Background: HbA(1c) is a widely used biomarker for the management of diabetes mellitus and can be quantified from blood samples by using various methods, including ion-exchange high-performance liquid chromatography (HPLC), boronate affinity HPLC, and capillary electrophoresis (CE). Here, we evaluated the accuracy of four separation methods for determination of HbA(1c) values in Chinese patients with different hemoglobin disorders. Methods: Blood samples from normal patients, patients with beta-thalassemia, patients exhibiting heterozygosity, and patients exhibiting homozygosity were analyzed using ion-exchange HPLC (Variant II Turbo, Bio-Rad and Adams A(1c) HA-8160, Arkray, run in diabetes mode), boronate affinity HPLC (Ultra(2), Trinity Biotech), and CE (Capillarys 2 Flex Piercing, Sebia). Results: Samples from patients with beta-thalassemia produced significant positive biases on the Variant II Turbo system compared to the other three systems. For heterozygous beta A/beta E patients, a good agreement was observed between Capillarys 2 Flex Piercing and Ultra(2) systems, while a significant negative bias was observed between HA-8160 and Capillarys 2 Flex Piercing systems and between Variant II Turbo and Capillarys 2 Flex Piercing systems. For homozygous (beta E/beta E) patients, a clear context without HbA, all systems except the Capillarys 2 Flex Piercing system yielded random HbA(1c) results. Only the Capillarys 2 Flex Piercing system could detect all hemoglobin variants tested. Conclusions: beta-Thalassemia can cause errors in HbA(1c) determination using the Variant II Turbo system. HbE heterozygosity or HbE homozygosity also complicated HbA(1c) measurements. The Capillarys 2 Flex Piercing system detected all Hb variants and HbA(1c) in patients with beta-thalassemia and could provide measurements with high accuracy.

Background: HbA_1c is a widely used biomarker for diabetes mellitus management. Here, we evaluated the accuracy of six methods for determining HbA_1c values in Chinese patients with common α- and β-globin chains variants in China. Methods: Blood samples from normal subjects and individuals exhibiting hemoglobin variants were analyzed for HbA_1c, using Sebia Capillarys 2 Flex Piercing (C2FP), Bio-Rad Variant II Turbo 2.0, Tosoh HLC-723 G8 (ver. 5.24), Arkray ADAMS A1c HA-8180V fast mode, Cobas c501 and Trinity Ultra² systems. Results: DNA sequencing revealed five common β-globin chain variants and three common α-globin chain variants. The most common variant was Hb E, followed by Hb New York, Hb J-Bangkok, Hb G-Coushatta, Hb Q-Thailand, Hb G-Honolulu, Hb Ube-2 and Hb G-Taipei. Variant II Turbo 2.0, Ultra² and Cobas c501 showed good agreement with C2FP for most samples with variants. HLC-723 G8 yielded no HbA_1c values for Hb J-Bangkok, Hb Q-Thailand and Hb G-Honolulu. Samples with Hb E, Hb G-Coushatta, Hb G-Taipei and Hb Ube-2 produced significant negative biases for HLC-723 G8. HA-8180V showed statistically significant differences for Hb E, Hb G-Coushatta, Hb G-Taipei, Hb Q-Thailand and Hb G-Honolulu. HA-8180V yielded no HbA_1c values for Hb J-Bangkok. All methods showed good agreement for samples with Hb New York. Conclusions: Some common hemoglobin variants can interfere with HbA_1c determination by the most popular methods in China.

In order to ensure the quality in clinical laboratories and meet the low risk requirements of patients and clinicians, a risk analysis and assessment model based on Sigma metrics and intended use was constructed, based on which differential sigma performance (σ) expectations of 42 analytes were developed. Failure mode and effects analysis was applied to produce an analytic risk rating based on three factors, each test of which was graded as follows: 1) Sigma metrics; 2) the severity of harm; 3) intended use. By multiplying the score of Sigma metrics by the score of severity of harm by the score of intended use, each was assigned a typical risk priority number (RPN), with RPN ≤ 25 rated as low risk. Low risk was defined as acceptable standards; the sigma performance expectations were calculated. Among the 42 analytes, tests with σ ≥ 6, 5 ≤ σ < 6, 4 ≤ σ < 5, 3 ≤ σ < 4, σ < 3 were 21, 5, 5, 6, and 5, respectively; there were 7 high-risk tests, 8 of them medium risk tests. According to the risk assessment conclusion, 13 tests had sigma performance expectations ≥ 6; 15 test items had sigma performance expectations ≥ 5, while 3 test items had sigma performance expectations ≥ 4; 11 test items had sigma performance expectations ≥ 3. Constructing the risk analysis and assessment model based on Sigma metrics and intended use will help clinical laboratories to identify the high-risk tests more objectively and comprehensively. Such model can also be used to establish the sigma performance expectations and meet the low risk requirements of patients and clinicians.

The clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated (Cas) proteins constitute the innate adaptive immune system in several bacteria and archaea. This immune system helps them in resisting the invasion of phages and foreign DNA by providing sequence-specific acquired immunity. Owing to the numerous advantages such as ease of use, low cost, high efficiency, good accuracy, and a diverse range of applications, the CRISPR-Cas system has become the most widely used genome editing technology. Hence, the advent of the CRISPR/Cas technology highlights a tremendous potential in clinical diag nosis and could become a powerful asset for modern medicine. This study reviews the recently reported application platforms for screening, diagnosis, and treatment of different diseases based on CRISPR/Cas systems. The limitations, current challenges, and future prospectus are summarized; this article would be a valuable reference for future genome-editing practices.