Afekta

Publications

Our team has accumulated over 50 years of experience in scientific research. We have been
involved in nearly 100 metabolomics-related publications, which have received more than
2500 citations. Listed below are the most important papers.

Methodology

  1. Babu, AF, Koistinen, VM, Turunen, S, Solano-Aguilar, G, Urban Jr, JF, Zarei, I, & Hanhineva, K (2022). Identification and Distribution of Sterols, Bile Acids, and Acylcarnitines by LC–MS/MS in Humans, Mice, and Pigs—A Qualitative Analysis. Metabolites, 12(1), 49.
  2. Klåvus, A, Kokla, M, Noerman, S, Koistinen, VM, Tuomainen, M, Zarei, I, ... & Hanhineva, K (2020). “Notame”: workflow for non-targeted LC–MS metabolic profiling. Metabolites, 10(4), 135.

Microbiota

  1. Moadi, L, Turjeman, S, Asulin, N, & Koren, O (2024). The effect of testosterone on the gut microbiome in mice. Communications Biology, 7(1), 880.
  2. Cohen, A, Turjeman, S, Levin, R, Tal, S, & Koren, O (2024). Comparison of canine colostrum and milk using a multi-omics approach. Animal Microbiome, 6(1), 19.
  3. Husso, A, Pessa-Morikawa, T, Koistinen, VM, Kärkkäinen, O, Kwon, HN, Lahti, L, ... & Niku, M (2023). Impacts of maternal microbiota and microbial metabolites on fetal intestine, brain, and placenta. BMC Biology, 21(1), 207.
  4. Ahmed, H, Leyrolle, Q, Koistinen, V, Kärkkäinen, O, Layé, S, Delzenne, N, & Hanhineva, K (2022). Microbiota-derived metabolites as drivers of gut–brain communication. Gut Microbes, 14(1), 2102878.
  5. Pessa-Morikawa, T, Husso, A, Kärkkäinen, O, Koistinen, V, Hanhineva, K, Iivanainen, A, & Niku, M (2022). Maternal microbiota-derived metabolic profile in fetal murine intestine, brain and placenta. BMC Microbiology, 22(1), 46.
  6. Haikonen, R, Kärkkäinen, O, Koistinen, V, & Hanhineva, K (2022). Diet-and microbiota-related metabolite, 5-aminovaleric acid betaine (5-AVAB), in health and disease. Trends in Endocrinology & Metabolism, 33(7), 463-480.
  7. Zarei, I, Koistinen, VM, Kokla, M, Klåvus, A, Babu, AF, Lehtonen, M, ... & Hanhineva, K (2022). Tissue-wide metabolomics reveals wide impact of gut microbiota on mice metabolite composition. Scientific Reports, 12(1), 15018.
  8. Koistinen, VM, Hedberg, M, Shi, L, Johansson, A, Savolainen, O, Lehtonen, M, Aura, AM, Hanhineva, K, & Landberg, R (2022). Metabolite Pattern Derived from Lactiplantibacillus plantarum—Fermented Rye Foods and In Vitro Gut Fermentation Synergistically Inhibits Bacterial Growth. Molecular Nutrition & Food Research, 66(21), 2101096.
  9. Koistinen, V. M., Kärkkäinen, O., Borewicz, K., Zarei, I., Jokkala, J., Micard, V., ... & Hanhineva, K. (2019). Contribution of gut microbiota to metabolism of dietary glycine betaine in mice and in vitro colonic fermentation. Microbiome, 7(1), 103.
  10. Koistinen, V. M., & Hanhineva, K. (2017). Microbial and endogenous metabolic conversions of rye phytochemicals. Molecular Nutrition & Food Research, 61(7), 1600627.
  11. Hanhineva, K., Aura, A. M., Rogachev, I., Matero, S., Skov, T., Aharoni, A., ... & Mykkänen, H. (2012). In vitro microbiotic fermentation causes an extensive metabolite turnover of rye bran phytochemicals. PLoS One, 7(6).

Biomedicine

  1. Masalin S, Klåvus A, Rönö K, Koistinen H, Koistinen V, Kärkkäinen O, Jääskeläinen TJ, Klemetti MM (2024). Analysis of early-pregnancy metabolome in early- and late-onset gestational diabetes reveals distinct associations with maternal overweight. Diabetologia.
  2. Iannone, V, Lok, J, Babu, AF, Gómez-Gallego, C, Willman, RM, Koistinen, VM, ... & El-Nezami, H (2023). Associations of altered hepatic gene expression in American lifestyle-induced obesity syndrome diet-fed mice with metabolic changes during NAFLD development and progression. The Journal of Nutritional Biochemistry, 115, 109307.
  3. Babu, AF, Csader, S, Männistö, V, Tauriainen, MM, Pentikäinen, H, Savonen, K, ... & Schwab, U (2022). Effects of exercise on NAFLD using non-targeted metabolomics in adipose tissue, plasma, urine, and stool. Scientific Reports, 12(1), 6485.
  4. Toljamo, A, Koistinen, V, Hanhineva, K, Kärenlampi, S, & Kokko, H (2021). Terpenoid and lipid profiles vary in different Phytophthora cactorum–strawberry interactions. Phytochemistry, 189, 112820.
  5. Palviainen M, Saari H, Kärkkäinen O, Pekkinen J, Auriola S, Yliperttula M, Puhka M, Hanhineva K, Siljander P. (2019). Metabolic signature of extracellular vesicles depends on the cell culture conditions. Journal of Extracellular Vesicles, 8, 1596669.
  6. Kärkkäinen O, Tuomainen T, Mutikainen M, Lehtonen M, Ruas JL, Hanhineva K, Tavi P. (2019). Heart specific PGC-1α deletion identifies metabolome of cardiac restricted metabolic heart failure. Cardiovascular research, 115: 107-118.
  7. Voutilainen T and Kärkkäinen O. (2019). Changes in the human metabolome associated with alcohol use: a review. Alcohol and Alcoholism, 54, 225-234.
  8. Jääskeläinen T, Kärkkäinen O, Jokkala J, Litonius K, Heinonen S, Auriola S, Lehtonen M, Hanhineva K, Laivuori H for the FINNPEC. (2018). A Non-Targeted LC-MS Profiling Reveals Elevated Levels of Carnitine Precursors and Trimethylated Compounds in the Cord Plasma of Pre-Eclamptic Infants. Scientific Reports, 8, 14616.
  9. Lehikoinen A, Kärkkäinen O, Lehtonen M, Auriola S, Hanhineva K, Heinonen S. (2018). Alcohol and substance use are associated with altered metabolome in the first trimester serum samples of pregnant mothers. European Journal of Obstetrics & Gynecology and Reproductive Biology, 223:79-84.
  10. Kärkkäinen, O., Tuomainen, T., Koistinen, V., Tuomainen, M., Leppänen, J., Laitinen, T., ... & Tavi, P. (2018). Whole grain intake associated molecule 5-aminovaleric acid betaine decreases β-oxidation of fatty acids in mouse cardiomyocytes. Scientific Reports, 8(1), 1-7.
  11. Koistinen, V. M., Bento da Silva, A., Abrankó, L., Low, D., Garcia Villalba, R., Tomás Barberán, F., ... & Bronze, M. R. (2018). Interlaboratory coverage test on plant food bioactive compounds and their metabolites by mass spectrometry-based untargeted metabolomics. Metabolites, 8(3), 46.
  12. De Mello, V. D., Paananen, J., Lindström, J., Lankinen, M. A., Shi, L., Kuusisto, J., ... & Bergdahl, I. A. (2017). Indolepropionic acid and novel lipid metabolites are associated with a lower risk of type 2 diabetes in the Finnish Diabetes Prevention Study. Scientific Reports, 7, 46337.
  13. Puurunen, J., Sulkama, S., Tiira, K., Araujo, C., Lehtonen, M., Hanhineva, K., & Lohi, H. (2016). A non-targeted metabolite profiling pilot study suggests that tryptophan and lipid metabolisms are linked with ADHD-like behaviours in dogs. Behavioral and Brain Functions, 12(1), 27.
  14. Puurunen, J., Tiira, K., Lehtonen, M., Hanhineva, K., & Lohi, H. (2016). Non-targeted metabolite profiling reveals changes in oxidative stress, tryptophan and lipid metabolisms in fearful dogs. Behavioral and Brain Functions, 12(1), 7.
  15. Lankinen, M. A., Hanhineva, K., Kolehmainen, M., Lehtonen, M., Auriola, S., Mykkänen, H., ... & Uusitupa, M. (2015). CMPF does not associate with impaired glucose metabolism in individuals with features of metabolic syndrome. PloS one, 10(4).

Nutrition

  1. Meuronen, T, Lankinen, MA, Kärkkäinen, O, Laakso, M, Pihlajamäki, J, Hanhineva, K, & Schwab, U (2022). FADS1 rs174550 genotype and high linoleic acid diet modify plasma PUFA phospholipids in a dietary intervention study. European Journal of Nutrition, 1-12.
  2. Bento-Silva, A, Koistinen, VM, Mena, P, Bronze, MR, Hanhineva, K, Sahlstrøm, S, ... & Aura, AM (2020). Factors affecting intake, metabolism and health benefits of phenolic acids: do we understand individual variability?. European Journal of Nutrition, 59, 1275-1293.
  3. Noerman S, Kärkkäinen O, Mattsson A, Paananen J, Lehtonen M, Nurmi T, Tuomainen TP, Voutilainen S, Hanhineva K, Virtanen J. (2019). Metabolic profiling of high egg consumption and the associated lower risk of type 2 diabetes in middle-aged Finnish men. Molecular Nutrition & Food Research, 63, 1800605.
  4. Kärkkäinen, O., Lankinen, M. A., Vitale, M., Jokkala, J., Leppänen, J., Koistinen, V., ... & Rivellese, A. A. (2018). Diets rich in whole grains increase betainized compounds associated with glucose metabolism. The American Journal of Clinical Nutrition, 108(5), 971-979.
  5. de Mello, V. D., Lankinen, M. A., Lindström, J., Puupponen-Pimiä, R., Laaksonen, D. E., Pihlajamäki, J., ... & Hanhineva, K. (2017). Fasting serum hippuric acid is elevated after bilberry (Vaccinium myrtillus) consumption and associates with improvement of fasting glucose levels and insulin secretion in persons at high risk of developing type 2 diabetes. Molecular Nutrition & Food Research, 61(9), 1700019.
  6. Tovar, J., de Mello, V. D., Nilsson, A., Johansson, M., Paananen, J., Lehtonen, M., ... & Björck, I. (2017). Reduction in cardiometabolic risk factors by a multifunctional diet is mediated via several branches of metabolism as evidenced by nontargeted metabolite profiling approach. Molecular Nutrition & Food Research, 61(2), 1600552.
  7. Bondia-Pons, I., Martinez, J. A., de la Iglesia, R., Lopez-Legarrea, P., Poutanen, K., Hanhineva, K., & Zulet, M. D. L. Á. (2015). Effects of short- and long-term Mediterranean-based dietary treatment on plasma LC-QTOF/MS metabolic profiling of subjects with metabolic syndrome features: The Metabolic Syndrome Reduction in Navarra (RESMENA) randomized controlled trial. Molecular Nutrition & Food Research, 59(4), 711-728.
  8. Hanhineva, K., Lankinen, M. A., Pedret, A., Schwab, U., Kolehmainen, M., Paananen, J., ... & Uusitupa, M. (2015). Nontargeted metabolite profiling discriminates diet-specific biomarkers for consumption of whole grains, fatty fish, and bilberries in a randomized controlled trial. The Journal of Nutrition, 145(1), 7-17.
  9. Hanhineva, K. (2015). Application of Metabolomics to Assess Effects of Controlled Dietary Interventions. Current Nutrition Reports, 4(4), 365-376.
  10. Hanhineva, K., Brunius, C., Andersson, A., Marklund, M., Juvonen, R., Keski‐Rahkonen, P., ... & Landberg, R. (2015). Discovery of urinary biomarkers of whole grain rye intake in free-living subjects using nontargeted LC-MS metabolite profiling. Molecular Nutrition & Food Research, 59(11), 2315-2325.
  11. Pekkinen, J., Rosa-Sibakov, N., Micard, V., Keski-Rahkonen, P., Lehtonen, M., Poutanen, K., ... & Hanhineva, K. (2015). Amino acid-derived betaines dominate as urinary markers for rye bran intake in mice fed high-fat diet—A nontargeted metabolomics study. Molecular Nutrition & Food Research, 59(8), 1550-1562.
  12. Hanhineva, K., Keski-Rahkonen, P., Lappi, J., Katina, K., Pekkinen, J., Savolainen, O., ... & Poutanen, K. (2014). The postprandial plasma rye fingerprint includes benzoxazinoid-derived phenylacetamide sulfates. The Journal of Nutrition, 144(7), 1016-1022.
  13. Pekkinen, J., Rosa, N. N., Savolainen, O. I., Keski-Rahkonen, P., Mykkänen, H., Poutanen, K., ... & Hanhineva, K. (2014). Disintegration of wheat aleurone structure has an impact on the bioavailability of phenolic compounds and other phytochemicals as evidenced by altered urinary metabolite profile of diet-induced obese mice. Nutrition & metabolism, 11(1), 1.
  14. Hanhineva, K., Barri, T., Kolehmainen, M., Pekkinen, J., Pihlajamäki, J., Vesterbacka, A., ... & Poutanen, K. (2013). Comparative nontargeted profiling of metabolic changes in tissues and biofluids in high-fat diet-fed Ossabaw pig. Journal of proteome research, 12(9), 3980-3992.
  15. Pekkinen, J., Olli, K., Huotari, A., Tiihonen, K., Keski-Rahkonen, P., Lehtonen, M., ... & Hanhineva, K. (2013). Betaine supplementation causes increase in carnitine metabolites in the muscle and liver of mice fed a high-fat diet as studied by nontargeted LC-MS metabolomics approach. Molecular Nutrition & Food Research, 57(11), 1959-1968.
  16. Bondia-Pons, I., Barri, T., Hanhineva, K., Juntunen, K., Dragsted, L. O., Mykkänen, H., & Poutanen, K. (2013). UPLC-QTOF/MS metabolic profiling unveils urinary changes in humans after a whole grain rye versus refined wheat bread intervention. Molecular Nutrition & Food Research, 57(3), 412-422.

Food

  1. Koistinen, V. M., Mattila, O., Katina, K., Poutanen, K., Aura, A. M., & Hanhineva, K. (2018). Metabolic profiling of sourdough fermented wheat and rye bread. Scientific Reports, 8(1), 1-11.
  2. Koistinen, V. M., Nordlund, E., Katina, K., Mattila, I., Poutanen, K., Hanhineva, K., & Aura, A. M. (2017). Effect of bioprocessing on the in vitro colonic microbial metabolism of phenolic acids from rye bran fortified breads. Journal of Agricultural and Food Chemistry, 65(9), 1854-1864.
  3. Kårlund, A., Hanhineva, K., Lehtonen, M., McDougall, G. J., Stewart, D., & Karjalainen, R. O. (2017). Non-targeted metabolite profiling highlights the potential of strawberry leaves as a resource for specific bioactive compounds. Journal of the Science of Food and Agriculture, 97(7), 2182-2190.
  4. Koistinen, V. M., & Hanhineva, K. (2017). Mass spectrometry-based analysis of whole-grain phytochemicals. Critical Reviews in Food Science and Nutrition, 57(8), 1688-1709.
  5. Koistinen, V. M., Katina, K., Nordlund, E., Poutanen, K., & Hanhineva, K. (2016). Changes in the phytochemical profile of rye bran induced by enzymatic bioprocessing and sourdough fermentation. Food Research International, 89, 1106-1115.
  6. Kårlund, A., Moor, U., McDougall, G., Lehtonen, M., Karjalainen, R. O., & Hanhineva, K. (2016). Metabolic profiling discriminates between strawberry (Fragaria × ananassa Duch.) cultivars grown in Finland or Estonia. Food Research International, 89, 647-653.
  7. Kårlund, A., Hanhineva, K., Lehtonen, M., Karjalainen, R. O., & Sandell, M. (2015). Nontargeted metabolite profiles and sensory properties of strawberry cultivars grown both organically and conventionally. Journal of Agricultural and Food Chemistry, 63(3), 1010-1019.
  8. Savolainen, O., Pekkinen, J., Katina, K., Poutanen, K., & Hanhineva, K. (2015). Glycosylated benzoxazinoids are degraded during fermentation of wheat bran. Journal of Agricultural and Food Chemistry, 63(25), 5943-5949.
  9. Bondia-Pons, I., Savolainen, O., Törrönen, R., Martinez, J. A., Poutanen, K., & Hanhineva, K. (2014). Metabolic profiling of Goji berry extracts for discrimination of geographical origin by non-targeted liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. Food Research International, 63, 132-138.
  10. Savolainen, O. I., Coda, R., Suomi, K., Katina, K., Juvonen, R., Hanhineva, K., & Poutanen, K. (2014). The role of oxygen in the liquid fermentation of wheat bran. Food Chemistry, 153, 424-431.
  11. Hanhineva, K., Rogachev, I., Aura, A. M., Aharoni, A., Poutanen, K., & Mykkänen, H. (2012). Identification of novel lignans in the whole grain rye bran by non-targeted LC–MS metabolite profiling. Metabolomics, 8(3), 399-409.
  12. Hanhineva, K., Rogachev, I., Aura, A. M., Aharoni, A., Poutanen, K., & Mykkänen, H. (2011). Qualitative characterization of benzoxazinoid derivatives in whole grain rye and wheat by LC-MS metabolite profiling. Journal of Agricultural and Food Chemistry, 59(3), 921-927.
  13. Hanhineva, K., Kokko, H., Siljanen, H., Rogachev, I., Aharoni, A., & Kärenlampi, S. O. (2009). Stilbene synthase gene transfer caused alterations in the phenylpropanoid metabolism of transgenic strawberry (Fragaria × ananassa). Journal of Experimental Botany, 60(7), 2093-2106.
  14. Hanhineva, K., Soininen, P., Anttonen, M. J., Kokko, H., Rogachev, I., Aharoni, A., ... & Kärenlampi, S. (2009). NMR and UPLC-qTOF-MS/MS characterisation of novel phenylethanol derivatives of phenylpropanoid glucosides from the leaves of strawberry (Fragaria × ananassa cv. Jonsok). Phytochemical Analysis, 20(5), 353-364.
  15. Fait, A.*, Hanhineva, K.*, Beleggia, R., Dai, N., Rogachev, I., Nikiforova, V. J., ... & Aharoni, A. (2008). Reconfiguration of the achene and receptacle metabolic networks during strawberry fruit development. Plant Physiology, 148(2), 730-750. *Equal contribution.
  16. Hanhineva, K., Rogachev, I., Kokko, H., Mintz-Oron, S., Venger, I., Kärenlampi, S., & Aharoni, A. (2008). Non-targeted analysis of spatial metabolite composition in strawberry (Fragaria × ananassa) flowers. Phytochemistry, 69(13), 2463-2481.

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Afekta Technologies Ltd.
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PL 1199
70210 Kuopio, Finland
info@afekta.com
+358 44 243 2322