Addressing the quality challenge of a human biospecimen biobank through the creation of a quality management system.

BACKGROUND: The objective of the COMET (COllection of MEtabolic Tissues) biobank project is to create a high-quality collection of insulin-sensitive tissues (liver, muscle, adipose tissues, and epiploic artery) and blood sample derivatives (plasma, serum, DNA and RNA), collected from 270 grade 2-3 obese patients undergoing bariatric surgery. Relevant data on patient such as clinical/biological characteristics and sample handling are also collected. For this, our aim was to establish a Quality Management System (QMS) to meet the reliability and quality requirements necessary for its scientific exploitation. MATERIALS AND METHODS: The COMET QMS includes: (1) Quality Assurance to standardize all stages of the biobanking process, (2) Quality Controls on samples from the first patients included in order to validate the sample management process and ensure reproducible quality; and 3) "in process" Quality Controls to ensure the reliability of the storage procedures and the stability of the samples over time. RESULTS: For serum and plasma, several corrective actions, such as temperature handling and centrifugation conditions, were made to the protocol and led to improvement of the volume and quality of samples. Regarding DNA, all samples evaluated achieved a satisfactory level of purity and integrity and most of them yielded the required DNA quantity. All frozen tissue samples had RNAs of good purity. RNA quality was confirmed by RIN, achieving values in most cases over 7 and efficient amplification of housekeeping genes by RT-qPCR, with no significant differences among samples from the same tissue type. In the "in process" Quality Controls, DNA, RNA, and histological integrity of tissues showed no differences among samples after different preservation times. CONCLUSION: Quality Control results have made it possible to validate the entire biobank process and confirm the utility of implementing QMS to guarantee the quality of a biospecimen collection.

The triglycerides and glucose (TyG) index: A new marker associated with nonalcoholic steatohepatitis (NASH) in obese patients.

AIM: Diagnosis of nonalcoholic steatohepatitis (NASH) relies on liver biopsy. Noninvasive tools would be useful to target patients to refer for a biopsy. We aimed to determine the diagnostic value of the triglycerides and glucose (TyG) index, an insulin-resistance indicator, to predict NASH. METHODS: Our study included grade II-III obese patients aged 18-65 years undergoing bariatric surgery and included in the COMET (COllection of MEtabolic Tissues) biobank (NCT02861781). Liver biopsies performed during bariatric surgery were collected from the biobank along with blood derivatives. Biopsies were analysed according to the steatosis, activity and fibrosis (SAF) scoring system to diagnose NASH, nonalcoholic fatty liver disease (NAFLD), and fibrosis. Logistic regression models were performed to identify factors predicting NASH, NAFLD, and fibrosis. RESULTS: Of 238 analysed subjects (mean age 43±12 years, 33.6% men), 29% had type 2 diabetes. Steatosis was present in 67.2%, while NASH and advanced fibrosis (stage F3) were diagnosed in 18.1% and 2.9% respectively. TyG index was independently associated with NASH (odds ratio (OR): 4.7 [95% confidence interval: 2.3;9.5] P < 0.0001), NAFLD (OR: 2.0 [1.1;3.7] P = 0.03) and stages 2-3 fibrosis (OR: 4.0 [1.5;10.8] P = 0.007). NASH was also predicted by gamma-glutamyl transferase (GGT) with an area under the ROC curve: 0.79 [0.71;0.87 P = 0.04] for GGT and TyG index combined. CONCLUSION: In our cohort of severely obese patients, TyG index, when associated with GGT level, exhibited high diagnostic performance to predict NASH. Although validation in larger populations is needed, this result may be of considerable clinical value to predict need for liver biopsy.

Optimization of RNA extraction methods from human metabolic tissue samples of the COMET biobank.

Constitution of biobank of human tissues requires careful handling and storage of biological material, to guarantee the quality of samples. Tissue preparation is also critical for further applications such as transcriptomic profiling. In this study, our aim was to evaluate the impact of different disruption techniques (FastPrep-24 instrument, GentleMACS dissociator, and syringe/needle) and homogenizing buffers (RLT versus QIAzol) on RNA purity and quality of metabolic tissues (adipose tissues, liver and skeletal muscle) present in the COMET Biobank. For all homogenization methods used and tissue types, the A260/280 ratios reached values ≥ 1.8, which are in the range of what is found in human tissues and cell lines, while the A260/230 ratios were however ≤ 1.8, with the lowest value obtained with GentleMACS Dissociator. In addition, GentleMACS Dissociator combined with QIAzol reagent gave the highest RIN value and 28S/18S ratio for all tissues tested, except for muscle. Performing RT-qPCR, Ct values for different housekeeping genes can be influenced by extraction methods and RNA quality of samples. In conclusion, we have demonstrated that different disruption techniques and homogenizing buffers impact the purity and some quality markers of RNA, and can also impact quantification of mRNAs by RT-qPCR in human metabolic tissues.