This revealed that proteins in circulation were organized into regulatory modules under genetic control and closely associated with current and future common diseases. Unlike networks in solid tissues, serum protein networks comprise members synthesized across different tissues of the body. Genetic analysis reveals that this cross-tissue regulation of the serum proteome participates in systemic homeostasis and mirrors the global disease state of individuals. Here, we discuss how application of this information in routine clinical evaluations may transform the future practice of medicine.
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Affiliation(s)
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, Cambridge, MA 02139, USA
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, IS-201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Vilmundur Gudnason
- Icelandic Heart Association, IS-201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Valur Emilsson
- Icelandic Heart Association, IS-201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland.
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16
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Whole-genome sequencing analysis of the cardiometabolic proteome. Nat Commun 2020; 11:6336. [PMID: 33303764 PMCID: PMC7729872 DOI: 10.1038/s41467-020-20079-2] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 10/26/2020] [Indexed: 12/14/2022] Open
Abstract
The human proteome is a crucial intermediate between complex diseases and their genetic and environmental components, and an important source of drug development targets and biomarkers. Here, we comprehensively assess the genetic architecture of 257 circulating protein biomarkers of cardiometabolic relevance through high-depth (22.5×) whole-genome sequencing (WGS) in 1328 individuals. We discover 131 independent sequence variant associations (P < 7.45 × 10−11) across the allele frequency spectrum, all of which replicate in an independent cohort (n = 1605, 18.4x WGS). We identify for the first time replicating evidence for rare-variant cis-acting protein quantitative trait loci for five genes, involving both coding and noncoding variation. We construct and validate polygenic scores that explain up to 45% of protein level variation. We find causal links between protein levels and disease risk, identifying high-value biomarkers and drug development targets. The human proteome represents a crucial link between complex disease and genetic/environmental factors. Here, the authors investigate 257 cardiometabolic-relevant protein biomarkers in whole genome sequencing data from 1328 individuals, revealing the genetic architecture underlying biomarker variation.
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17
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Gyllensten U, Bosdotter Enroth S, Stålberg K, Sundfeldt K, Enroth S. Preoperative Fasting and General Anaesthesia Alter the Plasma Proteome. Cancers (Basel) 2020; 12:cancers12092439. [PMID: 32867270 PMCID: PMC7564209 DOI: 10.3390/cancers12092439] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 08/22/2020] [Accepted: 08/26/2020] [Indexed: 01/15/2023] Open
Abstract
Background: Blood plasma collected at time of surgery is an excellent source of patient material for investigations into disease aetiology and for the discovery of novel biomarkers. Previous studies on limited sets of proteins and patients have indicated that pre-operative fasting and anaesthesia can affect protein levels, but this has not been investigated on a larger scale. These effects could produce erroneous results in case-control studies if samples are not carefully matched. Methods: The proximity extension assay (PEA) was used to characterize 983 unique proteins in a total of 327 patients diagnosed with ovarian cancer and 50 age-matched healthy women. The samples were collected either at time of initial diagnosis or before surgery under general anaesthesia. Results: 421 of the investigated proteins (42.8%) showed statistically significant differences in plasma abundance levels comparing samples collected at time of diagnosis or just before surgery under anaesthesia. Conclusions: The abundance levels of the plasma proteome in samples collected before incision, i.e., after short-time fasting and under general anaesthesia differs greatly from levels in samples from awake patients. This emphasizes the need for careful matching of the pre-analytical conditions of samples collected from controls to cases at time of surgery in the discovery as well as clinical use of protein biomarkers.
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Affiliation(s)
- Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-751 08 Uppsala, Sweden;
| | | | - Karin Stålberg
- Department of Women’s and Children’s Health, Uppsala University, SE-751 85 Uppsala, Sweden;
| | - Karin Sundfeldt
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-416 85 Gothenburg, Sweden;
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-751 08 Uppsala, Sweden;
- Correspondence: ; Tel.: +46-18-4714913
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18
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Hillary RF, Trejo-Banos D, Kousathanas A, McCartney DL, Harris SE, Stevenson AJ, Patxot M, Ojavee SE, Zhang Q, Liewald DC, Ritchie CW, Evans KL, Tucker-Drob EM, Wray NR, McRae AF, Visscher PM, Deary IJ, Robinson MR, Marioni RE. Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults. Genome Med 2020; 12:60. [PMID: 32641083 PMCID: PMC7346642 DOI: 10.1186/s13073-020-00754-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 06/10/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets. METHODS In this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches). RESULTS We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified 3 CpG sites spread across 3 proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to 1 polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease and between IL12B and Crohn's disease. CONCLUSIONS Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel Trejo-Banos
- Department of Computational Biology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Athanasios Kousathanas
- Department of Computational Biology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Sarah E Harris
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Marion Patxot
- Department of Computational Biology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Sven Erik Ojavee
- Department of Computational Biology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Qian Zhang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - David C Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Elliot M Tucker-Drob
- Department of Psychology, The University of Texas at Austin, Austin, TX, 78712, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, 78712, USA
| | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Matthew R Robinson
- Institute of Science and Technology Austria, 3400, Klosterneuburg, Austria.
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
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19
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Jentsch MC, Burger H, Meddens MBM, Beijers L, van den Heuvel ER, Meddens MJM, Schoevers RA. Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics. Int J Mol Sci 2020; 21:ijms21093039. [PMID: 32344909 PMCID: PMC7246841 DOI: 10.3390/ijms21093039] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 04/21/2020] [Accepted: 04/22/2020] [Indexed: 12/27/2022] Open
Abstract
The identification of biomarkers associated with major depressive disorder (MDD) holds great promise to develop an objective laboratory test. However, current biomarkers lack discriminative power due to the complex biological background, and not much is known about the influence of potential modifiers such as gender. We first performed a cross-sectional study on the discriminative power of biomarkers for MDD by investigating gender differences in biomarker levels. Out of 28 biomarkers, 21 biomarkers were significantly different between genders. Second, a novel statistical approach was applied to investigate the effect of gender on MDD disease classification using a panel of biomarkers. Eleven biomarkers were identified in men and eight in women, three of which were active in both genders. Gender stratification caused a (non-significant) increase of Area Under Curve (AUC) for men (AUC = 0.806) and women (AUC = 0.807) compared to non-stratification (AUC = 0.739). In conclusion, we have shown that there are differences in biomarker levels between men and women which may impact accurate disease classification of MDD when gender is not taken into account.
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Affiliation(s)
- Mike C. Jentsch
- Brainscan BV, 7418 AH Deventer, The Netherlands
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
- Correspondence: (M.C.J.); (R.A.S.); Tel.: +31-62-874-6151 (M.C.J); Tel.: +31-50-361-2065 (R.A.S.)
| | - Huibert Burger
- Department of General Practice, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | | | - Lian Beijers
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Edwin R. van den Heuvel
- Department of Mathematics and Computer Science, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
| | | | - Robert A. Schoevers
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
- Research School of Behavioral and Cognitive Neurosciences, University of Groningen, 9713 AV Groningen, The Netherlands
- Correspondence: (M.C.J.); (R.A.S.); Tel.: +31-62-874-6151 (M.C.J); Tel.: +31-50-361-2065 (R.A.S.)
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20
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Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers. Sci Rep 2019; 9:16844. [PMID: 31727947 PMCID: PMC6856527 DOI: 10.1038/s41598-019-53111-7] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 10/26/2019] [Indexed: 02/07/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified associations between thousands of common genetic variants and human traits. However, common variants usually explain a limited fraction of the heritability of a trait. A powerful resource for identifying trait-associated variants is whole genome sequencing (WGS) data in cohorts comprised of families or individuals from a limited geographical area. To evaluate the power of WGS compared to imputations, we performed GWAS on WGS data for 72 inflammatory biomarkers, in a kinship-structured cohort. When using WGS data, we identified 18 novel associations that were not detected when analyzing the same biomarkers with genotyped or imputed SNPs. Five of the novel top variants were low frequency variants with a minor allele frequency (MAF) of <5%. Our results suggest that, even when applying a GWAS approach, we gain power and precision using WGS data, presumably due to more accurate determination of genotypes. The lack of a comparable dataset for replication of our results is a limitation in our study. However, this further highlights that there is a need for more genetic epidemiological studies based on WGS data.
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21
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Berggrund M, Enroth S, Lundberg M, Assarsson E, Stålberg K, Lindquist D, Hallmans G, Grankvist K, Olovsson M, Gyllensten U. Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay. Mol Cell Proteomics 2019; 18:735-743. [PMID: 30692274 PMCID: PMC6442356 DOI: 10.1074/mcp.ra118.001208] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 01/24/2019] [Indexed: 12/16/2022] Open
Abstract
Human papillomavirus (HPV) is recommended as the primary test in cervical cancer screening, with co-testing by cytology for HPV-positive women to identify cervical lesions. Cytology has low sensitivity and there is a need to identify biomarkers that could identify dysplasia that are likely to progress to cancer. We searched for plasma proteins that could identify women with cervical cancer using the multiplex proximity extension assay (PEA). The abundance of 100 proteins were measured in plasma collected at the time of diagnosis of patients with invasive cervical cancer and in population controls using the Olink Multiplex panels CVD II, INF I, and ONC II. Eighty proteins showed increased levels in cases compared with controls. We identified a signature of 11 proteins (PTX3, ITGB1BP2, AXIN1, STAMPB, SRC, SIRT2, 4E-BP1, PAPPA, HB-EGF, NEMO and IL27) that distinguished cases and controls with a sensitivity of 0.96 at a specificity of 1.0. This signature was evaluated in a prospective replication cohort with samples collected before, at or after diagnosis and achieved a sensitivity of 0.78 and a specificity 0.56 separating samples collected at the time of diagnosis of invasive cancer from samples collected prior to diagnosis. No difference in abundance was seen between samples collected prior to diagnosis or after treatment as compared with population controls, indicating that this protein signature is mainly informative close to time of diagnosis. Further studies are needed to determine the optimal window in time prior to diagnosis for these biomarker candidates.
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Affiliation(s)
- Malin Berggrund
- From the ‡Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-75108 Uppsala, Sweden
| | - Stefan Enroth
- From the ‡Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-75108 Uppsala, Sweden
| | - Martin Lundberg
- §OLINK Proteomics, Uppsala Science Park, SE-751 83, Uppsala, Sweden
| | - Erika Assarsson
- §OLINK Proteomics, Uppsala Science Park, SE-751 83, Uppsala, Sweden
| | - Karin Stålberg
- Department of Women's and Children's Health, 751 85, Uppsala University, Uppsala, Sweden
| | - David Lindquist
- Department of Radiation Sciences, Umeå University, SE-90187 Umeå, Sweden
| | - Göran Hallmans
- Department of Public Health and Clinical Medicine, Nutritional Research, Umeå University, SE-90187 Umeå, Sweden
| | - Kjell Grankvist
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, SE-90185 Umeå, Sweden
| | - Matts Olovsson
- Department of Women's and Children's Health, 751 85, Uppsala University, Uppsala, Sweden
| | - Ulf Gyllensten
- From the ‡Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-75108 Uppsala, Sweden;.
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22
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Molvin J, Pareek M, Jujic A, Melander O, Råstam L, Lindblad U, Daka B, Leósdóttir M, Nilsson PM, Olsen MH, Magnusson M. Using a Targeted Proteomics Chip to Explore Pathophysiological Pathways for Incident Diabetes- The Malmö Preventive Project. Sci Rep 2019; 9:272. [PMID: 30670722 PMCID: PMC6342982 DOI: 10.1038/s41598-018-36512-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 11/21/2018] [Indexed: 12/19/2022] Open
Abstract
Multiplex proteomic platforms provide excellent tools for investigating associations between multiple proteins and disease (e.g., diabetes) with possible prognostic, diagnostic, and therapeutic implications. In this study our aim was to explore novel pathophysiological pathways by examining 92 proteins and their association with incident diabetes in a population-based cohort (146 cases of diabetes versus 880 controls) followed over 8 years. After adjusting for traditional risk factors, we identified seven proteins associated with incident diabetes. Four proteins (Scavenger receptor cysteine rich type 1 protein M130, Fatty acid binding protein 4, Plasminogen activator inhibitor 1 and Insulin-like growth factor-binding protein 2) with a previously established association with incident diabetes and 3 proteins (Cathepsin D, Galectin-4, Paraoxonase type 3) with a novel association with incident diabetes. Galectin-4, with an increased risk of diabetes, and Paraoxonase type 3, with a decreased risk of diabetes, remained significantly associated with incident diabetes after adjusting for plasma glucose, implying a glucose independent association with diabetes.
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Affiliation(s)
- John Molvin
- Department of Clinical Sciences, Lund University, Clinical Research Center, Malmö, Sweden. .,Department of Cardiology, Skåne University Hospital Malmö, Malmö, Sweden.
| | - Manan Pareek
- Cardiology Section, Department of Internal Medicine, Holbæk Hospital, Holbæk, Denmark.,Brigham and Women's Hospital Heart & Vascular Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Amra Jujic
- Department of Clinical Sciences, Lund University, Clinical Research Center, Malmö, Sweden
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Clinical Research Center, Malmö, Sweden.,Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Lennart Råstam
- Department of Clinical Sciences, Lund University, Clinical Research Center, Malmö, Sweden
| | - Ulf Lindblad
- Institute of Medicine, Department of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Bledar Daka
- Institute of Medicine, Department of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Margrét Leósdóttir
- Department of Clinical Sciences, Lund University, Clinical Research Center, Malmö, Sweden.,Department of Cardiology, Skåne University Hospital Malmö, Malmö, Sweden
| | - Peter M Nilsson
- Department of Clinical Sciences, Lund University, Clinical Research Center, Malmö, Sweden.,Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Michael H Olsen
- Cardiology Section, Department of Internal Medicine, Holbæk Hospital, Holbæk, Denmark.,Centre for Individualized Medicine in Arterial Diseases (CIMA), Odense University Hospital, University of Southern Denmark, Odense, Denmark
| | - Martin Magnusson
- Department of Clinical Sciences, Lund University, Clinical Research Center, Malmö, Sweden.,Department of Cardiology, Skåne University Hospital Malmö, Malmö, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
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