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1. Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

Author

Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B., De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E. Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W., Schwenk, Jochen M., Adamski, Jerzy, McCarthy, Mark I., Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, Brunak, Søren, Froguel, Philippe, Thomas, Cecilia Engel, Häussler, Ragna S., Beulens, Joline, Rutters, Femke, Nijpels, Giel, van Oort, Sabine, Groeneveld, Lenka, Elders, Petra, Giorgino, Toni, Rodriquez, Marianne, Nice, Rachel, Perry, Mandy, Bianzano, Susanna, Graefe-Mody, Ulrike, Hennige, Anita, Grempler, Rolf, Baum, Patrick, Stærfeldt, Hans Henrik, Shah, Nisha, Teare, Harriet, Ehrhardt, Beate, Tillner, Joachim, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinevich, Iryna, Cabrelli, Louise, Loftus, Heather, Bizzotto, Roberto, Tura, Andrea, Dekkers, Koen, Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B., De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E. Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W., Schwenk, Jochen M., Adamski, Jerzy, McCarthy, Mark I., Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, Brunak, Søren, Froguel, Philippe, Thomas, Cecilia Engel, Häussler, Ragna S., Beulens, Joline, Rutters, Femke, Nijpels, Giel, van Oort, Sabine, Groeneveld, Lenka, Elders, Petra, Giorgino, Toni, Rodriquez, Marianne, Nice, Rachel, Perry, Mandy, Bianzano, Susanna, Graefe-Mody, Ulrike, Hennige, Anita, Grempler, Rolf, Baum, Patrick, Stærfeldt, Hans Henrik, Shah, Nisha, Teare, Harriet, Ehrhardt, Beate, Tillner, Joachim, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinevich, Iryna, Cabrelli, Louise, Loftus, Heather, Bizzotto, Roberto, Tura, Andrea, and Dekkers, Koen

Abstract

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug–omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug–drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities., Correction in DOI 10.1038/s41587-023-01805-9QC 20230626

Published
2023
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2. Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits

Author

Brown, Andrew A., Fernandez-Tajes, Juan J., Hong, Mun gwan, Brorsson, Caroline A., Koivula, Robert W., Davtian, David, Dupuis, Théo, Sartori, Ambra, Michalettou, Theodora Dafni, Forgie, Ian M., Adam, Jonathan, Allin, Kristine H., Caiazzo, Robert, Cederberg, Henna, De Masi, Federico, Elders, Petra J.M., Giordano, Giuseppe N., Haid, Mark, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew T., Heggie, Alison J., Howald, Cédric, Jones, Angus G., Kokkola, Tarja, Laakso, Markku, Mahajan, Anubha, Mari, Andrea, McDonald, Timothy J., McEvoy, Donna, Mourby, Miranda, Musholt, Petra B., Nilsson, Birgitte, Pattou, Francois, Penet, Deborah, Raverdy, Violeta, Ridderstråle, Martin, Romano, Luciana, Rutters, Femke, Sharma, Sapna, Teare, Harriet, ‘t Hart, Leen, Tsirigos, Konstantinos D., Vangipurapu, Jagadish, Vestergaard, Henrik, Brunak, Søren, Franks, Paul W., Frost, Gary, Grallert, Harald, Jablonka, Bernd, McCarthy, Mark I., Pavo, Imre, Pedersen, Oluf, Ruetten, Hartmut, Walker, Mark, Adragni, Kofi, Allesøe, Rosa Lundbye L., Artati, Anna A., Arumugam, Manimozhiyan, Atabaki-Pasdar, Naeimeh, Baltauss, Tania, Banasik, Karina, Barnett, Anna L., Baum, Patrick, Bell, Jimmy D., Beulens, Joline W., Bianzano, Susanna B., Bizzotto, Roberto, Bonnefond, Amelie, Cabrelli, Louise, Dale, Matilda, Dawed, Adem Y., de Preville, Nathalie, Dekkers, Koen F., Deshmukh, Harshal A., Dings, Christiane, Donnelly, Louise, Dutta, Avirup, Ehrhardt, Beate, Engelbrechtsen, Line, Eriksen, Rebeca, Fan, Yong, Ferrer, Jorge, Fitipaldi, Hugo, Forman, Annemette, Fritsche, Andreas, Froguel, Philippe, Gassenhuber, Johann, Gough, Stephen, Graefe-Mody, Ulrike, Grempler, Rolf, Groeneveld, Lenka, Groop, Leif, Gudmundsdóttir, Valborg, Gupta, Ramneek, Hennige, Anita M.H., Hill, Anita V., Holl, Reinhard W., Hudson, Michelle, Jacobsen, Ulrik Plesner, Jennison, Christopher, Johansen, Joachim, Jonsson, Anna, Karaderi, Tugce, Kaye, Jane, Kennedy, Gwen, Klintenberg, Maria, Kuulasmaa, Teemu, Lehr, Thorsten, Loftus, Heather, Lundgaard, Agnete Troen T., Mazzoni, Gianluca, McRobert, Nicky, McVittie, Ian, Nice, Rachel, Nicolay, Claudia, Nijpels, Giel, Palmer, Colin N., Pedersen, Helle K., Perry, Mandy H., Pomares-Millan, Hugo, Prehn, Cornelia P., Ramisch, Anna, Rasmussen, Simon, Robertson, Neil, Rodriquez, Marianne, Sackett, Peter, Scherer, Nina, Shah, Nisha, Sihinevich, Iryna, Slieker, Roderick C., Sondertoft, Nadja B., Steckel-Hamann, Birgit, Thomas, Melissa K., Thomas, Cecilia Engel E., Thomas, Elizabeth Louise L., Thorand, Barbara, Thorne, Claire E., Tillner, Joachim, Tura, Andrea, Uhlen, Mathias, van Leeuwen, Nienke, van Oort, Sabine, Verkindt, Helene, Vogt, Josef, Wad Sackett, Peter W., Wesolowska-Andersen, Agata, Whitcher, Brandon, White, Margaret W., Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., Viñuela, Ana, Brown, Andrew A., Fernandez-Tajes, Juan J., Hong, Mun gwan, Brorsson, Caroline A., Koivula, Robert W., Davtian, David, Dupuis, Théo, Sartori, Ambra, Michalettou, Theodora Dafni, Forgie, Ian M., Adam, Jonathan, Allin, Kristine H., Caiazzo, Robert, Cederberg, Henna, De Masi, Federico, Elders, Petra J.M., Giordano, Giuseppe N., Haid, Mark, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew T., Heggie, Alison J., Howald, Cédric, Jones, Angus G., Kokkola, Tarja, Laakso, Markku, Mahajan, Anubha, Mari, Andrea, McDonald, Timothy J., McEvoy, Donna, Mourby, Miranda, Musholt, Petra B., Nilsson, Birgitte, Pattou, Francois, Penet, Deborah, Raverdy, Violeta, Ridderstråle, Martin, Romano, Luciana, Rutters, Femke, Sharma, Sapna, Teare, Harriet, ‘t Hart, Leen, Tsirigos, Konstantinos D., Vangipurapu, Jagadish, Vestergaard, Henrik, Brunak, Søren, Franks, Paul W., Frost, Gary, Grallert, Harald, Jablonka, Bernd, McCarthy, Mark I., Pavo, Imre, Pedersen, Oluf, Ruetten, Hartmut, Walker, Mark, Adragni, Kofi, Allesøe, Rosa Lundbye L., Artati, Anna A., Arumugam, Manimozhiyan, Atabaki-Pasdar, Naeimeh, Baltauss, Tania, Banasik, Karina, Barnett, Anna L., Baum, Patrick, Bell, Jimmy D., Beulens, Joline W., Bianzano, Susanna B., Bizzotto, Roberto, Bonnefond, Amelie, Cabrelli, Louise, Dale, Matilda, Dawed, Adem Y., de Preville, Nathalie, Dekkers, Koen F., Deshmukh, Harshal A., Dings, Christiane, Donnelly, Louise, Dutta, Avirup, Ehrhardt, Beate, Engelbrechtsen, Line, Eriksen, Rebeca, Fan, Yong, Ferrer, Jorge, Fitipaldi, Hugo, Forman, Annemette, Fritsche, Andreas, Froguel, Philippe, Gassenhuber, Johann, Gough, Stephen, Graefe-Mody, Ulrike, Grempler, Rolf, Groeneveld, Lenka, Groop, Leif, Gudmundsdóttir, Valborg, Gupta, Ramneek, Hennige, Anita M.H., Hill, Anita V., Holl, Reinhard W., Hudson, Michelle, Jacobsen, Ulrik Plesner, Jennison, Christopher, Johansen, Joachim, Jonsson, Anna, Karaderi, Tugce, Kaye, Jane, Kennedy, Gwen, Klintenberg, Maria, Kuulasmaa, Teemu, Lehr, Thorsten, Loftus, Heather, Lundgaard, Agnete Troen T., Mazzoni, Gianluca, McRobert, Nicky, McVittie, Ian, Nice, Rachel, Nicolay, Claudia, Nijpels, Giel, Palmer, Colin N., Pedersen, Helle K., Perry, Mandy H., Pomares-Millan, Hugo, Prehn, Cornelia P., Ramisch, Anna, Rasmussen, Simon, Robertson, Neil, Rodriquez, Marianne, Sackett, Peter, Scherer, Nina, Shah, Nisha, Sihinevich, Iryna, Slieker, Roderick C., Sondertoft, Nadja B., Steckel-Hamann, Birgit, Thomas, Melissa K., Thomas, Cecilia Engel E., Thomas, Elizabeth Louise L., Thorand, Barbara, Thorne, Claire E., Tillner, Joachim, Tura, Andrea, Uhlen, Mathias, van Leeuwen, Nienke, van Oort, Sabine, Verkindt, Helene, Vogt, Josef, Wad Sackett, Peter W., Wesolowska-Andersen, Agata, Whitcher, Brandon, White, Margaret W., Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., and Viñuela, Ana

Abstract

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Published
2023

9. Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration

Author

Wilman, Henry R., Parisinos, Constantinos A., Atabaki-Pasdar, Naeimeh, Kelly, Matt, Thomas, E. Louise, Neubauer, Stefan, Jennison, Christopher, Ehrhardt, Beate, Baum, Patrick, Schoelsch, Corinna, Freijer, Jan, Grempler, Rolf, Graefe-Mody, Ulrike, Hennige, Anita, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinecich, Iryna, Pattou, Francois, Raverdi, Violeta, Caiazzo, Robert, Torres, Fanelly, Verkindt, Helene, Mari, Andrea, Tura, Andrea, Giorgino, Toni, Bizzotto, Froguel, Philippe, Bonneford, Amelie, Canouil, Mickael, Dhennin, Veronique, Brorsson, Caroline, Brunak, Soren, de Masi, Federico, Gudmundsdóttir, Valborg, Pedersen, Helle, Banasik, Karina, Thomas, Cecilia, Sackett, Peter, Staerfeldt, Hans-Henrik, Lundgaard, Agnete, Koopman, Anitra, Rutters, Femke, Beulens, Joline, Groeneveld, Lenka, Thomas, Louise, Whitcher, Brandon, Mahajan, Anubha, Hingorani, Aroon D., Patel, Riyaz S., Hemingway, Harry, Franks, Paul W., Bell, Jimmy D., Banerjee, Rajarshi, Yaghootkar, Hanieh, Epidemiology and Data Science, APH - Health Behaviors & Chronic Diseases, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, and APH - Aging & Later Life

Abstract

Background & Aims: Excess liver iron content is common and is linked to the risk of hepatic and extrahepatic diseases. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. Methods: First, we performed a genome-wide association study (GWAS) in 8,289 individuals from UK Biobank, whose liver iron level had been quantified by magnetic resonance imaging, before validating our findings in an independent cohort (n = 1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 25 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 traits and disease outcomes. Results: We identified 3 independent genetic variants (rs1800562 [C282Y] and rs1799945 [H63D] in HFE and rs855791 [V736A] in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p

Published
2019
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11. The Novel, Potent, and Selective DPP-IV Inhibitor BI 1356 Significantly Lowers HbA1c after only 4 Weeks of Treatment in Patients with Type 2 Diabetes.

Author

Forst, Thomas, Uhlig-Laske, Barbara, Ring, Arne, Ritzhaupt, Armin, Graefe-Mody, Ulrike, and Dugi, Klaus A.

Subjects
HYPOGLYCEMIC agents, DRUG tolerance, TYPE 2 diabetes, BLOOD sugar, GLUCAGON
Abstract

BI 1356 is a novel, potent, selective, and long acting DPP-IV inhibitor in development for type 2 diabetes. The safety and tolerability of 2.5, 5 and 10 mg BI 1356 administered once daily for 28 days was investigated in a randomised, double-blind, placebo controlled, multiple dose study in 77 male and female patients with type 2 diabetes aged 40 to 69 years. The effect of BI 1356 on glycaemic control was also explored. Before treatment, patients entered a 14-day washout period of previous medication. A meal tolerance test (MTT) was performed on days -1, 1, and 29 together with measurements of glucose, GLP-1 and glucagon. The effect on HbA1c reduction was explored using an ANOVA model. Treatment with BI 1356 was well tolerated. Five patients (5/16, 31%) treated with placebo and 21 patients (21/61, 34%) treated with BI 1356 experienced at least one adverse event (AE). Most AEs were mild in intensity. Nasopharyngitis and back pain (5 patients each), and upper abdominal pain and headache (3 patients each) were the most common AEs. The incidence of nasopharyngitis and back pain was comparable between placebo and BI 1356. None of the patients experienced symptoms of hypoglycaemia. Safety laboratory parameters were stable relative to baseline. After 4 weeks of treatment with BI 1356, GLP-1 levels increased up to 4-fold and glucagon concentrations were reduced by up to 24%. Compared to baseline, glucose levels were significantly reduced after the MTT by up to 105 mg⋅h/dL depending on dose. Despite the short treatment duration, the small group sizes (n = 16-26), and a low mean baseline HbA1c of 7.0%, a significant (one-sided at p<0.025) placebo-corrected mean change in HbA1c of -0.31%, -0.37%, and -0.28% was observed for the 2.5, 5, and 10 mg dose groups, respectively. In summary, treatment of type 2 diabetic patients with BI 1356 was well tolerated and safe, and resulted in a statistically significant reduction of HbA1c after only 4 weeks of treatment. [ABSTRACT FROM AUTHOR]

Published
2007

12. BI 1356, a Novel and Selective Xanthine Based DPP-IV Inhibitor, Demonstrates Good Safety and Tolerability with a Wide Therapeutic Window.

Author

Huettner, Silke, Graefe-Mody, Ulrike, Ring, Arne, Ritzhaupt, Armin, and Dugi, Klaus A.

Subjects
*XANTHINE, *BLOOD sugar monitoring, *PLACEBOS, *DRUG side effects, *DRUG tolerance
Abstract

BI 1356 is a xanthine analogue which exhibits a high potency for DPP-IV inhibition, increases the half-life of circulating incretin hormones, and improves glucose homeostasis in preclinical studies. In a randomised, double-blind, placebo controlled single rising dose study in healthy male volunteers aged 21-65 years, BI 1356 was administered at doses ranging from 2.5 to 600 mg once daily to investigate safety, tolerability, pharmacokinetics, and pharmacodynamics. BI 1356 was well tolerated. There were no serious adverse events and no hypoglycaemic episodes. The Incidence of any adverse event (ALE) (28% for BI 1356, 38% for placebo) or of drug related AEs (19% vs. 31%) was not higher for BI 1356 compared to placebo. The most common AEs reported were headache, influenza-like illness and nausea with an incidence comparable between BI 1356 and placebo. No clinically relevant deviations in laboratory parameters (haematology, coagulation, clinical chemistry, and urinalysis) were reported. ECGs were centrally evaluated by a specialised provider and did not show any clinically relevant deviations or any indication of a QT prolonging effect up to and including the 600 mg dose. The exposure of BI 1356 increased Jess than proportionally from 2.5 to 5 mg, while C[sub max] and AUC increased more than proportionally from 25 to 100 mg and approximately proportionally for doses ranging from 100 to 600 mg. Renal excretion was low and does not constitute the main pathway for elimination of BI 1356. After single doses of 2.5 mg and 5 mg BI 1356, DPP-IV activity was reduced by 73% and 86% within 3 h, respectively. Twenty-four h after administration of 25-600 mg BI 1356, mean plasma DPP-IV inhibition was greater than 90%. In summary, BI 1356 was well tolerated and safe. The results of the pharmacokinetic and pharmacodynamic profile after single doses demonstrate the potency and full 24 h duration of action of BI 1356. Based on an estimated therapeutic dose of 5 mg, the therapeutic window of BI 1356 is expected to be >100 fold. [ABSTRACT FROM AUTHOR]

Published
2007

13. Treatment with BI 1356, a Novel and Potent DPP-IV Inhibitor, Significantly Reduces Glucose Excursions after an oGTT in Patients with Type 2 Diabetes.

Author

Heise, Tim, Tiessen, Renger, Huettner, Silke, Ring, Arne, Ritzhaupt, Armin, Graefe-Mody, Ulrike, and Dugi, Klaus A.

Subjects
INSULIN synthesis inhibitors, TYPE 2 diabetes, PHARMACOKINETICS, PHARMACODYNAMICS, DRUG side effects
Abstract

BI 1356 is a novel, potent, and selective DPP-IV inhibitor currently in development for type 2 diabetes. The safety, pharmacokinetics, and pharmacodynamic properties of BI 1356 were investigated in a randomised, double-blind, placebo-controlled study in patients with type 2 diabetes. Forty-seven male type 2 diabetic patients, aged 21-65 and with a BMI of 18-35 kg/m², were treated once daily with 1, 2.5, 5, or 10 mg BI 1356, or placebo for 12 days. Treatment with BI 1356 was well tolerated. The incidence of adverse events in patients treated with BI 1356 (54%) was not higher when compared to placebo (75%). There were no serious adverse events and no episodes of hypoglycaemia. BI 1356 plasma concentrations and exposure increased less than proportionally with dose. The maximum plasma concentrations of BI 1356 at steady-state ranged from 4.5 nmol/L (1 mg dose group) to 13.6 nmol/L (10 mg), with a median t[sub max] of 1.5 h. Reductions in plasma DPP-IV activity were well correlated with plasma concentrations of BI 1356. Two hours after administration of 2.5 mg BI 1356, DPP-IV activity was reduced by >80% and remained at that level at steady-state. Levels of GLP-1 were increased by more than 2-fold. Following an oGTT on day 13, 24 h after the last dose of BI 1356, area under the plasma glucose excursions were reduced by 53 (1 mg BI 1356), 106 (2.5 mg), 82 (5 mg), 111 (10 mg), and 25 (placebo) mg.h/dL, respectively. Despite the small group sizes, these reductions reached statistical significance for 2.5, 5, and 10 mg BI 1356 compared to baseline and compared to placebo (p<0.05 for both). In summary, 24 h after the last dose, DPP-IV inhibition was >70% after administration of BI 1356 doses of > 1 mg, and significant improvements in glucose parameters were observed in patients with type 2 diabetes. Given this potency and duration of action, BI 1356 has the potential to be a best in class DPP-IV inhibitor. [ABSTRACT FROM AUTHOR]

Published
2007

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