There are 11 clinical trials
Increasing evidence attests the influence of multiple metabolic genetic risk factors in the progression of alcoholic liver disease. Deleterious pathways involved in metabolism such as lipid peroxidation and cytokines have been implicated in promoting inflammation leading to fibrosis increase and liver injury progression. The aim of this study was to assess the role of rs738409 single nucleotide polymorphism in the PNPLA3 gene in alcoholic liver disease patients.
The aim of this study was to assess the role of rs738409 single nucleotide polymorphism in the PNPLA3 gene in alcoholic liver disease patients.
After liver histology assessment for liver liver dammage a potential correlation of fibrosis and steatosis was studied with rs738409 PNPLA3 polymorphism.
Description: After liver histology assessment for liver liver dammage a potential correlation of fibrosis and steatosis was studied with rs738409 PNPLA3 polymorphism
Measure: Assessment of fibrosis and steatosis by liver biopsy in alcoholic liver disease patients.To explore whether there is a different response to omega-3 fatty acid rich diet with respect to the hepatic fat fraction % (HFF), triglyceride, and ALT levels between the rs738409 minor allele (GG) and the common allele homozygous (CC) of PNPLA3. Hypothesis: We expect that subjects homozygous for the minor allele of the rs73049 SNP will lower their triglyceride, hepatic fat content, and ALT levels more with dietary intervention than the common allele homozygous supplementation.
Genetic Effect on Omega 3 Fatty Acids for the Treatment of Fatty Liver Disease To explore whether there is a different response to omega-3 fatty acid rich diet with respect to the hepatic fat fraction % (HFF), triglyceride, and ALT levels between the rs738409 minor allele (GG) and the common allele homozygous (CC) of PNPLA3.
Description: subjects follow study designed meal plan
Measure: reduction in hepatic fat fraction Time: 12 weeksDescription: subjects follow study designed meal plan
Measure: reduction in triglycerides Time: 12 weeksDescription: subjects follow study designed meal plan
Measure: lower ALT levels Time: 12 weeksA. BACKGROUND Accumulation of fat in the liver due to non-alcoholic causes (NAFLD) is associated with hepatic insulin resistance, which impairs the ability of insulin to inhibit the production of glucose and VLDL . This leads to increases in serum glucose, insulin and triglyceride concentrations as well as hyperinsulinemia. Recent epidemiologic studies have shown that a major reason for the metabolic syndrome as well as the accompanying increased risk of cardiovascular disease and type 2 diabetes is overconsumption of simple sugars. The investigators have recently shown that overeating simple sugars (1000 extra calories/day, "CANDY" diet) increases liver fat content by 30% within 3 weeks (4), and recapitulates features of the metabolic syndrome such as hypertriglyceridemia and a low HDL cholesterol concentration. The fatty acids in intrahepatocellular triglycerides may originate from peripheral lipolysis, de novo lipogenesis, uptake of chylomicron remnants by the liver and from hepatic uptake of fatty acids released during intravascular hydrolysis of triglyceride-rich lipoproteins (the spillover pathway). A classic study using stable isotope methodology by the group of Elisabeth Parks showed that in subjects with NAFLD, the excess intrahepatocellular triglycerides originate from peripheral lipolysis and de novo lipogenesis. It is well-established that ingestion of a high carbohydrate as compared to high fat diet stimulates de novo lipogenesis in humans. Meta-analyses comparing isocaloric high fat and high carbohydrate diets have shown that high carbohydrate but not high fat diets increase increase serum triglycerides and lower HDL cholesterol. Since hypertriglyceridemia results from overproduction of VLDL from the liver, these data suggest the composition of the diet influences hepatic lipid metabolism. Whether this is because overfeeding fat leads to preferential deposition of fat in adipose tissue while high carbohydrate diets induce a relative greater increase in liver fat is unknown. There are no previous studies comparing effects of chronic overfeeding of fat as compared to carbohydrate on liver fat or and the sources of intrahepatic fatty acids. A common polymorphism in PNPLA3 at rs738409 (adiponutrin) gene is associated with a markedly increase liver fat content. This finding has been replicated in at least 20 studies across the world. The investigators have shown that PNPLA3 is regulated by the carbohydrate response element binding protein 1. Mice overexpressing the human I148M PNPLA3 variant in the liver exhibit an increase in liver triglycerides and cholesteryl esters on a high sucrose but not high fat diet. These data suggest that overfeeding a high carbohydrate as compared to a high fat diet may increase liver fat more in subjects carrying the I148M allele than in non-carriers. B. HYPOTHESIS The investigators hypothesize that overfeeding a high fat as compared to an isocaloric high carbohydrate diet influences the source of intrahepatocellular triglycerides. During a high fat diet, relatively more of intrahepatocellular triglycerides originate from peripheral lipolysis and less from DNL than during a high carbohydrate diet in the face of a similar increase in liver fat. It is also possible given the lack of previous overfeeding data comparing 2 different overfeeding diets that the high fat diet induces a smaller increase in liver fat than a high carbohydrate diet even in the face of an identical increase in caloric intake because a greater fraction of ingested fat is channeled to adipose tissue than the liver. The investigators also hypothesize that liver fat may increase more in carriers than non-carriers of the I148M variant in PNPLA3 during a high carbohydrate than a high fat diet. C. SPECIFIC AIMS The investigators wish to randomize, using the method of minimization (considers baseline age, BMI, gender, liver fat, PNPLA3 genotype) 40 non-diabetic subjects with NAFLD as determined by the non-invasive score developed in our laboratory or previous knowledge of liver fat content based on MRS to overeat either a high carbohydrate or high fat diet (1000 extra calories per day) for 3 weeks. Before and after the overfeeding diets, will measure liver fat content by 1H-MRS and the rate of adipose tissue lipolysis using doubly labeled water (DDW) and [1,1,2,3,3-2H5] glycerol as described in detail below. The investigators also wish to characterize glucose, insulin, fatty acid and triacylglyceride profiles before and while on the experimental diet. An adipose tissue biopsy is taken to determine whether expression of genes involved in lipogenesis or lipolysis, or those involved in adipose tissue inflammation change in response to overfeeding, and for measurement of LPL activity. After overfeeding, both groups will undergo weight loss to restore normal weight as described in our recent study. The metabolic study is repeated after weight loss.
A common polymorphism in PNPLA3 at rs738409 (adiponutrin) gene is associated with a markedly increase liver fat content.
Description: the rate of DNL and adipose tissue lipolysis is measured using doubly labeled water (DDW) and [1,1,2,3,3-2H5] glycerol
Measure: De novo lipogenesis (DNL) and measurement of lipolysis Time: 3 weeksDescription: Laboratory tests including fasting glucose, insulin, C-peptide, liver enzymes, total, LDL and HDL cholesterol and TG concentrations PNPLA3 genotyping is performed also
Measure: Analytical procedures Time: 3 weeksDescription: Needle biopsies of abdominal subcutaneus tissue will be taken for subsequent isolation of RNA for measurements of gene expression (by quantitative PCR). Fat cell size is also measured.
Measure: Biopsies and analysis of subcutaneus adipose tissue Time: 3 weeksDescription: Indirect calorimetry is the method by which metabolic rate is estimated from measurements of oxygen (O2) consumption and carbon dioxide (CO2) production.
Measure: Indirect calorimetry Time: 3 weekNon-alcoholic fatty liver disease (NAFLD) is a common disorder, affecting ~30% of people in the general population and up to 96% of obese individuals. Variations in several genes have been found to be associated with fatty liver, but these associations only explain a small percentage of the risk, and further studies are needed. In many cases NAFLD does not cause serious side effects, but in some individuals it progresses to scarring or hardening of the liver, liver failure, and cancer. The purpose of this research study is to determine if individuals who carry certain genetic variations in a gene related to bile and choline metabolism have an increased risk of fatty liver progressing to fibrosis, or scarring of the liver. This study will also use a new, non-invasive method called the FibroScan® to measure liver fat and liver stiffness. The FibroScan® device is FDA approved for use to measure liver stiffness, but not for the liver fat measurement. However, the FibroScan® instrument is considered a non-significant risk device. Since its induction in Europe and worldwide in 2003, there have been no adverse effects reported with this device.
As additional proof of principle that the measurements we are making correlate with genetics, the investigators will also measure two genetic variants that have been shown in many studies to correlate with liver fat and fibrosis by their research team and others: PNPLA3 rs738409 and rs2281135.
Description: Measured by FibroScan® instrument
Measure: Liver stiffness measurement via transient elastography Time: Study Day 1Description: Measured using FibroScan® instrument
Measure: Liver fat measurement via Controlled Attenuation Parameter Time: Study Day 1Description: This is a calculated score which is a good predictor of liver disease
Measure: NAFLD-Fibrosis score Time: Study Day 1The present study investigates relationship between non-alcoholic fatty liver disease and its risk factors, such as genetic background and diseases, such as chronic kidney disease and diabetes mellitus.
In case of patatin-like phospholipase domain-containing protein 3 gene (PNPLA3) : rs738409, rs2281135, rs2294918 single nuclear polimorfism (SNP) will be examined.
Description: The association of hepatic steatosis with chronic kidney disease, diabetes mellitus and the the persence of these two will be assessed
Measure: Association of NFS (NAFLD fibrosis score) and HSI (hepatic steatosis index) with underlying conditions Time: 2 yearsDescription: The association of hepatic steatosis with genetic factors will be assessed. In case of patatin-like phospholipase domain-containing protein 3 gene (PNPLA3) : rs738409, rs2281135, rs2294918 single nuclear polimorfism (SNP) will be examined
Measure: Association of genetical factors with NFS and HSI Time: 2 yearsDescription: The association of serum creatinine, eGFR, blood urea nitrogen, serum sodium, serum potassium, serum calcium with NFS and HSI will be assessed
Measure: Association of hepatic steatosis with renal function Time: 2 yearsDescription: Association of HbA1C, fructosamine, blood glucose, serum insulin, HOMAIR, serum uric acid with NFS and HSI
Measure: Association of glucose metabolism parameters with hepaic steatosis indices Time: 2 yearsDescription: Association of serum bilirubine, serum GOT, serum GPT, serum GGT, serum ALP, serum LDH, INR, serum total protein, serum albumin with NFS and HSI
Measure: Association of liver function and hepatic setatosis indices Time: 2 yearsDescription: Association of serum total cholesterol, serum HDL-cholesterol, serum LDL-cholesterol, serum triglyceride, serum carnitine with NFS and HSI
Measure: Association of serum lipid profile and hepatic setatosis indices Time: 2 yearsDescription: association of serum iron, serum transferrine, serum transferrine saturation, serum ferritine with NFS and HSI
Measure: Association of iron metabolism parameters with hepatic setatosis indices Time: 2 yearsDescription: Association of blood count, erythrocyte sedimentation rate, CRP with NFS and HSI
Measure: The relationship between blood count, sedimentation and inflammation with hepatic setatosis indices Time: 2 yearsDescription: association of urinary total protein, urinary albumin, urinary total protein/creatinine ratio, urinary albumin/creatinine ratio with NFS and HSI
Measure: Assotion of serum proteins with hepatic setatosis indices Time: 2 yearsDescription: Association of serum meta-Tyr, serum ortho-Tyr, urinary meta-Tyr, urinary ortho-Tyr, urinary meta-Tyr/creatinine ratio, urinary ortho-Tyr/creatinine ratio with NFS and HSI
Measure: Association of pathological tyrosine isoforms with hepatic setatosis indices Time: 2 yearsNonalcoholic fatty liver disease (NAFLD) is frequently associated with obesity. NAFLD genetic susceptibility involves Patatin Like Phospholipase Domain Containing 3 (PNPLA3) rs738409 and Transmembrane 6 Superfamily Member 2 (TM6SF2) rs58542926 polymorphisms. To date, biochemical mechanisms that affect the "metabolic flexibility" in obese NAFLD subjects, in presence or absence of genetic susceptibility, need to be better clarified. Different studies demonstrated that a dietary intervention, accompanied by a physical personalized training, significantly reduce either the hepatic fat content either insulin resistance in overweight and obese subjects, independently of weight loss. On these bases, the aim of the study is to evaluate "metabolic flexibility" in obese NAFLD subjects taking in account their genetics (presence or absence of PNPLA3 and TM6SF2 polymorphisms) and the histopathological diagnosis of either simple steatosis or nonalcoholic steatohepatitis (NASH). In addition, the composition of gut microbiota will be evaluated. Finally, in this study, two distinct healthy dietary profiles accompanied by a personalized physical training, will be tested in order to comprehend whether and how "healthy diets" could be effective not only in the prevention, but also in the clinical treatment of NAFLD and other related conditions.
NAFLD genetic susceptibility involves Patatin Like Phospholipase Domain Containing 3 (PNPLA3) rs738409 and Transmembrane 6 Superfamily Member 2 (TM6SF2) rs58542926 polymorphisms.
The risk of cardiovascular disease is determined by the complex interplay between an individual's genetic make-up, lifestyle, and the environment. We are investigating three potential genetic risk factors in this observational, cross-sectional, epidemiology pilot study to investigate if and how functional variants identified in large-scale genome wide association studies can explain a predisposition to cardiovascular disease. By determining the molecular mechanisms that are regulated at the EDNRA, PNPLA3 and PROCR CVD risk loci, we hope to translate findings from this study into the clinical setting for better diagnosis, prevention and treatment for patients suffering with cardiovascular disease. Volunteers will enter into one of the study's three arms based on their genotype: EDNRA locus (Arm 1), PNPLA3 locus (Arm 2), or PROCR locus (Arm 3). Members of the Cambridge Bioresource who match for the target alleles will be invited to participate and will enter into one of the three study arms. All study assessment visits will take place at Addenbrooke's Hospital in collaboration with the University of Cambridge. Volunteers will participate in the study for a maximum of 12 months and depending on study arm they are assigned to, they will complete procedures including a medical, demographic and lifestyle factors questionnaire; height, weight and body fat assessments; in addition to blood pressure/heart rate measurements. Minimally invasive procedures including forearm blood flow and venepuncture will be performed to assess the primary objectives of the study. The hypothesis for arm 1 is that the genetic variant we are investigating at the EDNRA gene locus alters the function of the endothelin receptor A leading to an increased risk of coronary artery disease and large artery stroke. For study arm 2, we hypothesize that the genetic variant we are investigating in PNPLA3 will increase the risk of Non-alcoholic fatty liver disease but reduce the risk of Coronary Heart Disease. For study arm 3, we hypothesize that the genetic variant we are investigating in the PROCR locus triggers molecular events that potentially increase the risk of Venous Thrombosis/Venous Thromboembolism nut reducing blood pressure. Furthermore we aim to investigate the anti-inflammatory effects to see if there is an effect on explaining reduced risk of CHD. This study is funded from the BHF Cambridge Center of Excellence and the Wellcome Trust Institutional Strategic Support Fund.
If they are homozygous for the G-allele, they are assigned to the 'control' group - Arm 2: The G-allele of rs738409, they are assigned to the 'case' group.
Description: Arm 1 specific measurement to be measured using venous occlusion plethysmography. Outcome measure will compare results between case vs control groups.
Measure: Forearm Blood Flow (Arterial contractility) Time: 2 yearsDescription: Arm 2 specific measurement collectively comparing the lipid dynamic results between case vs control groups.
Measure: Blood Biochemistry (Lipoprotein composition/dynamics) Time: 2 yearsDescription: Arm 3 specific measurement comparing results between case vs control groups.
Measure: EPCR levels/shedding Time: 2 yearsDescription: Arm 3 specific measurement to be measured by platelet coagulation function assay comparing results between case vs control groups.
Measure: Platelet aggregation/function Time: 2 yearsDescription: Arm 3 specific measurement to be measured by an endothelial permeability assay comparing results between case vs control groups.
Measure: Endothelial permeability Time: 2 yearsDescription: Arm 3 specific measurement to be measured by a leukocyte-endothelium adhesion assay comparing results between case vs control groups.
Measure: Leukocyte-endothelium adhesion Time: 2 yearsDescription: All study arms comparing results between case vs control groups.
Measure: Blood pressure Time: 2 yearsDescription: All study arms comparing results between case vs control groups.
Measure: Heart rate Time: 2 yearsRaised blood cholesterol (also referred to as blood LDL-cholesterol) is a major risk factor for developing heart disease. Dietary saturated fat is recognised as the main dietary component responsible for raising blood LDL-cholesterol, and reducing its intake has been the mainstay of dietary guidelines for the prevention of heart disease for over 30 years. However, there is very little evidence for a direct link between the intake of saturated fat and risk of dying from heart disease. One explanation for this, is that the link between saturated fat intake and heart disease is not a direct one, but relies heavily on the ability of saturated fat to raise blood LDL-cholesterol levels. This LDL cholesterol-raising effect of saturated fat is complex, and highly variable between individuals because of differences in the metabolism of dietary fat and cholesterol between people. The main aim of this study is to measure the amount of variation in blood LDL-cholesterol in 150 healthy volunteers (75 at the University of Surrey and 75 at the University of Reading) in response to lowering the amount of saturated fat in the diet to the level recommended by the government for the prevention of heart disease. This collaborative project between the Universities of Reading, Surrey and Imperial ('RISSCI-1 Blood Cholesterol Response Study') will permit identification of two subgroups of men who show either a high or low LDL-cholesterol response to a reduction in dietary saturated intake. These participants (n=36) will be provided with an opportunity to participate in a similar follow-up study ('RISSCI-2') that will also take place at the University of Surrey and Reading. In this follow-up study, the participants will be asked to repeat a similar study protocol as for RISSCI-1, but undergo more detailed measurements to determine how saturated fat is metabolised in the body.
rs738409 C/G), eNOS.
Description: Polymorphic genes with potential influence on the serum LDL response to dietary saturated fat, e.g.: ATP-binding cassette proteins (cholesterol efflux proteins) ABCG5 (e.g. C1950G) ABCG8 (e.g. D19H, C1895T), functional polymorphisms in the farnesoid X receptor (FXR) and bile acid transporters (e.g. solute carrier organics anion 1B1). Fatty acid desaturases (FADS1 and FADS2). The patatin-like phospholipase domain-containing protein (PNPLA3) (e.g. rs738409 C/G), eNOS. Lipid/cholesterol homeostasis: serum apolipoprotein genes: APOE (ε2,ε3,ε4 e.g. rs429358 and rs7412), APOA-I (e.g. -75G/A), APOA4 (e.g. 360-2), APOA5 (e.g. -113/T>:c), APOCIII, APOB (e.g. -516C/T). Lipase genes: (e.g. LPL, HL, MGLL). Lipoprotein receptor genes (e.g. pvu11 in the LDL receptor), lipid transfer proteins (e.g. CETP e.g Taq1B, MTP), and other polymorphic genes related to the absorption and metabolism of dietary fat and regulation of lipid/cholesterol homeostasis.
Measure: Other relevant genes involved in the absorption and metabolism of dietary fat Time: BaselineDescription: Analyses conducted by Imperial College London
Measure: Metabolomic analysis for the determination of the low molecular weight metabolite profiles in the biological fluids Time: Baseline, 4 weeks (after diet 1), 8 weeks (after diet 2)Description: BMI will also be calculated (kg/ height in m^2)
Measure: Weight Time: Baseline, 4 weeks (after diet 1), 8 weeks (after diet 2)Description: Measured via pulse wave assessment using the Mobil-O-graph device.
Measure: Fasting vascular stiffness Time: baseline, 4 weeks (after diet 1), 8 weeks (after diet 2)Nonalcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease in the United States. The most advanced forms of NAFLD are associated with increased liver-related mortality and lower overall survival. The current standard of care for NAFLD is lifestyle changes through diet and exercise. The human genome and regulation of gene expression is influenced by physical activity. NAFLD is a prothrombotic state with derangements in all three phases of hemostasis leading to clinically important clotting events. Exercise can improve coagulation in healthy persons. In this proposal, we seek to begin a line of work to answer the question "Can lifestyle changes effectively mitigate the increased risk of clotting in patients with NAFLD?" focusing initially on the at-risk population genetically susceptible to advanced disease.
Patatin like phospholipase-3 (PNPLA3) rs738409 polymorphism.
Patatin like phospholipase-3 (PNPLA3) rs738409 polymorphism (GG, GC and CC genotypes) plays a crucial role in the development of NAFLD.
Description: The primary outcome of interest is change in fibrinolysis as measured by PAI-1 level immediately following completion of the exercise program.
Measure: PAI-1 level Time: 5 monthsDescription: hemostatic marker
Measure: Change in von williebrand factor (vWF) Time: 5 monthsDescription: hemostatic marker
Measure: change in p-selection Time: 5 monthsDescription: hemostatic marker
Measure: change in protein S Time: 5 monthsDescription: hemostatic marker
Measure: change in factor VIII Time: 5 monthsDescription: hemostatic marker
Measure: change in fibrinogen Time: 5 monthsDescription: hemostatic marker
Measure: change in antithrombin Time: 5 monthsDescription: hemostatic marker
Measure: change in protein C Time: 5 monthsDescription: fibrosis marker
Measure: change in adiponectin Time: 5 monthsDescription: genotyping subjects (GG, GC and CC genotypes)
Measure: Patatin like phospholipase-3 (PNPLA3) rs738409 polymorphism Time: 5 monthsDescription: hemostatic marker
Measure: Change in PAI-1 stratified by PNPLA3 genotype Time: 5 monthsDescription: measured by magnetic resonance imaging proton density fat fractionation (MRI-PDFF)
Measure: change in % hepatic fat Time: 5 monthsDescription: hemostatic markers
Measure: correlation between VO2 max and hemostatic markers Time: 5 monthsDescription: quality of life
Measure: health related quality of life (HRQOL) change Time: 5 monthsDescription: fibrosis
Measure: change in hepatic fibrosis stage Time: 5 monthsThis Phase 1, first-in-human (FiH), single-ascending-dose (SAD) study, will assess the safety and tolerability of AZD2693 and characterize the pharmacokinetics (PK) of AZD2693, following subcutaneous (SC) SAD administration of AZD2693 in male and female subjects of non -childbearing potential in 3 Populations: overweight but otherwise healthy subjects, healthy Chinese and Japanese subjects, and patients with NASH homozygous for the patatin-like phospholipase domain-containing protein 3 (PNPLA3) 148M Risk Allele
For those without MRE, a vibration-controlled transient elastography (VCTE) between 7.1 Kpa and 9.9 Kpa. - Homozygous for the PNPLA3 148M SNP rs738409 (PNPLA3 148 MM).
Description: To investigate the safety and tolerability of SC administration of single ascending doses of AZD2693
Measure: Number of subjects with adverse event and/or abnormal vital signs, laboratory and/or physical examination findings Time: From screening upto Week 16 (follow-up)Description: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Maximum observed plasma drug concentration (Cmax) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Time to reach maximum observed concentration following drug administration (tmax) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Apparent terminal elimination half-life associated with the terminal slope (λz) of the semi-logarithmic concentration-time curve, estimated as (ln2)/λz (t½λz) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Area under the plasma concentration-time curve from time zero to 48 hours after dosing [AUC(0-48h)] Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Area under the plasma concentration-curve from time zero to the time of last quantifiable analyte concentration (AUClast) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Area under the concentration-time curve from time zero extrapolated to infinity (AUC) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Apparent total body clearance of drug from plasma after extravascular administration calculated as Dose/AUC (CL/F) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Mean residence time (MRT) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Time delay between drug administration and the first observed concentration in plasma (tlag) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Apparent volume of distribution for parent drug at terminal phase (extravascular administration), estimated by dividing CL/F by λz (Vz/F) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Area under the plasma concentration-time curve from time zero to time of last quantifiable analyte concentration divided by the dose administered (AUClast/D) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Area under the plasma concentration-time curve from time zero extrapolated to infinity divided by the dose administered (AUC/D) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Observed maximum plasma concentration divided by the dose administered (Cmax/D) Time: At Day 1 Pre-dose, 0.25hours[h], 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 4h, 5h, 6h, 8h, 12h, 24h, 36h, 48h and 72h post-dose and 1, 2, 4, 8, 12 and 16 weeks post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Amount of analyte excreted into the urine from time t1 to t2 [Ae(t1-t2)] Time: At Pre-dose, 0-6hours[h], 6-12h and then 0-12h intervals up to 72h post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Cumulative amount of analyte excreted into the urine from time zero through the last sampling interval [Ae(0-last)] Time: At Pre-dose, 0-6hours[h], 6-12h and then 0-12h intervals up to 72h post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Fraction of dose excreted unchanged into the urine from time t1 to t2 [fe(t1-t2)] Time: At Pre-dose, 0-6hours[h], 6-12h and then 0-12h intervals up to 72h post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Cumulative fraction (%) of dose excreted unchanged into the urine from time zero to the last measured time point [fe(0-last)] Time: At Pre-dose, 0-6hours[h], 6-12h and then 0-12h intervals up to 72h post-doseDescription: To characterize the PK of AZD2693 following SC administration of SAD of AZD2693
Measure: Renal clearance of drug from plasma, estimated by dividing Ae(0-t) by AUC(0-t) where the 0-t interval is the same for both Ae and AUC [CLR] Time: At Pre-dose, 0-6hours[h], 6-12h and then 0-12h intervals up to 72h post-doseDescription: To assess the effect of AZD2693 on changes in LFC using magnetic resonance imaging based proton density fat fraction (MRI-PDFF) compared to placebo
Measure: Changes in liver fat content (LFC) from baseline assessment Time: At screening and follow-up visits on Weeks 4, 8 and 12 post-doseThis study is intended to investigate the safety and tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) of AZD2693, following subcutaneous (SC) administration of multiple ascending doses in patients with Non-alcoholic Steatohepatitis (NASH) with fibrosis Stage 1 to 3 and homozygous for the PNPLA3 148M risk allele.
- Participants who are homozygous for rs738409 (PNPLA3 148M).
Description: Safety and tolerability will be evaluated in terms of number of subjects with adverse events and/or abnormal values of vital signs and/or clinical laboratory and/or electrocardiogram and/or renal assessments and/or blood assessments.
Measure: Number of participants with adverse events Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on changes in LFC using magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) compared to placebo will be assessed. Samples will be taken under fasting conditions (10 h) in the morning at the same time (±1.5-2 h) during the day before lunch.
Measure: Absolute change from baseline to Week 8 and Week 12 in liver fat content (LFC) Time: Baseline (Day 1), Week 8, Week 12Description: The effect of AZD2693 on changes in LFC using magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) compared to placebo will be assessed. Samples will be taken under fasting conditions (10 h) in the morning at the same time (±1.5-2 h) during the day before lunch.
Measure: Percent change from baseline to Week 8 and Week 12 in liver fat content (LFC) Time: Baseline (Day 1), Week 8, Week 12Description: The effect of AZD2693 on circulating markers of hepatic inflammation compared to placebo will be assessed.
Measure: Absolute change from baseline in Alanine Aminotransferase Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on circulating markers of hepatic inflammation compared to placebo will be assessed.
Measure: Percent change from baseline in Alanine Aminotransferase Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on circulating markers of hepatic inflammation compared to placebo will be assessed.
Measure: Absolute change from baseline in Aspartate Aminotransferase Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on circulating markers of hepatic inflammation compared to placebo will be assessed.
Measure: Percent change from baseline in Aspartate Aminotransferase Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on circulating markers of hepatic inflammation compared to placebo will be assessed.
Measure: Absolute change from baseline in Gamma Glutamyl Transferase Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on circulating markers of hepatic inflammation compared to placebo will be assessed.
Measure: Percent change from baseline in Gamma Glutamyl Transferase Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on circulating markers of hepatic inflammation compared to placebo will be assessed. ELF score: <7.7: no or mild fibrosis, ≥7.7 to <9.8: moderate fibrosis, ≥9.8 to <11.3: severe fibrosis, and ≥11.3: cirrhosis. A negative change from baseline indicates decreased fibrosis.
Measure: Absolute change from baseline in Enhanced Liver Fibrosis (ELF) score Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on circulating markers of hepatic inflammation compared to placebo will be assessed. ELF score: <7.7: no or mild fibrosis, ≥7.7 to <9.8: moderate fibrosis, ≥9.8 to <11.3: severe fibrosis, and ≥11.3: cirrhosis. A negative change from baseline indicates decreased fibrosis.
Measure: Percent change from baseline in ELF score Time: Up to 36 weeks (From Screening to Final Visit)Description: The effect of AZD2693 on cholesteryl ester 16:1/16:0 compared to placebo will be assessed.
Measure: Absolute change from baseline in plasma cholesteryl ester 16:1/16:0 ratio. Time: Days 1, 29, 50, and 78Description: The effect of AZD2693 on cholesteryl ester 16:1/16:0 compared to placebo will be assessed.
Measure: Percent change from baseline in plasma cholesteryl ester 16:1/16:0 ratio. Time: Days 1, 29, 50, and 78Description: The effect of AZD2693 on disease-specific biomarkers compared to placebo will be assessed.
Measure: Absolute change from baseline in disease-specific biomarkers Time: Days 1, 29, 50, and 78Description: The effect of AZD2693 on disease-specific biomarkers compared to placebo will be assessed.
Measure: Percentage change from baseline in disease-specific biomarkers Time: Days 1, 29, 50, and 78Description: To characterise effects of AZD2693 on lipid handling compared to placebo.
Measure: Absolute change from baseline β-Hydroxybutyrate and lipid profile Time: Days 1, 29, 50, and 78Description: To characterise effects of AZD2693 on lipid handling compared to placebo
Measure: Percent change from baseline β-Hydroxybutyrate and lipid profile Time: Days 1, 29, 50, and 78Description: Single dose PK parameters for AZD2693 and AZD2693 full-length antisense oligonucleotides (ASOs) will be derived from plasma concentrations
Measure: Maximum observed plasma drug concentration (Cmax) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Time to reach maximum observed plasma concentration (tmax) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single and multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Terminal elimination rate constant, estimated by log-linear least-squares regression of the terminal part of the concentration-time curve (λz) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single and multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Apparent terminal elimination half-life associated with the terminal slope (λz) of the semi-logarithmic concentration-time curve, estimated as (ln2)/λz (t½λz) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single and multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Area under the plasma concentration-time curve from time zero to 48 hours after dosing (AUC(0-48h)) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single and multiple dose PK parameters for AZD2693 and AZD2693 full-length antisense oligonucleotides (ASOs) will be derived from plasma concentrations
Measure: Area under the plasma concentration-curve from time zero to the time of last quantifiable analyte concentration (AUClast) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Area under the concentration-time curve from time zero extrapolated to infinity. AUC is estimated by AUClast + Clast/λz where Clast is the last observed quantifiable concentration (AUC) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Apparent total body clearance of drug from plasma after extravascular administration calculated as Dose/AUC (CL/F) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single and multiple dose PK parameters for AZD2693 and AZD2693 full-length antisense oligonucleotides (ASOs) will be derived from plasma concentrations
Measure: Mean residence time (MRT) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single and multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Time delay between drug administration and the first observed concentration in plasma (tlag) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Apparent volume of distribution for parent drug at terminal phase (extravascular administration), estimated by dividing the apparent clearance (CL/F) by λz (Vz/F) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single and multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Area under the plasma concentration-time curve from time zero to time of last quantifiable analyte concentration divided by the dose administered (AUClast/D) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Area under the plasma concentration-time curve from time zero extrapolated to infinity divided by the dose administered (AUC/D) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Observed maximum plasma concentration divided by the dose administered (Cmax/D) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Single and multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Time of the last quantifiable concentration (tlast) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Maximum observed plasma drug concentration at steady state (Cssmax) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Minimum observed drug concentration at steady state (Cssmin) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Time to reach maximum observed plasma concentration at steady state (tssmax) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Area under the concentration-time curve in the dose interval (AUCss) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Apparent total body clearance of drug from plasma after extravascular administration calculated as Dose/AUCss (CLss/F) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Area under the plasma concentration-time curve from time zero extrapolated to infinity divided by the dose administered (AUCss/D) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Observed maximum plasma concentration divided by the dose administered (Cssmax/D) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Accumulation ratio based on Cmax (RacCmax) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Accumulation ratio based on AUC (RacAUC) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Multiple dose PK parameters for AZD2693 and AZD2693 full-length ASOs will be derived from plasma concentrations
Measure: Temporal change parameter in systemic exposure (TCP) Time: First dose: pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 8 and 29 (pre-Dose 2). Last dose (Day 57): pre-dose, 0.5, 1, 2, 3, 4, 6, 8, 12, 24, 36, 48 hours post-dose and at Days 64, 78, 92, and 106.Description: Urine PK parameters for AZD2693 full-length ASOs will be derived from the urine data
Measure: Amount of analyte excreted into the urine from time t1 to t2 (Ae(t1-t2)) Time: Pre-dose and 0-6 hours, 6-12 hours, 12-24 hours, 24-36 hours and 36-48 hours post-dose.Description: Urine PK parameters for AZD2693 full-length ASOs will be derived from the urine data
Measure: Cumulative amount of analyte excreted from time zero through the last sampling interval (Ae(0-last)) Time: Pre-dose and 0-6 hours, 6-12 hours, 12-24 hours, 24-36 hours and 36-48 hours post-dose.Description: Urine PK parameters for AZD2693 full-length ASOs will be derived from the urine data
Measure: Fraction of dose excreted unchanged into the urine from time t1 to t2 (fe(t1-t2)) Time: Pre-dose and 0-6 hours, 6-12 hours, 12-24 hours, 24-36 hours and 36-48 hours post-dose.Description: Urine PK parameters for AZD2693 full-length ASOs will be derived from the urine data
Measure: Cumulative fraction (%) of dose excreted unchanged into the urine from time zero to the last measured time point (fe(0-last)) Time: Pre-dose and 0-6 hours, 6-12 hours, 12-24 hours, 24-36 hours and 36-48 hours post-dose.Description: Urine PK parameters for AZD2693 full-length ASOs will be derived from the urine data
Measure: Renal clearance of drug from plasma, estimated by dividing Ae(0-t) by AUC(0-t) where the 0-t interval is the same for both Ae and AUC (CLR) Time: Pre-dose and 0-6 hours, 6-12 hours, 12-24 hours, 24-36 hours and 36-48 hours post-dose.