Biobank Dataset by Pathology
This document has been developed within the framework of COST Action CA20121 (BenBedPhar), which aims to foster the transition from basic knowledge on the transcription factor NRF2 towards pharmacological and clinical applications in noncommunicable diseases (NCDs). Through its Working Groups1 and 3, BenBedPhar promotes the harmonization of biological sample collections, the standardization of procedures, and the establishment of technological platforms that facilitate access to human materials and metadata relevant to NRF2-related research. The integrated biobank dataset presented here represents a tangible outcome of these coordinated efforts. It compiles and harmonizes information from multiple European biobanks and research cohorts, organized by pathology, providing a unified view of available biospecimens, cohort structures, and demographic
variables. By linking biobank resources to BenBedPhar’s objectives in pharmacological regulation of NRF2, this deliverable creates a foundation for standardized access to biospecimens and data across Europe and strengthens the network’s capacity for translational research.
This integration supports the Action’s broader strategy to connect academic, clinical, and industrial sectors through harmonized infrastructures, promoting cross-disease analyses, biomarker validation, and therapeutic development. Continued updates of this dataset will further enhance interoperability and sustainability within the BenBedPhar network, facilitating future preclinical and
clinical research on NRF2-related mechanisms in major NCDs.
| Cohort owner (Cohort name) | Gothenburg H70 Birth Cohort Studies (Anna Zettergren) |
| Type of recruitment | Population-based longitudinal study of older individuals, recruited from the general population based on birth year and date. |
| Place of recruitment | Gothenburg, Sweden |
| Number of subjects | Approx. 10,000 (but much of the data is only available in sub-groups) |
| F/M | Approx 60% females |
| Age range | 70-110 |
| Healthy/disease (stage?) | Population-based cohorts (baseline age varies between 70 and 95 years of age) |
| Medications y/n | Self-reported information on medication |
| Lifestyle | |
| Dietary intake | Diet history interview (data on foods, energy and nutrient intake) |
| Physical activity | yes; interview and self-rating questionnaire (there are also measures of physical function, such as grip strength, gait speed, balance. |
| Biomarkers | |
| Body composition | DXA, Antropometric measures |
| Inflammation | CRP (not high sensitive) |
| Vascular/adipose tissue | |
| CV health | NT-proBNP |
| Kidney | Creatinine |
| Liver | AST, ALT |
| Lipid metabolism | Total-, HDL-, LDL-Cholesterol, Triglycerides |
| Glucose metabolism | |
| Protein status | N/A |
| Metabolomics | |
| Iron status | Hemoglobin |
| Vitamin & trace element status | Homocysteine (indirect measure of vit B12) |
| Fatty Acids | |
| AGEs | N/A |
| Glycation | |
| ROS/redox status | |
| Lipidperoxidation | |
| Others (please add) | Genetic data (i.e. GWAS), CSF-biomarkers for Alzheimer´s disease and neurodegeneration (Abeta42, t-tau, p-tau, NfL, Neurogranin), plasma-NfL, Neuroimaging |
| Samples available for further use | |
| Plasma/serum | yes |
| Spot urine | N/A |
| 24h urine | N/A |
| Pax tubes (or isolated RNA) | N/A |
| Cells | N/A |
| Tissues | N/A |
| others | |
| Genetics | GWAS |
| Transcription Factors | |
| NRF2/KEAP1 status | |
| redox gene status | |
| CSF Biomarkers | |
| Neuroimaging | Abeta42, t-tau, p-tau, NfL, Neurogranin |
Within the scope of BenBedPhar, the Ageing datasets contribute to understanding how NRF2-related mechanisms intersect with disease-specific pathways and clinical phenotypes. This integrated resource compiles approximately 51 entries from 0 biobank sources, representing collections from 0 countries. Sample matrices include a wide range of biological materials, which
collectively support translational analyses, biomarker discovery, and cross-disease comparison. By aligning this information under a harmonized structure, the Action strengthens its technological foundation for data-driven pharmacological innovation and facilitates coordination among research groups involved in preclinical and clinical NRF2 studies.
Alzheimer disease
| Cohort owner (Cohort name) | Spanish-Romanian cohort (Gina Manda) |
| Type of recruitment | Case-control: 40 AD (T0 baseline) and 40 controls Longitudinal: 40 AD (T0) and 32 (T1 after 1 years) |
| Place of recruitment | Spain (Hospital Universitari Santa Maria-IRB Leida, Lleida) |
| Number of subjects | 80 |
| F/M | 28F/52M |
| Age range | 45-86 |
| Healthy/disease (stage?) | 40 Alzheimer/40 controls |
| Medications y/n | AD treatment available |
| Lifestyle | |
| Dietary intake | N/A |
| Physical activity | N/A |
| Biomarkers | |
| Body composition | |
| Inflammation | Whole blood Gene expression of 168 NFKB-related genes and 84 REDOX genes for 80 individuals (Array 1, Array 2, Array 3) |
| Vascular/adipose tissue | |
| CV health | N/A |
| Kidney | N/A |
| Liver | N/A |
| Lipid metabolism | N/A |
| Glucose metabolism | |
| Protein status | N/A |
| Metabolomics | |
| Iron status | N/A |
| Vitamin & trace element status | N/A |
| Fatty Acids | |
| AGEs | N/A |
| Glycation | |
| ROS/redox status | |
| Lipidperoxidation | |
| Others (please add) | “For AD patients APOE genotype; CSF biomarkers TAU, pTAU, Aβ(1–40), plasma Total TAU, Aβ(1–40) and Aβ(1–42) https//www.dovepress.com/getfile.php?fileID=76016″ |
| Samples available for further use | |
| Plasma/serum | N/A |
| Spot urine | N/A |
| 24h urine | N/A |
| Pax tubes (or isolated RNA) | 112 |
| Cells | N/A |
| Tissues | N/A |
| others | |
| Genetics | |
| Transcription Factors | |
| NRF2/KEAP1 status | |
| redox gene status | |
| CSF Biomarkers | |
| Neuroimaging | |
| Cohort owner (Cohort name) | Alzheimer’s disease Cohort (Anna Zettergren) |
| Type of recruitment | Clinical sample, baseline only (not followed over time) |
| Place of recruitment | Swedish Memory Clinics |
| Number of subjects | Approx. 500 |
| F/M | Approx 60% females |
| Age range | mean age at onset 75 years |
| Healthy/disease (stage?) | Alzheimer’s Disease |
| Medications y/n | N/A |
| Lifestyle | |
| Dietary intake | N/A |
| Physical activity | N/A |
| Biomarkers | |
| Body composition | N/A |
| Inflammation | N/A |
| Vascular/adipose tissue | |
| CV health | N/A |
| Kidney | N/A |
| Liver | N/A |
| Lipid metabolism | N/A |
| Glucose metabolism | |
| Protein status | N/A |
| Metabolomics | |
| Iron status | N/A |
| Vitamin & trace element status | N/A |
| Fatty Acids | |
| AGEs | N/A |
| Glycation | |
| ROS/redox status | |
| Lipidperoxidation | |
| Others (please add) | Genetic data (i.e. GWAS), CSF-biomarkers for Alzheimer´s disease and neurodegeneration (Abeta42, t-tau, p-tau) |
| Samples available for further use | |
| Plasma/serum | N/A |
| Spot urine | N/A |
| 24h urine | N/A |
| Pax tubes (or isolated RNA) | N/A |
| Cells | N/A |
| Tissues | N/A |
| others | |
| Genetics | |
| Transcription Factors | |
| NRF2/KEAP1 status | |
| redox gene status | |
| CSF Biomarkers | |
| Neuroimaging | |
Within the scope of BenBedPhar, the Alzheimer disease datasets contribute to understanding how NRF2-related mechanisms intersect with disease-specific pathways and clinical phenotypes. This integrated resource compiles approximately 102 entries from 0 biobank sources, representing collections from 0 countries. Sample matrices include a wide range of biological materials, which collectively support translational analyses, biomarker discovery, and cross-disease comparison. By aligning this information under a harmonized structure, the Action strengthens its technological foundation for data-driven pharmacological innovation and facilitates coordination among research groups involved in preclinical and clinical NRF2 studies.
Cardiovascular disease
| Cohort owner (Cohort name) | Cardio_Adipose tissues (Eugenia Carvalho) |
| Type of recruitment | |
| Place of recruitment | Cardiothroracic Surgery Unit at the University Hospital of Coimbra, Coimbra, Portugal |
| Number of subjects | 36 (14 with diabetes) |
| F/M | 33/3 |
| Age range | 55-85 |
| Healthy/disease (stage?) | Patientes elected for cardiac disease, with or withouth diabetes |
| Medications y/n | yes (antiplatelets, antirihmics, anticoagulants, insulin, alpha glucosidase inhibitors, DPP4 inhibitors, metformin, beta blcokers, calcium channel blocker, angiotesnin receptor blockers, angiotensin inhibitors, diurectic, statins, vasodilectors) |
| Lifestyle | |
| Dietary intake | smoking and drinking habits |
| Physical activity | no |
| Biomarkers | |
| Body composition | yes: height, weight and BMI |
| Inflammation | |
| Vascular/adipose tissue | |
| CV health | INR (internantional normalized ratio) and CK (creatine Kinase) |
| Kidney | Urea; Creatinine |
| Liver | AST (aspartate aminotrasferase);ALT (alinino transferase);GGT; Alkaline Phosphatase (ALP); LDH (lactate dehidrogenase) |
| Lipid metabolism | Diagnose of dyslipidemia |
| Glucose metabolism | Fasting glucose levels |
| Protein status | |
| Metabolomics | |
| Iron status | |
| Vitamin & trace element status | |
| Fatty Acids | |
| AGEs | |
| Glycation | |
| ROS/redox status | |
| Lipidperoxidation | |
| Others (please add) | Blood pressure and diagnose of hipertension; type of cardioascular disease (coronary artery disease or valvule dysfunction or heart congenit disease) |
| Samples available for further use | |
| Plasma/serum | |
| Spot urine | |
| 24h urine | |
| Pax tubes (or isolated RNA) | |
| Cells | |
| Tissues | X (epicardial and subcutaneous adipose tissue) |
| others | |
| Genetics | |
| Transcription Factors | |
| NRF2/KEAP1 status | |
| redox gene status | |
| CSF Biomarkers | |
| Neuroimaging | |
| Cohort owner (Cohort name) | Cardio_Biofluids ( Eugenia Carvalho) |
| Type of recruitment | |
| Place of recruitment | Cardiothroracic Surgery Unit at the University Hospital of Coimbra, Coimbra, Portugal |
| Number of subjects | 191 (75 with diabetes) |
| F/M | 51/140 |
| Age range | 55-85 |
| Healthy/disease (stage?) | Patientes elected for cardiac disease, with or withouth diabetes |
| Medications y/n | yes (antiplatelets, antirihmics, anticoagulants, insulin, alpha glucosidase inhibitors, DPP4 inhibitors, metformin, beta blockers, calcium channel blockers, angiotesnin receptor blockers, angiotensin inhibitors, diurectic, statins, vasodilectors) |
| Lifestyle | |
| Dietary intake | smoking and drinking habits |
| Physical activity | no |
| Biomarkers | |
| Body composition | yes: height, weight and BMI |
| Inflammation | |
| Vascular/adipose tissue | |
| CV health | INR (internantional normalized ratio) and CK (creatine Kinase) |
| Kidney | Urea; Creatinine |
| Liver | AST (aspartate aminotrasferase);ALT (alinino transferase);GGT; Alkaline Phosphatase (ALP); LDH (lactate dehidrogenase) |
| Lipid metabolism | Diagnose of dyslipidemia |
| Glucose metabolism | Fasting glucose levels |
| Protein status | |
| Metabolomics | |
| Iron status | |
| Vitamin & trace element status | |
| Fatty Acids | |
| AGEs | |
| Glycation | |
| ROS/redox status | |
| Lipidperoxidation | |
| Others (please add) | Blood pressure and diagnose of hipertension; type of cardioascular disease (coronary artery disease or valvule dysfunction or heart congenit disease) |
| Samples available for further use | |
| Plasma/serum | X (and whole blood) |
| Spot urine | |
| 24h urine | |
| Pax tubes (or isolated RNA) | |
| Cells | |
| Tissues | |
| others | |
| Genetics | |
| Transcription Factors | |
| NRF2/KEAP1 status | |
| redox gene status | |
| CSF Biomarkers | |
| Neuroimaging | |
| Cohort owner (Cohort name) | Cardio_Internal thoracic artery (Eugenia Carvalho) |
| Type of recruitment | |
| Place of recruitment | Cardiothroracic Surgery Unit at the University Hospital of Coimbra, Coimbra, Portugal |
| Number of subjects | 31 (14 with diabetes) |
| F/M | 29/2 |
| Age range | 55-85 |
| Healthy/disease (stage?) | Patientes elected for cardiac disease, with or withouth diabetes |
| Medications y/n | yes (antiplatelets, antirihmics, anticoagulants, insulin, alpha glucosidase inhibitors, DPP4 inhibitors, metformin, beta blcokers, calcium channel blocker, angiotesnin receptor blockers, angiotensin inhibitors, diurectic, statins, vasodilectors) |
| Lifestyle | |
| Dietary intake | smoking and drinking habits |
| Physical activity | no |
| Biomarkers | |
| Body composition | yes: height, weight and BMI |
| Inflammation | |
| Vascular/adipose tissue | |
| CV health | INR (internantional normalized ratio) and CK (creatine Kinase) |
| Kidney | Urea; Creatinine |
| Liver | AST (aspartate aminotrasferase);ALT (alinino transferase);GGT; Alkaline Phosphatase (ALP); LDH (lactate dehidrogenase) |
| Lipid metabolism | Diagnose of dyslipidemia |
| Glucose metabolism | Fasting glucose levels |
| Protein status | |
| Metabolomics | |
| Iron status | |
| Vitamin & trace element status | |
| Fatty Acids | |
| AGEs | |
| Glycation | |
| ROS/redox status | |
| Lipidperoxidation | |
| Others (please add) | Blood pressure and diagnose of hipertension; type of cardioascular disease (coronary artery disease or valvule dysfunction or heart congenit disease) |
| Samples available for further use | |
| Plasma/serum | X |
| Spot urine | |
| 24h urine | |
| Pax tubes (or isolated RNA) | |
| Cells | |
| Tissues | X (internal thoracic artery) |
| others | |
| Genetics | |
| Transcription Factors | |
| NRF2/KEAP1 status | |
| redox gene status | |
| CSF Biomarkers | |
| Neuroimaging | |
Within the scope of BenBedPhar, the Cardiovascular disease datasets contribute to understanding how NRF2-related mechanisms intersect with disease-specific pathways and clinical phenotypes. This integrated resource compiles approximately 153 entries from 0 biobank sources, representing collections from 0 countries. Sample matrices include a wide range of biological materials, which collectively support translational analyses, biomarker discovery, and cross-disease comparison. By aligning this information under a harmonized structure, the Action strengthens its technological foundation for data-driven pharmacological innovation and facilitates coordination among research groups involved in preclinical and clinical NRF2 studies.
Cognitive impairment
| Cohort owner (Cohort name) | Romania (Gina Manda) |
| Type of recruitment | Longitudinal: 150 baseline (T0); 61 after 1month (T1); 32 after 6 months (T2) |
| Place of recruitment | Romania (National Institute of Pathology Victor Babes) |
| Number of subjects | 150 |
| F/M | 101F/49M |
| Age range | 28-88 |
| Healthy/disease (stage?) | 50 cognitive impairment/100 normal cognition |
| Medications y/n | Info available in Database |
| Lifestyle | |
| Dietary intake | N/A |
| Physical activity | N/A |
| Biomarkers | |
| Body composition | Only BMI is available for 112 individuals |
| Inflammation | Whole blood Gene expression of 84 NFKB-related genes and 84 REDOX genes for 76 individuals (Array 1, Array 3) |
| Vascular/adipose tissue | |
| CV health | Cytokines/chemokines/growth factors and CVD markers assessed in serum from 46 individuals (https//www.dovepress.com/getfile.php?fileID=66782) |
| Kidney | N/A |
| Liver | N/A |
| Lipid metabolism | N/A |
| Glucose metabolism | |
| Protein status | N/A |
| Metabolomics | |
| Iron status | N/A |
| Vitamin & trace element status | N/A |
| Fatty Acids | |
| AGEs | N/A |
| Glycation | |
| ROS/redox status | |
| Lipidperoxidation | |
| Others (please add) | |
| Samples available for further use | |
| Plasma/serum | All available |
| Spot urine | N/A |
| 24h urine | N/A |
| Pax tubes (or isolated RNA) | All available |
| Cells | PBMC or lymphocytes |
| Tissues | N/A |
| others | |
| Genetics | |
| Transcription Factors | |
| NRF2/KEAP1 status | |
| redox gene status | |
| CSF Biomarkers | |
| Neuroimaging | |
Within the scope of BenBedPhar, the Cognitive impairment datasets contribute to understanding how NRF2-related mechanisms intersect with disease-specific pathways and clinical phenotypes. This integrated resource compiles approximately 51 entries from 0 biobank sources, representing collections from 0 countries. Sample matrices include a wide range of biological materials, which collectively support translational analyses, biomarker discovery, and cross-disease comparison. By aligning this information under a harmonized structure, the Action strengthens its technological foundation for data-driven pharmacological innovation and facilitates coordination among research groups involved in preclinical and clinical NRF2 studies.
Hepatocellular carcinoma
| Cohort owner (Cohort name) | Jordi Muntané |
| Type of recruitment | Hepatocellular carcinoma |
| Place of recruitment | Institute of Biomedicine of Seville (Spain) |
| Number of subjects | 409 |
| F/M | 20/80 |
| Age range | 13-90 |
| Healthy/disease (stage?) | Stages A-D |
| Medications y/n | Transplantation, resection, radiofrequency, ablation, chemotherapy and systemic therapy |
| Lifestyle | |
| Dietary intake | Clinical history |
| Physical activity | Clinical history |
| Biomarkers | |
| Body composition | Clinical history |
| Inflammation | Clinical history |
| Vascular/adipose tissue | Clinical history |
| CV health | Clinical history |
| Kidney | Clinical history |
| Liver | Etiology, cirrhosis |
| Lipid metabolism | Clinical history |
| Glucose metabolism | Clinical history |
| Protein status | Clinical history |
| Metabolomics | Clinical history |
| Iron status | Clinical history |
| Vitamin & trace element status | Clinical history |
| Fatty Acids | Clinical history |
| AGEs | No available |
| Glycation | No available |
| ROS/redox status | No available |
| Lipidperoxidation | No available |
| Others (please add) | |
| Samples available for further use | |
| Plasma/serum | Yes |
| Spot urine | No |
| 24h urine | No |
| Pax tubes (or isolated RNA) | miRNA |
| Cells | Buffy coat/PBMCs (storage -80°C), Whole blood/Packed cells |
| Tissues | Cryopreserved tissue, Formalin/OCT-fixed Paraffin embedded tissue |
| others | |
| Genetics | No available |
| Transcription Factors | No available |
| NRF2/KEAP1 status | No available |
| redox gene status | No available |
| CSF Biomarkers | No available |
| Neuroimaging | Clinical history |
Within the scope of BenBedPhar, the Hepatocellular carcinoma datasets contribute to understanding how NRF2-related mechanisms intersect with disease-specific pathways and clinical phenotypes. This integrated resource compiles approximately 51 entries from 0 biobank sources, representing collections from 0 countries. Sample matrices include a wide range of biological materials, which collectively support translational analyses, biomarker discovery, and cross-disease comparison. By aligning this information under a harmonized structure, the Action strengthens its technological foundation for data-driven pharmacological innovation and facilitates coordination among research groups involved in preclinical and clinical NRF2 studies.
Obesity & Metabolic/Bariatric Surgery
| Cohort owner (Cohort name) | CHUC (Eugenia Carvalho) |
| Type of recruitment | Obesity Consultation |
| Place of recruitment | CHUC |
| Number of subjects | 92 (18 with diabetes) |
| F/M | 78/14 |
| Age range | 24-66 |
| Healthy/disease (stage?) | Healthy or type 2 diabetes; all obese |
| Medications y/n | yes (metformin) |
| Lifestyle | |
| Dietary intake | not evaluated |
| Physical activity | not evaluated |
| Biomarkers | |
| Body composition | yes: height, weight and BMI |
| Inflammation | yes: C-reactive protein |
| Vascular/adipose tissue | yes: leptin, adiponectin |
| CV health | no |
| Kidney | no |
| Liver | yes: AST (aspartate aminotrasferase) ALT (alinino transferase) |
| Lipid metabolism | yes: Triglycerides; LDL; HDL; Total Cholesterol |
| Glucose metabolism | yes: Fasting Glucose; Fasting insulin; fasting c-peptide; HbA1C |
| Protein status | no |
| Metabolomics | no |
| Iron status | no |
| Vitamin & trace element status | no |
| Fatty Acids | yes |
| AGEs | no |
| Glycation | yes: plasma levels of GLO-1 |
| ROS/redox status | no |
| Lipidperoxidation | no |
| Others (please add) | |
| Samples available for further use | |
| Plasma/serum | yes: plasma/serum |
| Spot urine | no |
| 24h urine | no |
| Pax tubes (or isolated RNA) | yes: isolated RNA of Visceral adipose tissue |
| Cells | no |
| Tissues | yes: Subcutaneous and Visceral Adipose tissue |
| others | |
| Genetics | no |
| Transcription Factors | yes |
| NRF2/KEAP1 status | yes (NRF2 mRNA in Visceral adipose tissue) |
| redox gene status | yes (catalase, gss, gsr expression in Visceral adipose tissue) |
| CSF Biomarkers | no |
| Neuroimaging | no |
| Cohort owner (Cohort name) | Metabolic Surgery (Eugenia Carvalho) |
| Type of recruitment | |
| Place of recruitment | General Surgery Department at CHUC |
| Number of subjects | 57 ( 23 with diabetes) |
| F/M | 38/19 |
| Age range | 18-65 |
| Healthy/disease (stage?) | People with Obesity |
| Medications y/n | yes |
| Lifestyle | |
| Dietary intake | No information |
| Physical activity | No information |
| Biomarkers | |
| Body composition | yes: height, weight and BMI, waist circunference, hip circunference and neck circunference |
| Inflammation | yes: C-reactive protein |
| Vascular/adipose tissue | No |
| CV health | No |
| Kidney | yes: Creatinine |
| Liver | yes: AST (aspartate aminotrasferase) ALT (alinino transferase) LDH (lactate dehidrogenase) |
| Lipid metabolism | Triglycerides; LDL; HDL; Total Cholesterol |
| Glucose metabolism | Fasting Glucose; Fasting insulin; fasting c-peptide; HbA1C |
| Protein status | no |
| Metabolomics | no |
| Iron status | no |
| Vitamin & trace element status | no |
| Fatty Acids | no |
| AGEs | no |
| Glycation | no |
| ROS/redox status | no |
| Lipidperoxidation | no |
| Others (please add) | Blood pressure |
| Samples available for further use | |
| Plasma/serum | plasma/serum/whole blood |
| Spot urine | no |
| 24h urine | no |
| Pax tubes (or isolated RNA) | no |
| Cells | no |
| Tissues | Subcutaneous and Visceral Adipose tissue |
| others | no |
| Genetics | no |
| Transcription Factors | no |
| NRF2/KEAP1 status | no |
| redox gene status | no |
| CSF Biomarkers | no |
| Neuroimaging | no |
| Cohort owner (Cohort name) | Metabolic Surgery (Eugenia Carvalho) |
| Type of recruitment | |
| Place of recruitment | General Surgery Department at CHUC |
| Number of subjects | 57 ( 23 with diabetes) |
| F/M | 38/19 |
| Age range | 18-65 |
| Healthy/disease (stage?) | People with Obesity |
| Medications y/n | yes |
| Lifestyle | |
| Dietary intake | No information |
| Physical activity | No information |
| Biomarkers | |
| Body composition | yes: height, weight and BMI, waist circunference, hip circunference and neck circunference |
| Inflammation | yes: C-reactive protein |
| Vascular/adipose tissue | No |
| CV health | No |
| Kidney | yes: Creatinine |
| Liver | yes: AST (aspartate aminotrasferase) ALT (alinino transferase) LDH (lactate dehidrogenase) |
| Lipid metabolism | Triglycerides; LDL; HDL; Total Cholesterol |
| Glucose metabolism | Fasting Glucose; Fasting insulin; fasting c-peptide; HbA1C |
| Protein status | no |
| Metabolomics | no |
| Iron status | no |
| Vitamin & trace element status | no |
| Fatty Acids | no |
| AGEs | no |
| Glycation | no |
| ROS/redox status | no |
| Lipidperoxidation | no |
| Others (please add) | Blood pressure |
| Samples available for further use | |
| Plasma/serum | plasma/serum/whole blood |
| Spot urine | no |
| 24h urine | no |
| Pax tubes (or isolated RNA) | no |
| Cells | no |
| Tissues | Subcutaneous and Visceral Adipose tissue |
| others | no |
| Genetics | no |
| Transcription Factors | no |
| NRF2/KEAP1 status | no |
| redox gene status | no |
| CSF Biomarkers | no |
| Neuroimaging | no |
Within the scope of BenBedPhar, the Pulmonary hypertension datasets contribute to understanding how NRF2-related mechanisms intersect with disease-specific pathways and clinical phenotypes. This integrated resource compiles approximately 51 entries from 0 biobank sources, representing collections from 0 countries. Sample matrices include a wide range of biological materials, which collectively support translational analyses, biomarker discovery, and cross-disease comparison. By aligning this information under a harmonized structure, the Action strengthens its technological foundation for data-driven pharmacological innovation and facilitates coordination among research groups involved in preclinical and clinical NRF2 studies.
Pulmonary hypertension
| Cohort owner (Cohort name) | María José Sánchez-Quintero |
| Type of recruitment | |
| Place of recruitment | Hospital Virgen de la Victoria, Málaga, Spain. Hospital 12 octubre, Madrid, Spain. |
| Number of subjects | 15-20 |
| F/M | Both |
| Age range | |
| Healthy/disease (stage?) | Pulmonary Hypertension |
| Medications y/n | |
| Lifestyle | |
| Dietary intake | |
| Physical activity | |
| Biomarkers | |
| Body composition | |
| Inflammation | |
| Vascular/adipose tissue | |
| CV health | |
| Kidney | |
| Liver | |
| Lipid metabolism | |
| Glucose metabolism | |
| Protein status | |
| Metabolomics | |
| Iron status | |
| Vitamin & trace element status | |
| Fatty Acids | |
| AGEs | |
| Glycation | |
| ROS/redox status | |
| Lipidperoxidation | |
| Others (please add) | |
| Samples available for further use | |
| Plasma/serum | yes |
| Spot urine | |
| 24h urine | |
| Pax tubes (or isolated RNA) | |
| Cells | yes. Fibroblasts, PBMCs. |
| Tissues | |
| others | |
| Genetics | |
| Transcription Factors | |
| NRF2/KEAP1 status | |
| redox gene status | |
| CSF Biomarkers | |
| Neuroimaging | |
Within the scope of BenBedPhar, the Pulmonary hypertension datasets contribute to understanding how NRF2-related mechanisms intersect with disease-specific pathways and clinical phenotypes. This integrated resource compiles approximately 51 entries from 0 biobank sources, representing collections from 0 countries. Sample matrices include a wide range of biological materials, which collectively support translational analyses, biomarker discovery, and cross-disease comparison. By aligning this information under a harmonized structure, the Action strengthens its technological foundation for data-driven pharmacological innovation and facilitates coordination among research groups involved in preclinical and clinical NRF2 studies.
Various diseases
| Cohort owner (Cohort name) | Ioannis Trougakos |
| Type of recruitment | In the clinic, public media |
| Place of recruitment | Athens, Greece |
| Number of subjects | >2500 |
| F/M | ~50% M, 50% F |
| Age range | 18-92 |
| Healthy/disease (stage?) | Health and various diseases |
| Medications y/n | Disease based / not in healthy |
| Lifestyle | |
| Dietary intake | Various (based also on health status) |
| Physical activity | Various (based also on health status) |
| Biomarkers | |
| Body composition | Various |
| Inflammation | N/A |
| Vascular/adipose tissue | N/A |
| CV health | N/A |
| Kidney | N/A |
| Liver | N/A |
| Lipid metabolism | N/A |
| Glucose metabolism | N/A |
| Protein status | N/A |
| Metabolomics | N/A |
| Iron status | N/A |
| Vitamin & trace element status | N/A |
| Fatty Acids | N/A |
| AGEs | N/A |
| Glycation | N/A |
| ROS/redox status | N/A |
| Lipidperoxidation | N/A |
| Others (please add) | N/A |
| Samples available for further use | |
| Plasma/serum | Yes |
| Spot urine | – |
| 24h urine | – |
| Pax tubes (or isolated RNA) | Isolated RNA |
| Cells | – |
| Tissues | – |
| others | – |
| Genetics | Not known |
| Transcription Factors | Not known |
| NRF2/KEAP1 status | Not known |
| redox gene status | Not known |
| CSF Biomarkers | Not known |
| Neuroimaging | Not known |
Within the scope of BenBedPhar, the Various diseases datasets contribute to understanding how NRF2-related mechanisms intersect with disease-specific pathways and clinical phenotypes. This integrated resource compiles approximately 51 entries from 0 biobank sources, representing collections from 0 countries. Sample matrices include a wide range of biological materials, which collectively support translational analyses, biomarker discovery, and cross-disease comparison. By aligning this information under a harmonized structure, the Action strengthens its technological foundation for data-driven pharmacological innovation and facilitates coordination among research groups involved in preclinical and clinical NRF2 studies.