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Giedraitis, VilmantasORCID iD iconorcid.org/0000-0003-3423-2021
Alternative names
Publications (10 of 44) Show all publications
Stenemo, M., Nowak, C., Byberg, L., Sundström, J., Giedraitis, V., Lind, L., . . . Ärnlöv, J. (2018). Circulating proteins as predictors of incident heart failure in the elderly. European Journal of Heart Failure, 20(1), 55-62
Open this publication in new window or tab >>Circulating proteins as predictors of incident heart failure in the elderly
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2018 (English)In: European Journal of Heart Failure, ISSN 1388-9842, E-ISSN 1879-0844, Vol. 20, no 1, p. 55-62Article in journal (Refereed) Published
Abstract [en]

Aims

To identify novel risk markers for incident heart failure using proteomic profiling of 80 proteins previously associated with cardiovascular pathology.

Methods and results

Proteomic profiling (proximity extension assay) was performed in two community‐based prospective cohorts of elderly individuals without heart failure at baseline: the Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS, n = 901, median age 70.2 (interquartile range 70.0–70.3) years, 80 events]; and the Uppsala Longitudinal Study of Adult Men [ULSAM, n = 685, median age 77.8 (interquartile range 76.9–78.1) years, 90 events]. Twenty‐nine proteins were associated with incident heart failure in the discovery cohort PIVUS after adjustment for age and sex, and correction for multiple testing. Eighteen associations replicated in ULSAM. In pooled analysis of both cohorts, higher levels of nine proteins were associated with incident heart failure after adjustment for established risk factors: growth differentiation factor 15 (GDF‐15), T‐cell immunoglobulin and mucin domain 1 (TIM‐1), tumour necrosis factor‐related apoptosis‐inducing ligand receptor 2 (TRAIL‐R2), spondin‐1 (SPON1), matrix metalloproteinase‐12 (MMP‐12), follistatin (FS), urokinase‐type plasminogen activator surface receptor (U‐PAR), osteoprotegerin (OPG), and suppression of tumorigenicity 2 (ST2). Of these, GDF‐15, U‐PAR, MMP‐12, TRAIL‐R2, SPON1 and FS were associated with worsened echocardiographic left ventricular systolic function at baseline, while only TIM‐1 was positively associated with worsened diastolic function (P < 0.02 for all).

Conclusion

Proteomic profiling identified several novel associations between proteins involved in apoptosis, inflammation, matrix remodelling, and fibrinolysis with incident heart failure in elderly individuals. Our results encourage additional studies investigating the underlying mechanisms and the clinical utility of our findings.

Keywords
Biomarkers, Epidemiology, Heart failure, Left ventricular dysfunction, Proteomics, Risk prediction
National Category
Cardiac and Cardiovascular Systems
Identifiers
urn:nbn:se:uu:diva-334416 (URN)10.1002/ejhf.980 (DOI)000423809700007 ()28967680 (PubMedID)
Funder
EU, Horizon 2020, 634869Swedish Research Council, 2012-2215; 2015-03477; 221-2013-1673Marianne and Marcus Wallenberg Foundation, 2012.0082Swedish Heart Lung Foundation, 20140422; 20150429; 20120169Knut and Alice Wallenberg Foundation, 2013.0126Göran Gustafsson Foundation for promotion of scientific research at Uppala University and Royal Institute of Technology, 1637
Note

Tove Fall och Johan Ärnlöv delar på sistaförfattarskapet.

Available from: 2017-11-23 Created: 2017-11-23 Last updated: 2018-08-24Bibliographically approved
Evangelou, E., Warren, H. R., Mosen-Ansorena, D., Mifsud, B., Pazoki, R., Gao, H., . . . Caulfield, M. J. (2018). Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.. Nature Genetics, 50(10), 1412-1425
Open this publication in new window or tab >>Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.
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2018 (English)In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 50, no 10, p. 1412-1425Article in journal (Refereed) Published
Abstract [en]

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

National Category
Medical Genetics
Identifiers
urn:nbn:se:uu:diva-367084 (URN)10.1038/s41588-018-0205-x (DOI)000446047000013 ()30224653 (PubMedID)
Funder
EU, European Research CouncilNovo Nordisk, NNF15CC0018486EU, FP7, Seventh Framework Programme, HEALTH-F2-2013-601456Wellcome trust, RE/13/1/30181Wellcome trust, WT098051
Available from: 2018-11-28 Created: 2018-11-28 Last updated: 2018-12-05Bibliographically approved
Nowak, C., Hetty, S., Salihovic, S., Castillejo-Lopez, C., Ganna, A., Cook, N. L., . . . Ingelsson, E. (2018). Glucose challenge metabolomics implicates medium-chain acylcarnitines in insulin resistance. Scientific Reports, 8, Article ID 8691.
Open this publication in new window or tab >>Glucose challenge metabolomics implicates medium-chain acylcarnitines in insulin resistance
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2018 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 8, article id 8691Article in journal (Refereed) Published
Abstract [en]

Insulin resistance (IR) predisposes to type 2 diabetes and cardiovascular disease but its causes are incompletely understood. Metabolic challenges like the oral glucose tolerance test (OGTT) can reveal pathogenic mechanisms. We aimed to discover associations of IR with metabolite trajectories during OGTT. In 470 non-diabetic men (age 70.6 +/- 0.6 years), plasma samples obtained at 0, 30 and 120 minutes during an OGTT were analyzed by untargeted liquid chromatography-mass spectrometry metabolomics. IR was assessed with the hyperinsulinemic-euglycemic clamp method. We applied age-adjusted linear regression to identify metabolites whose concentration change was related to IR. Nine trajectories, including monounsaturated fatty acids, lysophosphatidylethanolamines and a bile acid, were significantly associated with IR, with the strongest associations observed for medium-chain acylcarnitines C10 and C12, and no associations with L-carnitine or C2-, C8-, C14- or C16-carnitine. Concentrations of C10-and C12-carnitine decreased during OGTT with a blunted decline in participants with worse insulin resistance. Associations persisted after adjustment for obesity, fasting insulin and fasting glucose. In mouse 3T3-L1 adipocytes exposed to different acylcarnitines, we observed blunted insulin-stimulated glucose uptake after treatment with C10-or C12-carnitine. In conclusion, our results identify medium-chain acylcarnitines as possible contributors to IR.

National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:uu:diva-357687 (URN)10.1038/s41598-018-26701-0 (DOI)000434252600004 ()29875472 (PubMedID)
Funder
Knut and Alice Wallenberg Foundation, 2013.0126Swedish Research Council, 2015-03477
Note

Tove Fall and Erik Ingelsson contributed equally to this work.

Available from: 2018-08-23 Created: 2018-08-23 Last updated: 2018-08-23Bibliographically approved
Nowak, C., Carlsson, A. C., Östgren, C. J., Nyström, F. H., Alam, M., Feldreich, T., . . . Ärnlöv, J. (2018). Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes. Diabetologia, 61(8), 1748-1757
Open this publication in new window or tab >>Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes
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2018 (English)In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 61, no 8, p. 1748-1757Article in journal (Refereed) Published
Abstract [en]

Aims/hypothesis Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes. Methods We combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multivariable-adjusted Cox regression was used in a discovery/replication design to identify biomarkers for incident MACE. We used gradient-boosted machine learning and lasso regularised Cox regression in a random 75% training subsample to assess whether adding proteins to risk factors included in the Swedish National Diabetes Register risk model would improve the prediction of MACE in the separate 25% test subsample. Results Of 1211 adults with type 2 diabetes (32% women), 211 experienced a MACE over a mean (+/- SD) of 6.4 +/- 2.3 years. We replicated associations (< 5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit alpha (IL-27a), kidney injury molecule (KIM)-1, fibroblast growth factor (FGF)-23, protein S100-A12, TNF receptor (TNFR)-1, TNFR-2 and TNF-related apoptosis-inducing ligand receptor (TRAIL-R)2. Addition of the 80-protein assay to established risk factors improved discrimination in the separate test sample from 0.686 (95% CI 0.682, 0.689) to 0.748 (95% CI 0.746, 0.751). A sparse model of 20 added proteins achieved a C statistic of 0.747 (95% CI 0.653, 0.842) in the test sample. Conclusions/interpretation We identified eight protein biomarkers, four of which are novel, for risk of MACE in community residents with type 2 diabetes, and found improved risk prediction by combining multiplex proteomics with an established risk model. Multiprotein arrays could be useful in identifying individuals with type 2 diabetes who are at highest risk of a cardiovascular event.

Place, publisher, year, edition, pages
SPRINGER, 2018
Keywords
Biomarkers, Major adverse cardiovascular event, Proteomics, Risk, Type 2 diabetes
National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:uu:diva-361262 (URN)10.1007/s00125-018-4641-z (DOI)000437432200006 ()29796748 (PubMedID)
Funder
EU, Horizon 2020, 634869Swedish Research Council, 2012-2215Swedish Research Council, 2015-03477Swedish Society of MedicineSwedish Heart Lung Foundation
Available from: 2018-10-11 Created: 2018-10-11 Last updated: 2018-10-11Bibliographically approved
Turcot, V., Lu, Y., Highland, H. M., Schurmann, C., Justice, A. E., Fine, R. S., . . . Loos, R. J. F. (2018). Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nature Genetics, 50(1), 26-+
Open this publication in new window or tab >>Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity
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2018 (English)In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 50, no 1, p. 26-+Article in journal (Refereed) Published
Abstract [en]

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

National Category
Genetics
Identifiers
urn:nbn:se:uu:diva-343882 (URN)10.1038/s41588-017-0011-x (DOI)000423157400007 ()29273807 (PubMedID)
Funder
NIH (National Institute of Health), R01DK089256 R01DK101855 K99HL130580 R01DK106621 HL094535 HL109946 R01DK075787 R01HD057194 U01HG007416 1R01HL09257R01HL128914; K24HL105780; R01DK110113; U01HG007417; R01DK107786; K23HL114724EU, European Research Council, SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC; 323195; 293574
Available from: 2018-03-16 Created: 2018-03-16 Last updated: 2018-03-16Bibliographically approved
Mahajan, A., Wessel, J., Willems, S. M., Zhao, W., Robertson, N. R., Chu, A. Y., . . . McCarthy, M. I. (2018). Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nature Genetics, 50(4), 559-571
Open this publication in new window or tab >>Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
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2018 (English)In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 50, no 4, p. 559-571Article in journal (Refereed) Published
Abstract [en]

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 x 10(-7)); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio <= 1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2018
National Category
Medical Genetics
Identifiers
urn:nbn:se:uu:diva-352709 (URN)10.1038/s41588-018-0084-1 (DOI)000429529300016 ()29632382 (PubMedID)
Available from: 2018-06-07 Created: 2018-06-07 Last updated: 2018-06-07Bibliographically approved
Velickaite, V., Giedraitis, V., Ström, K., Alafuzoff, I., Zetterberg, H., Lannfelt, L., . . . Ingelsson, M. (2017). Cognitive function in very old men does not correlate to biomarkers of Alzheimer's disease. BMC Geriatrics, 17(1), Article ID 208.
Open this publication in new window or tab >>Cognitive function in very old men does not correlate to biomarkers of Alzheimer's disease
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2017 (English)In: BMC Geriatrics, ISSN 1471-2318, E-ISSN 1471-2318, Vol. 17, no 1, article id 208Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: The Alzheimer's disease (AD) brain displays atrophy with amyloid-β (Aβ) and tau deposition, whereas decreased Aβ42 and increased tau are measured in cerebrospinal fluid (CSF). The aim of this study was to relate cognitive performance to the degree of brain atrophy, CSF biomarker levels and neuropathology in a cohort of aged men.

METHODS: Fifty-eight 86-92-year-old men from the Uppsala Longitudinal Study of Adult Men (ULSAM) cohort underwent cognitive testing, brain computed tomography and lumbar puncture. Atrophy was graded with established scales. Concentrations of CSF Aβ42, t-tau and p-tau were measured by ELISA. Thirteen brains were examined post mortem.

RESULTS: Forty-six of the individuals were considered non-demented, whereas twelve were diagnosed with dementia, either at baseline (n = 4) or during follow-up (n = 8). When comparing subjects with and without dementia, there were no differences in the degree of atrophy, although the mini mental state examination (MMSE) scoring correlated weakly with the degree of medial temporal atrophy (MTA) (p = 0.04). Moreover, the CSF biomarker levels did not differ significantly between healthy (n = 27) and demented (n = 8) subjects (median values 715 vs 472 pg/ml for Aβ42, 414 vs 427 pg/ml for t-tau and 63 vs 60 pg/ml for p-tau). Similarly, there were no differences in the biomarker levels between individuals with mild (n = 24) and severe (n = 11) MTA (median values 643 vs 715 pg/ml for Aβ42, 441 vs 401 pg/ml for t-tau and 64 vs 53 pg/ml for p-tau). Finally, the neuropathological changes did not correlate with any of the other measures.

CONCLUSION: In this cohort of aged men only a weak correlation could be seen between cognitive performance and MTA, whereas the various neuroradiological, biochemical and neuropathological measures did not correlate with each other. Thus, AD biomarkers seem to be less informative in subjects of an advanced age.

Keywords
AD biomarkers, Advanced age, Brain atrophy, CSF biomarkers, Cognitive performance, Neuropathology
National Category
Neurology Geriatrics Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:uu:diva-329266 (URN)10.1186/s12877-017-0601-6 (DOI)000410449900002 ()28886705 (PubMedID)
Note

V. Velickaite and V. Giedraitis contributed equally.

Available from: 2017-09-11 Created: 2017-09-11 Last updated: 2017-12-06Bibliographically approved
Flannick, J., Fuchsberger, C., Mahajan, A., Teslovich, T. M., Agarwala, V., Gaulton, K. J., . . . McCarthy, M. I. (2017). Data Descriptor: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. Scientific Data, 4, Article ID 170179.
Open this publication in new window or tab >>Data Descriptor: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
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2017 (English)In: Scientific Data, E-ISSN 2052-4463, Vol. 4, article id 170179Article in journal (Refereed) Published
Abstract [en]

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

National Category
Endocrinology and Diabetes Medical Genetics
Identifiers
urn:nbn:se:uu:diva-339776 (URN)10.1038/sdata.2017.179 (DOI)000418568400001 ()29257133 (PubMedID)
Funder
AstraZeneca
Note

Erratum in: Scientific Data, volume 5, Article number: 180002, 2018

Doi:10.1038/sdata.2018.2

Available from: 2018-02-09 Created: 2018-02-09 Last updated: 2018-05-08Bibliographically approved
Nolte, I. M., Munoz, M. L., Tragante, V., Amare, A. T., Jansen, R., Vaez, A., . . . de Geus, E. J. C. (2017). Genetic loci associated with heart rate variability and their effects on cardiac disease risk. Nature Communications, 8, Article ID 15805.
Open this publication in new window or tab >>Genetic loci associated with heart rate variability and their effects on cardiac disease risk
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2017 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 8, article id 15805Article in journal (Refereed) Published
Abstract [en]

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74 < r(g) < -0.55) and blood pressure (-0.35 < r(g) < -0.20). These findings provide clinically relevant biological insight into heritable variation in vagal heart rhythm regulation, with a key role for genetic variants (GNG11, RGS6) that influence G-protein heterotrimer action in GIRK-channel induced pacemaker membrane hyperpolarization.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2017
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-329672 (URN)10.1038/ncomms15805 (DOI)000403216600001 ()28613276 (PubMedID)
Available from: 2017-09-19 Created: 2017-09-19 Last updated: 2018-02-19Bibliographically approved
Warren, H. R., Evangelou, E., Cabrera, C. P., Gao, H., Ren, M., Mifsud, B., . . . Morris, A. P. (2017). Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nature Genetics, 49(3), 403-415
Open this publication in new window or tab >>Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk