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3. Roots of diversity relations

Author

Wurtz, Peter and Annila, Arto

Subjects
Quantitative Biology - Populations and Evolution
Abstract

The species-area relationship is one of the central generalizations in ecology however its origin has remained a puzzle. Since ecosystems are understood as energy transduction systems, the regularities in species richness are considered to result from ubiquitous imperatives in energy transduction. From a thermodynamic point of view, organisms are transduction mechanisms that distribute an influx of energy down along the steepest gradients to the ecosystem's diverse repositories of chemical energy, i.e., populations of species. Transduction machineries, i.e. ecosystems assembled from numerous species, may emerge and evolve toward high efficiency on large areas that hold more matter than small ones. This results in the well-known logistic-like relationship between the area and the number of species. The species-area relationship is understood, in terms of thermodynamics, to be the skewed cumulative curve of chemical energy distribution that is commonly known as the species-abundance relationship., Comment: 10, 3 figures

Published
2009
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5. Association of circulating metabolites with healthy diet and risk of cardiovascular disease: analysis of two cohort studies

Author

Akbaraly, Tasnime, Wurtz, Peter, Singh-Manoux, Archana, Shipley, Martin J., Haapakoski, Rita, Lehto, Maili, Desrumaux, Catherine, Kähönen, Mika, Lehtimäki, Terho, Mikkilä, Vera, Hingorani, Aroon, Humphries, Steve E., Kangas, Antti J., Soininen, Pasi, Raitakari, Olli, Ala-Korpela, Mika, Kivimäki, Mika, Department of Epidemiology and Public Health, Imperial College London, Mécanismes moléculaires dans les démences neurodégénératives (MMDN), Université de Montpellier (UM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de la Santé et de la Recherche Médicale (INSERM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL), University of Oulu, University College of London [London] (UCL), Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Tampere University Hospital, Faculty of Medicine and Life Sciences [Tampere], University of Tampere [Finland], University of Turku, University of Eastern Finland, University of Bristol [Bristol], Baker IDI Heart and Diabetes Institute 75 Commercial Rd, Melbourne, Victoria 3004, AustraliaBaker IDI Heart and Diabetes Institute 75 Commercial Rd, Melbourne, Victoria 3004, Australia, Baker Heart and Diabetes Institute (AUSTRALIA), Monash University [Melbourne], University of Helsinki, Lääketieteen ja biotieteiden tiedekunta - Faculty of Medicine and Life Sciences, University of Tampere, KARLI, Mélanie, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Clinicum, and Department of Public Health

Subjects
Adult, Male, Magnetic Resonance Spectroscopy, lcsh:Medicine, Risk Assessment, Cohort Studies, Biological Factors, Humans, Metabolomics, CORONARY-HEART-DISEASE, NUCLEAR-MAGNETIC-RESONANCE, lcsh:Science, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, lcsh:R, Sisätaudit - Internal medicine, WOMEN, MEN, WHITEHALL II COHORT, Middle Aged, PARTICLE-SIZE, 3142 Public health care science, environmental and occupational health, Cardiovascular Diseases, 3121 General medicine, internal medicine and other clinical medicine, YOUNG FINNS, Metabolome, EATING INDEX, Female, lcsh:Q, FATTY-ACIDS, Diet, Healthy, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

International audience; Diet may modify metabolomic profiles towards higher or lower cardiovascular disease (CVD) risk. We aimed to identify metabolite profiles associated with high adherence to dietary recommendations - the Alternative Healthy Eating Index (AHEI) - and the extent to which metabolites associated with AHEI also predict incident CVD. Relations between AHEI score and 80 circulating lipids and metabolites, quantified by nuclear magnetic resonance metabolomics, were examined using linear regression models in the Whitehall II study (n = 4824, 55.9 ± 6.1 years, 28.0% women) and were replicated in the Cardiovascular Risk in Young Finns Study (n = 1716, 37.7 ± 5.0 years, 56.3% women). We used Cox models to study associations between metabolites and incident CVD over the 15.8-year follow-up in the Whitehall II study. After adjustment for confounders, higher AHEI score (indicating healthier diet) was associated with higher degree of unsaturation of fatty acids (FA) and higher ratios of polyunsaturated FA, omega-3 and docosahexaenoic acid relative to total FA in both Whitehall II and Young Finns studies. A concordance of associations of metabolites with higher AHEI score and lower CVD risk was observed in Whitehall II. Adherence to healthy diet seems to be associated with specific FA that reduce risk of CVD.

Published
2018

6. Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults

Author

Wurtz, Peter, Soininen, Pasi, Kangas, Antti J., Ronnemaa, Tapani, Lehtimaki, Terho, Kahonen, Mika, Viikari, Jorma S., Raitakari, Olli T., and Ala-Korpela, Mika

Subjects
Insulin resistance -- Risk factors -- Diagnosis -- Research, Amino acids -- Physiological aspects -- Measurement -- Research, Biological markers -- Usage -- Research, Health
Abstract

OBJECTIVE--Branched-chain and aromatic amino acids are associated with the risk for future type 2 diabetes; however, the underlying mechanisms remain elusive. We tested whether amino acids predict insulin resistance index [...]

Published
2013
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7. Circulating metabolite predictors of glycemia in middle-aged men and women

Author

Wurtz, Peter, Tiainen, Mika, Makinen, Ville-Petteri, Kangas, Antti J., Soininen, Pasi, Saltevo, Juha, Keinanen-Kiukaanniemi, Sirkka, Mantyselka, Pekka, Lehtimaki, Terho, Laakso, Markku, Jula, Antti, Kahonen, Mira, Vanhala, Mauno, and Ala-Korpela, Mira

Subjects
Dextrose, Metabolites, Amino acids, Glucose, Nuclear magnetic resonance spectroscopy, Type 2 diabetes -- Risk factors -- Development and progression, Health
Abstract

OBJECTIVE--Metabolite predictors of deteriorating glucose tolerance may elucidate the pathogenesis of type 2 diabetes. We investigated associations of circulating metabolites from high-throughput profiling with fasting and postload glycemia cross-sectionally and [...]

Published
2012
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8. Metabolic signatures of insulin resistance in 7,098 young adults

Author

Wurtz, Peter, Makinen, Ville-Petteri, Soininen, Pasi, Kangas, Antti J., Tukiainen, Taru, Kettunen, Johannes, Savolainen, Markku J., Tammelin, Tuija, Viikari, Jorma S., Ronnemaa, Tapani, Kahonen, Mika, Lehtimaki, Terho, Ripatti, Samuli, Raitakari, Olli T., Jarvelin, Marjo-Riitta, and Ala-Korpela, Mika

Subjects
Metabolism -- Research, Insulin resistance -- Development and progression -- Analysis -- Research, Adults -- Health aspects, Health
Abstract

Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gin but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints., Development of type 2 diabetes is commonly preceded by insulin resistance manifested by increased insulin release to maintain glucose homeostasis (1). Already in young adulthood, impaired insulin sensitivity is associated [...]

Published
2012
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9. Investigating the effects of lycopene and green tea on the metabolome of men at risk of prostate cancer:The ProDiet randomised controlled trial

Author

Beynon, Rhona, Richmond, Rebecca, Dos Santos Ferreira, Diana, Ness, Andrew R, May, Margaret, Davey Smith, George, Vincent, Emma, Adams, Charleen, Ala-Korpela, Mika, Wurtz, Peter, Soidinsalo, Sebastian, Metcalfe, Chris, Donovan, Jenny, The Protect Study, Group, The PRACTICAL, Consortium, Lane, J. Athene, and Martin, Richard

Subjects
Centre for Surgical Research, dietary intervention, green tea, ICEP, prostate cancer, Mendelian randomisation, lycopene, BTC (Bristol Trials Centre)
Abstract

Lycopene and green tea consumption have been observationally associated with reduced prostate cancer risk, but the underlying mechanisms have not been fully elucidated. We investigated the effect of factorial randomisation to a 6-month lycopene and green tea dietary advice or supplementation intervention on 159 serum metabolite measures in 128 men with raised PSA levels (but prostate cancer-free), analysed by intention-to-treat. The causal effects of metabolites modified by the intervention on prostate cancer risk were then assessed by Mendelian randomisation, using summary statistics from 44,825 prostate cancer cases and 27,904 controls. The systemic effects of lycopene and green tea supplementation on serum metabolic profile were comparable to the effects of the respective dietary advice interventions (R 2 = 0.65 and 0.76 for lycopene and green tea respectively). Metabolites which were altered in response to lycopene supplementation were acetate [β (standard deviation difference vs. placebo): 0.69; 95% CI = 0.24, 1.15; p = 0.003], valine (β: -0.62; -1.03, -0.02; p = 0.004), pyruvate (β: -0.56; -0.95, -0.16; p = 0.006) and docosahexaenoic acid (β: -0.50; -085, -0.14; p = 0.006). Valine and diacylglycerol were lower in the lycopene dietary advice group (β: -0.65; -1.04, -0.26; p = 0.001 and β: -0.59; -1.01, -0.18; p = 0.006). A genetically instrumented SD increase in pyruvate increased the odds of prostate cancer by 1.29 (1.03, 1.62; p = 0.027). An intervention to increase lycopene intake altered the serum metabolome of men at risk of prostate cancer. Lycopene lowered levels of pyruvate, which our Mendelian randomisation analysis suggests may be causally related to reduced prostate cancer risk.

Published
2019

10. Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study

Author

Adams, Charleen, Richmond, Rebecca C., Santos Ferreira, Diana L, Spiller, Wes, Tan, Vanessa Y, Zheng, Jie, Wurtz, Peter, Donovan, Jenny L, Hamdy, Freddie C, Neal, David E, Lane, J Athene, Davey Smith, George, Relton, Caroline L, Eeles, Rosalind A, Henderson, Brian E, Haiman, Christopher A, Kote-Jarai, Zsofia, Schumacher, Fredrick R, Amin Al Olama, Ali, Benlloch, Sara, Muir, Kenneth, Berndt, Sonja I, Conti, David V, Wiklund, Fredrik, Chanock, Stephen J, Gapstur, Susan M, Stevens, Victoria L, Tangen, Catherine M, Batra, Jyotsna, Clements, Judith A, Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Wolk, Alicja, West, Catharine M L, Mucci, Lorelei A, Cancel-Tassin, Geraldine, Koutros, Stella, Sørensen, Karina D, Maehle, Lovise, Travis, Ruth C, Hamilton, Robert, Ingles, Sue Ann, Rosenstein, Barry S, Lu, Yong-Jie, Giles, Graham G, Kibel, Adam S, Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L, Park, Jong Y, Stanford, Janet L, Cybulski, Cezary, Nordestgaard, Borge G, Brenner, Hermann, Maier, Christiane, Kim, Jeri, John, Esther M, Teixeira, Manuel R, Neuhausen, Susan L, DeRuyck, Kim, Razack, Azad, Newcomb, Lisa F, Lessel, Davor, Kaneva, Radka P, Usmani, Nawaid, Claessens, Frank, Townsend, Paul, Gago Dominguez, Manuela, Roobol, Monique J, Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa A, Pandha, Hardev, Thibodeau, Stephen N, Martin, Richard M, Adams, Charleen, Richmond, Rebecca C., Santos Ferreira, Diana L, Spiller, Wes, Tan, Vanessa Y, Zheng, Jie, Wurtz, Peter, Donovan, Jenny L, Hamdy, Freddie C, Neal, David E, Lane, J Athene, Davey Smith, George, Relton, Caroline L, Eeles, Rosalind A, Henderson, Brian E, Haiman, Christopher A, Kote-Jarai, Zsofia, Schumacher, Fredrick R, Amin Al Olama, Ali, Benlloch, Sara, Muir, Kenneth, Berndt, Sonja I, Conti, David V, Wiklund, Fredrik, Chanock, Stephen J, Gapstur, Susan M, Stevens, Victoria L, Tangen, Catherine M, Batra, Jyotsna, Clements, Judith A, Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Wolk, Alicja, West, Catharine M L, Mucci, Lorelei A, Cancel-Tassin, Geraldine, Koutros, Stella, Sørensen, Karina D, Maehle, Lovise, Travis, Ruth C, Hamilton, Robert, Ingles, Sue Ann, Rosenstein, Barry S, Lu, Yong-Jie, Giles, Graham G, Kibel, Adam S, Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L, Park, Jong Y, Stanford, Janet L, Cybulski, Cezary, Nordestgaard, Borge G, Brenner, Hermann, Maier, Christiane, Kim, Jeri, John, Esther M, Teixeira, Manuel R, Neuhausen, Susan L, DeRuyck, Kim, Razack, Azad, Newcomb, Lisa F, Lessel, Davor, Kaneva, Radka P, Usmani, Nawaid, Claessens, Frank, Townsend, Paul, Gago Dominguez, Manuela, Roobol, Monique J, Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa A, Pandha, Hardev, Thibodeau, Stephen N, and Martin, Richard M

Abstract

BACKGROUND: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR). MATERIALS AND METHODS: The case-control portion of the study was conducted in nine UK centres with men aged 50-69 years who underwent prostate-specific antigen (PSA) screening for prostate cancer within the Prostate testing for cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (p <0.0014, multiple-testing threshold). These fell into four classes: i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); ii) fatty acids and ratios; iii) amino acids; iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal. CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk. IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

Published
2019
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11. Metabolic signatures of adiposity in young adults: Mendelian randomization analysis and effects of weight change

Author

Wurtz, Peter, Wang, Qin, Kangas, Antti J., Richmond, Rebecca C., Skarp, Joni, Tiainen, Mika, Tynkkynen, Tuulia, Soininen, Pasi, Havulinna, Aki S., Kaakinen, Marika, Viikari, Jorma S., Savolainen, Markku J., Kahonen, Mika, Lehtimaki, Terho, Mannisto, Satu, Blankenberg, Stefan, Zeller, Tanja, Laitinen, Jaana, Pouta, Anneli, Mantyselka, Pekka, Vanhala, Mauno, Elliott, Paul, Pietilainen, Kirsi H., Ripatti, Samuli, Salomaa, Veikko, Raitakari, Olli T., Jarvelin, Marjo-Riitta, Smith, George Davey, and Ala-Korpela, Mika

Subjects
Body weight -- Health aspects, Adipose tissues -- Health aspects, Biological sciences
Abstract

Background: Increased adiposity is linked with higher risk for cardiometabolic diseases. We aimed to determine to what extent elevated body mass index (BMI) within the normal weight range has causal effects on the detailed systemic metabolite profile in early adulthood. Methodsand Findings: We used Mendelian randomization to estimate causal effects of BMI on 82 metabolic measures in 12,664 adolescents and young adults from four population-based cohorts in Finland (mean age 26 y, range 16-39 y; 51% women; mean ± standard deviation BMI 24 ± 4 kg/[m.sup.2]). Circulating metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays. In cross-sectional analyses, elevated BMI was adversely associated with cardiometabolic risk markers throughout the systemic metabolite profile, including lipoprotein subclasses, fatty acid composition, amino acids, inflammatory markers, and various hormones (p < 0.0005 for 68 measures). Metabolite associations with BMI were generally stronger for men than for women (median 136%, interquartile range 125%-183%). A gene score for predisposition to elevated BMI, composed of 32 established genetic correlates, was used as the instrument to assess causality. Causal effects of elevated BMI closely matched observational estimates (correspondence 87% [+ or -] 3%; [R.sup.2] = 0.89), suggesting causative influences of adiposity on the levels of numerous metabolites (p < 0.0005 for 24 measures), including lipoprotein lipid subclasses and particle size, branched-chain and aromatic amino acids, and inflammation- related glycoprotein acetyls. Causal analyses of certain metabolites and potential sex differences warrant stronger statistical power. Metabolite changes associated with change in BMI during 6 y of follow-up were examined for 1,488 individuals. Change in BMI was accompanied by widespread metabolite changes, which had an association pattern similar to that of the crosssectional observations, yet with greater metabolic effects (correspondence 160% ± 2%; [R.sup.2] = 0.92). Conclusions: Mendelian randomization indicates causal adverse effects of increased adiposity with multiple cardiometabolic risk markers across the metabolite profile in adolescents and young adults within the non-obese weight range. Consistent with the causal influences of adiposity, weight changes were paralleled by extensive metabolic changes, suggesting a broadly modifiable systemic metabolite profile in early adulthood. Please see later in the article for the Editors' Summary., Introduction The prevalence of overweight and obesity has reached epidemic proportions and represents a major threat to public health worldwide [1,2]. Excess body weight, as assessed by body mass index [...]

Published
2014
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12. Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of all-cause mortality: an observational study of 17,345 persons

Author

Fischer, Krista, Kettunen, Johannes, Wurtz, Peter, Haller, Toomas, Havulinna, Aki S., Kangas, Antti J., Soininen, Pasi, Esko, Tonu, Tammesoo, Mari-Liis, Magi, Reedik, Smit, Steven, Palotie, Aarno, Ripatti, Samuli, Salomaa, Veikko, Ala-Korpela, Mika, Perola, Markus, and Metspalu, Andres

Subjects
Mortality -- Research -- Finland -- United Kingdom -- United States, Nuclear magnetic resonance spectroscopy -- Usage -- Research, Biological markers -- Physiological aspects -- Research, Biological sciences
Abstract

Background: Early identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts. Methods and Findings: 106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842;age range 18-103 y;508 deaths during a median of 5.4 y of follow-up). Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up). Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1-standard deviation increment, 95% CI 1.53-1.82, p = 5 x [10.sup.-31]), albumin (HR 0.70, 95% CI 0.65-0.76, p = 2 x [10.sup.-18]), very- low-density lipoprotein particle size (HR 0.69, 95% CI 0.62-0.77, p = 3 x [10.sup.-12]), and citrate (HR 1.33, 95% CI 1.21-1.45, p = 5 x [10.sup.-10]). All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001). Conclusions: Biomarker associations with cardiovascular, nonvascular, and cancer mortality suggest novel systemic connectivities across seemingly disparate morbidities. The biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. Further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers for guiding screening and prevention., Introduction Concentrations of metabolites and proteins in the circulation can be indicative of future disease outcomes. The existing molecular biomarkers for all-cause mortality, however, display modest predictive power and risk [...]

Published
2014
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13. Quantitative serum NMR metabolomics in large-scale epidemiology a primer on -omic technology

Author

Wurtz, Peter, Kangas, Antti J, Soininen, Pasi, Lawlor, Debbie, Davey Smith, George, and Ala-Korpela, Mika

Subjects
amino acids, metabolic profiling, Mendelian randomization, biomarkers, metabolomics, serum, drug development, fatty acids, NMR
Abstract

Detailed metabolic profiling in large-scale epidemiological studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use and has already been employed to profile over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites,and many other molecules from multiple metabolic pathways. Here we focus on applications of nuclear magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics canenhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiological understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings.

Published
2017

14. Circulating Metabolites and the Risk of Type 2 Diabetes—A Prospective Study of 10,938 Young Adults from Four Finnish Cohorts

Author

AHOLA-OLLI, ARI V., primary, MUSTELIN, LINDA, additional, KALIMERI, MARIA, additional, KETTUNEN, JOHANNES, additional, JOKELAINEN, JARI J., additional, AUVINEN, JUHA, additional, PUUKKA, KATRI S., additional, HAVULINNA, AKI S., additional, LEHTIMÄKI, TERHO, additional, KÄHÖNEN, MIKA, additional, SALOMAA, VEIKKO, additional, PEROLA, MARKUS, additional, JARVELIN, MARJO-RIITTA, additional, ALA-KORPELA, MIKA, additional, and WURTZ, PETER, additional

Published
2018
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15. Experimental and Human Evidence for Lipocalin-2 (Neutrophil Gelatinase-Associated Lipocalin [NGAL]) in the Development of Cardiac Hypertrophy and heart failure

Author

University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Marques, Francine Z., Prestes, Priscilla R., Byars, Sean G., Ritchie, Scott C., Wurtz, Peter, Patel, Sheila K., Booth, Scott A., Rana, Indrajeetsinh, Minoda, Yosuke, Berzins, Stuart P., Curl, Claire L., Bell, James R., Wai, Bryan, Srivastava, Piyush M., Kangas, Antti J., Soininen, Pasi, Ruohonen, Saku, Kahonen, Mika, Lehtimaki, Terho, Raitoharju, Emma, Havulinna, Aki, Perola, Markus, Raitakari, Olli, Salomaa, Veikko, Ala-Korpela, Mika, Kettunen, Johannes, McGlynn, Maree, Kelly, Jason, Wlodek, Mary E., Lewandowski, Paul A., Delbridge, Lea M., Burrell, Louise M., Inouye, Michael, Harrap, Stephen B., Charchar, Fadi J., University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Marques, Francine Z., Prestes, Priscilla R., Byars, Sean G., Ritchie, Scott C., Wurtz, Peter, Patel, Sheila K., Booth, Scott A., Rana, Indrajeetsinh, Minoda, Yosuke, Berzins, Stuart P., Curl, Claire L., Bell, James R., Wai, Bryan, Srivastava, Piyush M., Kangas, Antti J., Soininen, Pasi, Ruohonen, Saku, Kahonen, Mika, Lehtimaki, Terho, Raitoharju, Emma, Havulinna, Aki, Perola, Markus, Raitakari, Olli, Salomaa, Veikko, Ala-Korpela, Mika, Kettunen, Johannes, McGlynn, Maree, Kelly, Jason, Wlodek, Mary E., Lewandowski, Paul A., Delbridge, Lea M., Burrell, Louise M., Inouye, Michael, Harrap, Stephen B., and Charchar, Fadi J.

Abstract

Background-Cardiac hypertrophy increases the risk of developing heart failure and cardiovascular death. The neutrophil inflammatory protein, lipocalin-2 (LCN2/NGAL), is elevated in certain forms of cardiac hypertrophy and acute heart failure. However, a specific role for LCN2 in predisposition and etiology of hypertrophy and the relevant genetic determinants are unclear. Here, we defined the role of LCN2 in concentric cardiac hypertrophy in terms of pathophysiology, inflammatory expression networks, and genomic determinants. Methods and Results-We used 3 experimental models: a polygenic model of cardiac hypertrophy and heart failure, a model of intrauterine growth restriction and Lcn2-knockout mouse; cultured cardiomyocytes; and 2 human cohorts: 114 type 2 diabetes mellitus patients and 2064 healthy subjects of the YFS (Young Finns Study). In hypertrophic heart rats, cardiac and circulating Lcn2 was significantly overexpressed before, during, and after development of cardiac hypertrophy and heart failure. Lcn2 expression was increased in hypertrophic hearts in a model of intrauterine growth restriction, whereas Lcn2-knockout mice had smaller hearts. In cultured cardiomyocytes, Lcn2 activated molecular hypertrophic pathways and increased cell size, but reduced proliferation and cell numbers. Increased LCN2 was associated with cardiac hypertrophy and diastolic dysfunction in diabetes mellitus. In the YFS, LCN2 expression was associated with body mass index and cardiac mass and with levels of inflammatory markers. The single-nucleotide polymorphism, rs13297295, located near LCN2 defined a significant cis-eQTL for LCN2 expression. Conclusions-Direct effects of LCN2 on cardiomyocyte size and number and the consistent associations in experimental and human analyses reveal a central role for LCN2 in the ontogeny of cardiac hypertrophy and heart failure.

Published
2017

16. Metabolic profiling of pregnancy: cross-sectional and longitudinal evidence

Author

Wang, Qin, Wurtz, Peter, Auro, Kirsi, Lehtimäki, Terho, Kähönen, Mika, Lääketieteen yksikkö - School of Medicine, and University of Tampere

Subjects
Biolääketieteet - Biomedicine
Abstract

BACKGROUND: Pregnancy triggers well-known alterations in maternal glucose and lipid balance but its overall effects on systemic metabolism remain incompletely understood. METHODS: Detailed molecular profiles (87 metabolic measures and 37 cytokines) were measured for up to 4260 women (24-49 years, 322 pregnant) from three population-based cohorts in Finland. Circulating molecular concentrations in pregnant women were compared to those in non-pregnant women. Metabolic profiles were also reassessed for 583 women 6 years later to uncover the longitudinal metabolic changes in response to change in the pregnancy status. RESULTS: Compared to non-pregnant women, all lipoprotein subclasses and lipids were markedly increased in pregnant women. The most pronounced differences were observed for the intermediate-density, low-density and high-density lipoprotein triglyceride concentrations. Large differences were also seen for many fatty acids and amino acids. Pregnant women also had higher concentrations of low-grade inflammatory marker glycoprotein acetyls, higher concentrations of interleukin-18 and lower concentrations of interleukin-12p70. The changes in metabolic concentrations for women who were not pregnant at baseline but pregnant 6 years later (or vice versa) matched (or were mirror-images of) the cross-sectional association pattern. Cross-sectional results were consistent across the three cohorts and similar longitudinal changes were seen for 653 women in 4-year and 497 women in 10-year follow-up. For multiple metabolic measures, the changes increased in magnitude across the three trimesters. CONCLUSIONS: Pregnancy initiates substantial metabolic and inflammatory changes in the mothers. Comprehensive characterisation of normal pregnancy is important for gaining understanding of the key nutrients for fetal growth and development. These findings also provide a valuable molecular reference in relation to studies of adverse pregnancy outcomes. BioMed Central open access

Published
2016

18. Effects of hormonal contraception on systemic metabolism

Author

University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Quantitative Genetics, Wang, Qin, Wurtz, Peter, Auro, Kirsi, Morin-Papunen, Laure, Kangas, Antti J., Soininen, Pasi, Tiainen, Mika, Tynkkynen, Tuulia, Joensuu, Anni, Havulinna, Aki S., Aalto, Kristiina, Salmi, Marko, Blankenberg, Stefan, Zeller, Tanja, Viikari, Jorma, Kahonen, Mika, Lehtimaki, Terho, Salomaa, Veikko, Jalkanen, Sirpa, Jarvelin, Marjo-Riitta, Perola, Markus, Raitakari, Olli T., Lawlor, Debbie A., Kettunen, Johannes, Ala-Korpela, Mika, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Quantitative Genetics, Wang, Qin, Wurtz, Peter, Auro, Kirsi, Morin-Papunen, Laure, Kangas, Antti J., Soininen, Pasi, Tiainen, Mika, Tynkkynen, Tuulia, Joensuu, Anni, Havulinna, Aki S., Aalto, Kristiina, Salmi, Marko, Blankenberg, Stefan, Zeller, Tanja, Viikari, Jorma, Kahonen, Mika, Lehtimaki, Terho, Salomaa, Veikko, Jalkanen, Sirpa, Jarvelin, Marjo-Riitta, Perola, Markus, Raitakari, Olli T., Lawlor, Debbie A., Kettunen, Johannes, and Ala-Korpela, Mika

Abstract

Background: Hormonal contraception is commonly used worldwide, but its systemic effects across lipoprotein subclasses, fatty acids, circulating metabolites and cytokines remain poorly understood. Methods: A comprehensive molecular profile (75 metabolic measures and 37 cytokines) was measured for up to 5841 women (age range 24-49 years) from three population-based cohorts. Women using combined oral contraceptive pills (COCPs) or progestin-only contraceptives (POCs) were compared with those who did not use hormonal contraception. Metabolomics profiles were reassessed for 869 women after 6 years to uncover the metabolic effects of starting, stopping and persistently using hormonal contraception. Results: The comprehensive molecular profiling allowed multiple new findings on the metabolic associations with the use of COCPs. They were positively associated with lipoprotein subclasses, including all high-density lipoprotein (HDL) subclasses. The associations with fatty acids and amino acids were strong and variable in direction. COCP use was negatively associated with albumin and positively associated with creatinine and inflammatory markers, including glycoprotein acetyls and several growth factors and interleukins. Our findings also confirmed previous results e.g. for increased circulating triglycerides and HDL cholesterol. Starting COCPs caused similar metabolic changes to those observed cross-sectionally: the changes were maintained in consistent users and normalized in those who stopped using. In contrast, POCs were only weakly associated with metabolic and inflammatory markers. Results were consistent across all cohorts and for different COCP preparations and different types of POC delivery. Conclusions: Use of COCPs causes widespread metabolic and inflammatory effects. However, persistent use does not appear to accumulate the effects over time and the metabolic perturbations are reversed upon discontinuation. POCs have little effect on systemic metabolism and infla

Published
2016

19. Metabolic profiling of pregnancy

Author

University of Helsinki, Research Programs Unit, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Wang, Qin, Wurtz, Peter, Auro, Kirsi, Makinen, Ville-Petteri, Kangas, Antti J., Soininen, Pasi, Tiainen, Mika, Tynkkynen, Tuulia, Jokelainen, Jari, Santalahti, Kristiina, Salmi, Marko, Blankenberg, Stefan, Zeller, Tanja, Viikari, Jorma, Kahonen, Mika, Lehtimaki, Terho, Salomaa, Veikko, Perola, Markus, Jalkanen, Sirpa, Jarvelin, Marjo-Riitta, Raitakari, Olli T., Kettunen, Johannes, Lawlor, Debbie A., Ala-Korpela, Mika, University of Helsinki, Research Programs Unit, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Wang, Qin, Wurtz, Peter, Auro, Kirsi, Makinen, Ville-Petteri, Kangas, Antti J., Soininen, Pasi, Tiainen, Mika, Tynkkynen, Tuulia, Jokelainen, Jari, Santalahti, Kristiina, Salmi, Marko, Blankenberg, Stefan, Zeller, Tanja, Viikari, Jorma, Kahonen, Mika, Lehtimaki, Terho, Salomaa, Veikko, Perola, Markus, Jalkanen, Sirpa, Jarvelin, Marjo-Riitta, Raitakari, Olli T., Kettunen, Johannes, Lawlor, Debbie A., and Ala-Korpela, Mika

Abstract

Background: Pregnancy triggers well-known alterations in maternal glucose and lipid balance but its overall effects on systemic metabolism remain incompletely understood. Methods: Detailed molecular profiles (87 metabolic measures and 37 cytokines) were measured for up to 4260 women (24-49 years, 322 pregnant) from three population-based cohorts in Finland. Circulating molecular concentrations in pregnant women were compared to those in non-pregnant women. Metabolic profiles were also reassessed for 583 women 6 years later to uncover the longitudinal metabolic changes in response to change in the pregnancy status. Results: Compared to non-pregnant women, all lipoprotein subclasses and lipids were markedly increased in pregnant women. The most pronounced differences were observed for the intermediate-density, low-density and high-density lipoprotein triglyceride concentrations. Large differences were also seen for many fatty acids and amino acids. Pregnant women also had higher concentrations of low-grade inflammatory marker glycoprotein acetyls, higher concentrations of interleukin-18 and lower concentrations of interleukin-12p70. The changes in metabolic concentrations for women who were not pregnant at baseline but pregnant 6 years later (or vice versa) matched (or were mirror-images of) the cross-sectional association pattern. Cross-sectional results were consistent across the three cohorts and similar longitudinal changes were seen for 653 women in 4-year and 497 women in 10-year follow-up. For multiple metabolic measures, the changes increased in magnitude across the three trimesters. Conclusions: Pregnancy initiates substantial metabolic and inflammatory changes in the mothers. Comprehensive characterisation of normal pregnancy is important for gaining understanding of the key nutrients for fetal growth and development. These findings also provide a valuable molecular reference in relation to studies of adverse pregnancy outcomes.

Published
2016

20. Metabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase

Author

University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Clinicum, Wurtz, Peter, Wang, Qin, Soininen, Pasi, Kangas, Antti J., Fatemifar, Ghazaleh, Tynkkynen, Tuulia, Tiainen, Mika, Perola, Markus, Tillin, Therese, Hughes, Alun D., Mantyselka, Pekka, Kahonen, Mika, Lehtimaki, Terho, Sattar, Naveed, Hingorani, Aroon D., Casas, Juan-Pablo, Salomaa, Veikko, Kivimaki, Mika, Jarvelin, Marjo-Riitta, Smith, George Davey, Vanhala, Mauno, Lawlor, Debbie A., Raitakari, Olli T., Chaturvedi, Nish, Kettunen, Johannes, Ala-Korpela, Mika, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Clinicum, Wurtz, Peter, Wang, Qin, Soininen, Pasi, Kangas, Antti J., Fatemifar, Ghazaleh, Tynkkynen, Tuulia, Tiainen, Mika, Perola, Markus, Tillin, Therese, Hughes, Alun D., Mantyselka, Pekka, Kahonen, Mika, Lehtimaki, Terho, Sattar, Naveed, Hingorani, Aroon D., Casas, Juan-Pablo, Salomaa, Veikko, Kivimaki, Mika, Jarvelin, Marjo-Riitta, Smith, George Davey, Vanhala, Mauno, Lawlor, Debbie A., Raitakari, Olli T., Chaturvedi, Nish, Kettunen, Johannes, and Ala-Korpela, Mika

Abstract

BACKGROUND Statins are first-line therapy for cardiovascular disease prevention, but their systemic effects across lipoprotein subclasses, fatty acids, and circulating metabolites remain incompletely characterized. OBJECTIVES This study sought to determine the molecular effects of statin therapy on multiple metabolic pathways. METHODS Metabolic profiles based on serum nuclear magnetic resonance metabolomics were quantified at 2 time points in 4 population-based cohorts from the United Kingdom and Finland (N = 5,590; 2.5 to 23.0 years of follow-up). Concentration changes in 80 lipid and metabolite measures during follow-up were compared between 716 individuals who started statin therapy and 4,874 persistent nonusers. To further understand the pharmacological effects of statins, we used Mendelian randomization to assess associations of a genetic variant known to mimic inhibition of HMG-CoA reductase (the intended drug target) with the same lipids and metabolites for 27,914 individuals from 8 population-based cohorts. RESULTS Starting statin therapy was associated with numerous lipoprotein and fatty acid changes, including substantial lowering of remnant cholesterol (80% relative to low-density lipoprotein cholesterol [LDL-C]), but only modest lowering of triglycerides (25% relative to LDL-C). Among fatty acids, omega-6 levels decreased the most (68% relative to LDL-C); other fatty acids were only modestly affected. No robust changes were observed for circulating amino acids, ketones, or glycolysis-related metabolites. The intricate metabolic changes associated with statin use closely matched the association pattern with rs12916 in the HMGCR gene (R-2 = 0.94, slope 1.00 +/- 0.03). CONCLUSIONS Statin use leads to extensive lipid changes beyond LDL-C and appears efficacious for lowering remnant cholesterol. Metabolomic profiling, however, suggested minimal effects on amino acids. The results exemplify how detailed metabolic characterization of genetic proxies for drug ta

Published
2016

21. Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons

Author

University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Hjelt Institute, Fischer, Krista, Kettunen, Johannes, Wurtz, Peter, Haller, Toomas, Havulinna, Aki S., Kangas, Antti J., Soininen, Pasi, Esko, Tonu, Tammesoo, Mari-Liis, Maegi, Reedik, Smit, Steven, Palotie, Aarno, Ripatti, Samuli, Salomaa, Veikko, Ala-Korpela, Mika, Perola, Markus, Metspalu, Andres, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Hjelt Institute, Fischer, Krista, Kettunen, Johannes, Wurtz, Peter, Haller, Toomas, Havulinna, Aki S., Kangas, Antti J., Soininen, Pasi, Esko, Tonu, Tammesoo, Mari-Liis, Maegi, Reedik, Smit, Steven, Palotie, Aarno, Ripatti, Samuli, Salomaa, Veikko, Ala-Korpela, Mika, Perola, Markus, and Metspalu, Andres

Published
2014

22. Cross-sectional and longitudinal associations of circulating omega-3 and omega-6 fatty acids with lipoprotein particle concentrations and sizes: population-based cohort study with 6-year follow-up

Author

University of Helsinki, Department of General Practice and Primary Health Care, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Mantyselka, Pekka, Niskanen, Leo, Kautiainen, Hannu, Saltevo, Juha, Wurtz, Peter, Soininen, Pasi, Kangas, Antti J., Ala-Korpela, Mika, Vanhala, Mauno, University of Helsinki, Department of General Practice and Primary Health Care, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Mantyselka, Pekka, Niskanen, Leo, Kautiainen, Hannu, Saltevo, Juha, Wurtz, Peter, Soininen, Pasi, Kangas, Antti J., Ala-Korpela, Mika, and Vanhala, Mauno

Published
2014

23. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk

Author

Ehret, Georg B., Munroe, Patricia B., Rice, Kenneth M., Bochud, Murielle, Johnson, Andrew D., Chasman, Daniel I., Smith, Albert V., Tobin, Martin D., Verwoert, Germaine C., Hwang, Shih-Jen, Pihur, Vasyl, Vollenweider, Peter, O'Reilly, Paul F., Amin, Najaf, Bragg-Gresham, Jennifer L., Teumer, Alexander, Glazer, Nicole L., Launer, Lenore, Zhao, Jing Hua, Aulchenko, Yurii, Heath, Simon, Sober, Siim, Parsa, Afshin, Luan, Jian'an, Arora, Pankaj, Dehghan, Abbas, Zhang, Feng, Lucas, Gavin, Hicks, Andrew A., Jackson, Anne U., Peden, John F., Tanaka, Toshiko, Wild, Sarah H., Rudan, Igor, Igl, Wilmar, Milaneschi, Yuri, Parker, Alex N., Fava, Cristiano, Chambers, John C., Fox, Ervin R., Kumari, Meena, Go, Min Jin, van der Harst, Pim, Kao, Wen Hong Linda, Sjogren, Marketa, Vinay, D. G., Alexander, Myriam, Tabara, Yasuharu, Shaw-Hawkins, Sue, Whincup, Peter H., Liu, Yongmei, Shi, Gang, Kuusisto, Johanna, Tayo, Bamidele, Seielstad, Mark, Sim, Xueling, Nguyen, Khanh-Dung Hoang, Lehtimaki, Terho, Matullo, Giuseppe, Wu, Ying, Gaunt, Tom R., Onland-Moret, N. Charlotte, Cooper, Matthew N., Platou, Carl G. P., Org, Elin, Hardy, Rebecca, Dahgam, Santosh, Palmen, Jutta, Vitart, Veronique, Braund, Peter S., Kuznetsova, Tatiana, Uiterwaal, Cuno S. P. M., Adeyemo, Adebowale, Palmas, Walter, Campbell, Harry, Ludwig, Barbara, Tomaszewski, Maciej, Tzoulaki, Ioanna, Palmer, Nicholette D., Aspelund, Thor, Garcia, Melissa, Chang, Yen-Pei C., O'Connell, Jeffrey R., Steinle, Nanette I., Grobbee, Diederick E., Arking, Dan E., Kardia, Sharon L., Morrison, Alanna C., Hernandez, Dena, Najjar, Samer, McArdle, Wendy L., Hadley, David, Brown, Morris J., Connell, John M., Hingorani, Aroon D., Day, Ian N. M., Lawlor, Debbie A., Beilby, John P., Lawrence, Robert W., Clarke, Robert, Hopewell, Jemma C., Ongen, Halit, Dreisbach, Albert W., Li, Yali, Young, J. Hunter, Bis, Joshua C., Kahonen, Mika, Viikari, Jorma, Adair, Linda S., Lee, Nanette R., Chen, Ming-Huei, Olden, Matthias, Pattaro, Cristian, Bolton, Judith A. Hoffman, Koettgen, Anna, Bergmann, Sven, Mooser, Vincent, Chaturvedi, Nish, Frayling, Timothy M., Islam, Muhammad, Jafar, Tazeen H., Erdmann, Jeanette, Kulkarni, Smita R., Bornstein, Stefan R., Graessler, Juergen, Groop, Leif, Voight, Benjamin F., Kettunen, Johannes, Howard, Philip, Taylor, Andrew, Guarrera, Simonetta, Ricceri, Fulvio, Emilsson, Valur, Plump, Andrew, Barroso, Ine S., Khaw, Kay-Tee, Weder, Alan B., Hunt, Steven C., Sun, Yan V., Bergman, Richard N., Collins, Francis S., Bonnycastle, Lori L., Scott, Laura J., Stringham, Heather M., Peltonen, Leena, Perola, Markus, Vartiainen, Erkki, Brand, Stefan-Martin, Staessen, Jan A., Wang, Thomas J., Burton, Paul R., Artigas, Maria Soler, Dong, Yanbin, Snieder, Harold, Wang, Xiaoling, Zhu, Haidong, Lohman, Kurt K., Rudock, Megan E., Heckbert, Susan R., Smith, Nicholas L., Wiggins, Kerri L., Doumatey, Ayo, Shriner, Daniel, Veldre, Gudrun, Viigimaa, Margus, Kinra, Sanjay, Prabhakaran, Dorairaj, Tripathy, Vikal, Langefeld, Carl D., Rosengren, Annika, Thelle, Dag S., Corsi, Anna Maria, Singleton, Andrew, Forrester, Terrence, Hilton, Gina, McKenzie, Colin A., Salako, Tunde, Iwai, Naoharu, Kita, Yoshikuni, Ogihara, Toshio, Ohkubo, Takayoshi, Okamura, Tomonori, Ueshima, Hirotsugu, Umemura, Satoshi, Eyheramendy, Susana, Meitinger, Thomas, Wichmann, H. -Erich, Cho, Yoon Shin, Kim, Hyung-Lae, Lee, Jong-Young, Scott, James, Sehmi, Joban S., Zhang, Weihua, Hedblad, Bo, Nilsson, Peter, Smith, George Davey, Wong, Andrew, Narisu, Narisu, Stancakova, Alena, Raffel, Leslie J., Yao, Jie, Kathiresan, Sekar, O'Donnell, Christopher J., Schwartz, Stephen M., Ikram, M. Arfan, Longstreth, W. T., Jr., Mosley, Thomas H., Seshadri, Sudha, Shrine, Nick R. G., Wain, Louise V., Morken, Mario A., Swift, Amy J., Laitinen, Jaana, Prokopenko, Inga, Zitting, Paavo, Cooper, Jackie A., Humphries, Steve E., Danesh, John, Rasheed, Asif, Goel, Anuj, Hamsten, Anders, Watkins, Hugh, Bakker, Stephan J. L., van Gilst, Wiek H., Janipalli, Charles S., Mani, K. Radha, Yajnik, Chittaranjan S., Hofman, Albert, Mattace-Raso, Francesco U. S., Oostra, Ben A., Demirkan, Ayse, Isaacs, Aaron, Rivadeneira, Fernando, Lakatta, Edward G., Orru, Marco, Scuteri, Angelo, Ala-Korpela, Mika, Kangas, Antti J., Lyytikainen, Leo-Pekka, Soininen, Pasi, Tukiainen, Taru, Wurtz, Peter, Ong, Rick Twee-Hee, Doerr, Marcus, Kroemer, Heyo K., Voelker, Uwe, Voelzke, Henry, Galan, Pilar, Hercberg, Serge, Lathrop, Mark, Zelenika, Diana, Deloukas, Panos, Mangino, Massimo, Spector, Tim D., Zhai, Guangju, Meschia, James F., Nalls, Michael A., Sharma, Pankaj, Terzic, Janos, Kumar, M. V. Kranthi, Denniff, Matthew, Zukowska-Szczechowska, Ewa, Wagenknecht, Lynne E., Fowkes, F. Gerald R., Charchar, Fadi J., Schwarz, Peter E. H., Hayward, Caroline, Guo, Xiuqing, Rotimi, Charles, Bots, Michiel L., Brand, Eva, Samani, Nilesh J., Polasek, Ozren, Talmud, Philippa J., Nyberg, Fredrik, Kuh, Diana, Laan, Maris, Hveem, Kristian, Palmer, Lyle J., van der Schouw, Yvonne T., Casas, Juan P., Mohlke, Karen L., Vineis, Paolo, Raitakari, Olli, Ganesh, Santhi K., Wong, Tien Y., Tai, E. Shyong, Cooper, Richard S., Laakso, Markku, Rao, Dabeeru C., Harris, Tamara B., Morris, Richard W., Dominiczak, Anna F., Kivimaki, Mika, Marmot, Michael G., Miki, Tetsuro, Saleheen, Danish, Chandak, Giriraj R., Coresh, Josef, Navis, Gerjan, Salomaa, Veikko, Han, Bok-Ghee, Zhu, Xiaofeng, Kooner, Jaspal S., Melander, Olle, Ridker, Paul M., Bandinelli, Stefania, Gyllensten, Ulf B., Wright, Alan F., Wilson, James F., Ferrucci, Luigi, Farrall, Martin, Tuomilehto, Jaakko, Pramstaller, Peter P., Elosua, Roberto, Soranzo, Nicole, Sijbrands, Eric J. G., Altshuler, David, Loos, Ruth J. F., Shuldiner, Alan R., Gieger, Christian, Meneton, Pierre, Uitterlinden, Andre G., Wareham, Nicholas J., Gudnason, Vilmundur, Rotter, Jerome I., Rettig, Rainer, Uda, Manuela, Strachan, David P., Witteman, Jacqueline C. M., Hartikainen, Anna-Liisa, Beckmann, Jacques S., Boerwinkle, Eric, Vasan, Ramachandran S., Boehnke, Michael, Larson, Martin G., Jarvelin, Marjo-Riitta, Psaty, Bruce M., Abecasis, Goncalo R., Chakravarti, Aravinda, Elliott, Paul, van Duijn, Cornelia M., Newton-Cheh, Christopher, Levy, Daniel, Caulfield, Mark J., Johnson, Toby, Ehret, Georg B., Munroe, Patricia B., Rice, Kenneth M., Bochud, Murielle, Johnson, Andrew D., Chasman, Daniel I., Smith, Albert V., Tobin, Martin D., Verwoert, Germaine C., Hwang, Shih-Jen, Pihur, Vasyl, Vollenweider, Peter, O'Reilly, Paul F., Amin, Najaf, Bragg-Gresham, Jennifer L., Teumer, Alexander, Glazer, Nicole L., Launer, Lenore, Zhao, Jing Hua, Aulchenko, Yurii, Heath, Simon, Sober, Siim, Parsa, Afshin, Luan, Jian'an, Arora, Pankaj, Dehghan, Abbas, Zhang, Feng, Lucas, Gavin, Hicks, Andrew A., Jackson, Anne U., Peden, John F., Tanaka, Toshiko, Wild, Sarah H., Rudan, Igor, Igl, Wilmar, Milaneschi, Yuri, Parker, Alex N., Fava, Cristiano, Chambers, John C., Fox, Ervin R., Kumari, Meena, Go, Min Jin, van der Harst, Pim, Kao, Wen Hong Linda, Sjogren, Marketa, Vinay, D. G., Alexander, Myriam, Tabara, Yasuharu, Shaw-Hawkins, Sue, Whincup, Peter H., Liu, Yongmei, Shi, Gang, Kuusisto, Johanna, Tayo, Bamidele, Seielstad, Mark, Sim, Xueling, Nguyen, Khanh-Dung Hoang, Lehtimaki, Terho, Matullo, Giuseppe, Wu, Ying, Gaunt, Tom R., Onland-Moret, N. Charlotte, Cooper, Matthew N., Platou, Carl G. P., Org, Elin, Hardy, Rebecca, Dahgam, Santosh, Palmen, Jutta, Vitart, Veronique, Braund, Peter S., Kuznetsova, Tatiana, Uiterwaal, Cuno S. P. M., Adeyemo, Adebowale, Palmas, Walter, Campbell, Harry, Ludwig, Barbara, Tomaszewski, Maciej, Tzoulaki, Ioanna, Palmer, Nicholette D., Aspelund, Thor, Garcia, Melissa, Chang, Yen-Pei C., O'Connell, Jeffrey R., Steinle, Nanette I., Grobbee, Diederick E., Arking, Dan E., Kardia, Sharon L., Morrison, Alanna C., Hernandez, Dena, Najjar, Samer, McArdle, Wendy L., Hadley, David, Brown, Morris J., Connell, John M., Hingorani, Aroon D., Day, Ian N. M., Lawlor, Debbie A., Beilby, John P., Lawrence, Robert W., Clarke, Robert, Hopewell, Jemma C., Ongen, Halit, Dreisbach, Albert W., Li, Yali, Young, J. Hunter, Bis, Joshua C., Kahonen, Mika, Viikari, Jorma, Adair, Linda S., Lee, Nanette R., Chen, Ming-Huei, Olden, Matthias, Pattaro, Cristian, Bolton, Judith A. Hoffman, Koettgen, Anna, Bergmann, Sven, Mooser, Vincent, Chaturvedi, Nish, Frayling, Timothy M., Islam, Muhammad, Jafar, Tazeen H., Erdmann, Jeanette, Kulkarni, Smita R., Bornstein, Stefan R., Graessler, Juergen, Groop, Leif, Voight, Benjamin F., Kettunen, Johannes, Howard, Philip, Taylor, Andrew, Guarrera, Simonetta, Ricceri, Fulvio, Emilsson, Valur, Plump, Andrew, Barroso, Ine S., Khaw, Kay-Tee, Weder, Alan B., Hunt, Steven C., Sun, Yan V., Bergman, Richard N., Collins, Francis S., Bonnycastle, Lori L., Scott, Laura J., Stringham, Heather M., Peltonen, Leena, Perola, Markus, Vartiainen, Erkki, Brand, Stefan-Martin, Staessen, Jan A., Wang, Thomas J., Burton, Paul R., Artigas, Maria Soler, Dong, Yanbin, Snieder, Harold, Wang, Xiaoling, Zhu, Haidong, Lohman, Kurt K., Rudock, Megan E., Heckbert, Susan R., Smith, Nicholas L., Wiggins, Kerri L., Doumatey, Ayo, Shriner, Daniel, Veldre, Gudrun, Viigimaa, Margus, Kinra, Sanjay, Prabhakaran, Dorairaj, Tripathy, Vikal, Langefeld, Carl D., Rosengren, Annika, Thelle, Dag S., Corsi, Anna Maria, Singleton, Andrew, Forrester, Terrence, Hilton, Gina, McKenzie, Colin A., Salako, Tunde, Iwai, Naoharu, Kita, Yoshikuni, Ogihara, Toshio, Ohkubo, Takayoshi, Okamura, Tomonori, Ueshima, Hirotsugu, Umemura, Satoshi, Eyheramendy, Susana, Meitinger, Thomas, Wichmann, H. -Erich, Cho, Yoon Shin, Kim, Hyung-Lae, Lee, Jong-Young, Scott, James, Sehmi, Joban S., Zhang, Weihua, Hedblad, Bo, Nilsson, Peter, Smith, George Davey, Wong, Andrew, Narisu, Narisu, Stancakova, Alena, Raffel, Leslie J., Yao, Jie, Kathiresan, Sekar, O'Donnell, Christopher J., Schwartz, Stephen M., Ikram, M. Arfan, Longstreth, W. T., Jr., Mosley, Thomas H., Seshadri, Sudha, Shrine, Nick R. G., Wain, Louise V., Morken, Mario A., Swift, Amy J., Laitinen, Jaana, Prokopenko, Inga, Zitting, Paavo, Cooper, Jackie A., Humphries, Steve E., Danesh, John, Rasheed, Asif, Goel, Anuj, Hamsten, Anders, Watkins, Hugh, Bakker, Stephan J. L., van Gilst, Wiek H., Janipalli, Charles S., Mani, K. Radha, Yajnik, Chittaranjan S., Hofman, Albert, Mattace-Raso, Francesco U. S., Oostra, Ben A., Demirkan, Ayse, Isaacs, Aaron, Rivadeneira, Fernando, Lakatta, Edward G., Orru, Marco, Scuteri, Angelo, Ala-Korpela, Mika, Kangas, Antti J., Lyytikainen, Leo-Pekka, Soininen, Pasi, Tukiainen, Taru, Wurtz, Peter, Ong, Rick Twee-Hee, Doerr, Marcus, Kroemer, Heyo K., Voelker, Uwe, Voelzke, Henry, Galan, Pilar, Hercberg, Serge, Lathrop, Mark, Zelenika, Diana, Deloukas, Panos, Mangino, Massimo, Spector, Tim D., Zhai, Guangju, Meschia, James F., Nalls, Michael A., Sharma, Pankaj, Terzic, Janos, Kumar, M. V. Kranthi, Denniff, Matthew, Zukowska-Szczechowska, Ewa, Wagenknecht, Lynne E., Fowkes, F. Gerald R., Charchar, Fadi J., Schwarz, Peter E. H., Hayward, Caroline, Guo, Xiuqing, Rotimi, Charles, Bots, Michiel L., Brand, Eva, Samani, Nilesh J., Polasek, Ozren, Talmud, Philippa J., Nyberg, Fredrik, Kuh, Diana, Laan, Maris, Hveem, Kristian, Palmer, Lyle J., van der Schouw, Yvonne T., Casas, Juan P., Mohlke, Karen L., Vineis, Paolo, Raitakari, Olli, Ganesh, Santhi K., Wong, Tien Y., Tai, E. Shyong, Cooper, Richard S., Laakso, Markku, Rao, Dabeeru C., Harris, Tamara B., Morris, Richard W., Dominiczak, Anna F., Kivimaki, Mika, Marmot, Michael G., Miki, Tetsuro, Saleheen, Danish, Chandak, Giriraj R., Coresh, Josef, Navis, Gerjan, Salomaa, Veikko, Han, Bok-Ghee, Zhu, Xiaofeng, Kooner, Jaspal S., Melander, Olle, Ridker, Paul M., Bandinelli, Stefania, Gyllensten, Ulf B., Wright, Alan F., Wilson, James F., Ferrucci, Luigi, Farrall, Martin, Tuomilehto, Jaakko, Pramstaller, Peter P., Elosua, Roberto, Soranzo, Nicole, Sijbrands, Eric J. G., Altshuler, David, Loos, Ruth J. F., Shuldiner, Alan R., Gieger, Christian, Meneton, Pierre, Uitterlinden, Andre G., Wareham, Nicholas J., Gudnason, Vilmundur, Rotter, Jerome I., Rettig, Rainer, Uda, Manuela, Strachan, David P., Witteman, Jacqueline C. M., Hartikainen, Anna-Liisa, Beckmann, Jacques S., Boerwinkle, Eric, Vasan, Ramachandran S., Boehnke, Michael, Larson, Martin G., Jarvelin, Marjo-Riitta, Psaty, Bruce M., Abecasis, Goncalo R., Chakravarti, Aravinda, Elliott, Paul, van Duijn, Cornelia M., Newton-Cheh, Christopher, Levy, Daniel, Caulfield, Mark J., and Johnson, Toby

Abstract

Blood pressure is a heritable trait(1) influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (>= 140 mm Hg systolic blood pressure or >= 90 mm Hg diastolic blood pressure)(2). Even small increments in blood pressure are associated with an increased risk of cardiovascular events(3). This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention.

Published
2011
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24. 516-P: Urine Metabolite Biomarkers Predict Progression of Diabetic Nephropathy in 2,531 Individuals with Type 1 Diabetes.

Author

MUTTER, STEFAN, VALO, ERKKA A., AITTOMÄKI, VILJAMI, FORSBLOM, CAROL, GROOP, PER-HENRIK, and WURTZ, PETER

Abstract

People living with type 1 diabetes have increased risk to develop diabetic nephropathy. No targeted cure exists, but the progression can be slowed down if detected early. We tested whether metabolic biomarkers measured in urine could predict progression of diabetic nephropathy (DN) in the Finnish nationwide FinnDiane Study. At baseline, 18 urine metabolites were measured with nuclear magnetic resonance metabolomics and scaled relative to urine creatinine. Individuals were followed for DN status for 9.0 years (± 5.1 years) until they progressed to their most severe DN status (334 events) or the latest known DN status for non-progressors. A Bonferroni-corrected P<0.003 was considered significant. Five out of 18 urine metabolites were robustly associated with risk for DN progression in Cox regression models adjusted for sex, year of diabetes diagnosis as well as baseline age, DN status, BMI and eGFR. Individuals with elevated urinary levels of alanine (Hazard Ratio (HR) = 1.49 [1.26, 1.77] per 1-SD creatinine-scaled metabolite concentration, , P=3×10-6), valine (HR = 1.34 [1.22, 1.48], P=4×10-9), 2–hydroxyisobutyrate (HR = 1.48 [1.30, 1.67], P=1×10-9), cis-Aconitate (HR = 1.17 [1.06, 1.28], P=9×10-4) and pseudouridine (HR = 1.45 [1.24, 1.69], P=4×10-6) showed higher DN progression rate. We conclude that urinary biomarkers are indicative of kidney disease progression in type 1 diabetes, independently of baseline microalbuminuria and eGFR. The urinary biomarkers span multiple metabolic pathways, including microbial metabolism, citric acid cycle, and amino acids reflecting adiposity and dietary quality. Disclosure: S. Mutter: None. E.A. Valo: None. V. Aittomäki: Employee; Self; Nightingale Health Ltd. Other Relationship; Self; Nightingale Health Ltd. C. Forsblom: None. P. Groop: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Sanofi, Sanofi. Speaker's Bureau; Self; Astellas Pharma Inc., AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medscape, Merck Sharp & Dohme Corp., Mundipharma International. P. Wurtz: Employee; Self; Nightingale Health Ltd. Stock/Shareholder; Self; Nightingale Health Ltd. Funding: Folkhälsan Finland; Novo Nordisk Foundation; Academy of Finland [ABSTRACT FROM AUTHOR]

Published
2020
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25. Metabolomic consequences of genetic inhibition of PCSK9 compared with statin treatment

Author

Sliz, Eeva, Kettunen, Johannes, Holmes, Michael, Oliver-Williams, Clare, Boachie, Charles, Wang, Qin, Mannikko, Minna, Sebert, Sylvain, Walters, Robin, Lin, Kuang, Millwood, Iona, Clarke, Robert, Lee, Liming, Rankin, Naomi, Welsh, Paul, Delles, Christian, Ford, Ian, Jukema, Wouter, Trompet, Stella, Perola, Markus, Salomaa, Veikko, Jarvelin, Marjo-Riitta, Chen, Zhengming, Lawlor, Debbie, Ala-Korpela, Mika, Danesh, John, Davey Smith, George, Sattar, Naveed, Butterworth, Adam, and Wurtz, Peter

Subjects
lipoproteins, Mendelian randomization analysis, lipids (amino acids, peptides, and proteins), metabolomics, 3. Good health
Abstract

Both statins and PCSK9 inhibitors lower blood low-density lipoprotein cholesterol (LDL-C) levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these two lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial, and compared the results with the effects of genetic inhibition of PCSK9, acting as a naturally occurring trial. Methods: 228 circulating metabolic measures were quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5,359 individuals (2,659 on treatment) in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial at 6-months post-randomization. The corresponding metabolic measures were analyzed in eight population cohorts (N=72,185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors. Results: Scaled to an equivalent lowering of LDL-C, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy ( R 2 =0.88). Alterations in lipoprotein lipid composition and fatty acid balance were similar. However, discrepancies were observed for very-low-density lipoprotein (VLDL) lipid measures. For instance, genetic inhibition of PCSK9 showed weaker effects on lowering of VLDL-cholesterol compared with statin therapy (54% vs. 77% reduction, relative to the lowering effect on LDL-C; P =2x10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no robust effects on amino acids, ketones, and a marker of inflammation (GlycA); in contrast, statin treatment lowered GlycA levels. Conclusions: Genetic inhibition of PCSK9 results in similar metabolic effects as statin therapy across a detailed lipid and metabolite profile. However, for the same lowering of LDL-C, PCSK9 inhibitors are predicted to be less efficacious at lowering VLDL lipids, which could potentially translate into subtle differences in cardiovascular risk reduction.

26. Abstract 10212: Fasting Samples Are Not Required for Nmr Metabolic Profiling Studies of Cardiovascular Disease Risk: Prospective Data for 4,400 Individuals Profiled Few Weeks Apart

Author

Tikkanen, Emmi, Kanerva, Noora, Aittomaki, Viljami, M?nnist?, Satu, Salomaa, Veikko V, and Wurtz, Peter

Abstract

Background:Metabolic profiling technologies have uncovered a wealth of blood biomarkers predictive of cardiovascular disease (CVD) incidence and progression. Due to dietary influences, fasting samples are commonly recommended for metabolomics. However, the consistency of biomarker results for fasting and non-fasting samples with cardiovascular disease is unknown.Methods:For 4,400 participants of the FINRISK 2007 survey and its extension DILGOM cohort, fasting (9-21 hours) and non-fasting (0-7 hours) blood samples were collected 4-8 weeks apart. We quantified 228 circulating biomarkers by NMR metabolomics and compared fasting and non-fasting biomarker associations with incident CVD (n=285 events) using Cox proportional hazard models.Results:Lipids were highly correlated between fasting and non-fasting visits (for instance, r=0.86 for apoB/apoA1, r=0.88 for HDL particle size, and r=0.73 for remnant-cholesterol). Correlations were slightly weaker for fatty acids (r=0.48 for omega-3%, r=0.62 for omega-6% and r=0.67 for MUFA%). The consistency of concentrations was weaker for branched-chain and aromatic amino acids as well as glycolysis metabolites (r=0.41-0.53), which were similar to fasting vs non-fasting glucose (r=0.51). However, biomarker associations with CVD risk were remarkably consistent for fasting and non-fasting samples (Figure 1). Fatty acids, amino acids, glycolysis-related metabolites, glycoprotein acetylation and detailed lipoprotein measures were predictive of CVD events in both fasting and non-fasting samples.Conclusions:Metabolic biomarker associations with incident CVD are similar for fasting and non-fasting samples in large cohort studies. Non-fasting blood samples are appropriate to use for biomarker discovery and risk prediction analyses with NMR metabolomics.

Published
2019
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27. Abstract 10433: Differences in Lipoprotein and Metabolite Biomarkers for Subtypes of Cardiovascular Disease: Blood Biomarker Profiling of 25,000 Individuals From Four Prospective Studies

Author

Tikkanen, Emmi, Aittomaki, Viljami, Mustelin, Linda, Jousilahti, Pekka, Salomaa, Veikko V, and Wurtz, Peter

Abstract

Background:Cardiovascular disease (CVD) is a heterogenous group of diseases, and the underlying metabolic abnormalities for different CVD subtypes are unclear. We conducted detailed metabolic profiling of incident coronary artery disease (CAD), ischemic stroke (IS), and peripheral artery disease (PAD) to identify novel risk factors and new treatment targets for these diseases.Methods:We measured 228 circulating biomarkers using an NMR metabolomics platform (Nightingale Health, Finland) in four large prospective studies from Finland (national FINRISK studies, total n= 25,299). We used Cox proportional hazard modelling to estimate associations between biomarkers and incident CAD, IS and PAD (nevents = 1387, 758, and 339, respectively, during the median follow-up time of 14 years).Results:We observed substantial differences in biomarker association profiles for the CVD subtypes (Figure 1). Higher cholesterol in VLDL and LDL lipoproteins and apolipoprotein B associated with increased CAD risk (HR=1.32, 95% CI 1.25-1.40; 1.23, 95% CI 1.16-1.30; and 1.35, 95% CI 1.28-1.43 per SD-change), but not with IS (HR=1.07, 95% CI 0.99-1.15; 0.99, 95% CI 0.91-1.07; and 1.04, 95% CI 0.96-1.13) or PAD (HR=1.10, 95% CI 0.98-1.24; 0.88, 95% CI 0.79-0.99; and 1.05, 95% CI 0.93-1.18). In contrast, high triglycerides in LDL increased the risk for both CAD and PAD. Further, we observed stronger effects of some fatty acids, amino acids, glycolysis-related metabolites and glycoprotein acetyls for PAD when compared to other endpoints.Conclusions:Different metabolic abnormalities underlie the pathophysiology of CVD subtypes. Novel biomarkers could be used to guide the development of new therapies for these diseases.

Published
2019
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28. CLASSIC ON THE AIR.

Author

Gendrich, Charles P., McGurrell, Neal, Gillman, Mark, Wurtz, Peter, Crouse, Don, and Allen, R. C.

Subjects
WIT & humor, AERONAUTICS
Abstract

Several jokes are presented about over-the-air conversations from readers.

Published
2012

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