Severe combined immunodeficiency (SCID), the most severe form of T-cell immunodeficiency, can be screened at birth by quantifying T-cell receptor excision circles (TRECs) in dried blood spot (DBS) samples. Early detection of this condition speeds up the establishment of appropriate treatment and increases the patient's life expectancy. Newborn screening for SCID started in January 2017 in Catalonia, the first Spanish and European region to universally include this testing. The results obtained in the first 2 years of experience are evaluated here. All babies born between January 2017 and December 2018 were screened. TREC quantification in DBS (1.5 mm diameter) was performed with the Enlite Neonatal TREC kit from PerkinElmer (Turku, Finland). In 2018, the retest cutoff in the detection algorithm was updated based on the experience gained in the first year, and changed from 34 to 24 copies/μL. This decreased the retest rate from 3.34 to 1.4% (global retest rate, 2.4%), with a requested second sample rate of 0.23% and a positive detection rate of 0.02%. Lymphocyte phenotype (T, B, NK populations), expression of CD45RA/RO isoforms, percentage and intensity of TCR αβ and TCR γδ, presence of HLA-DR+ T lymphocytes, and in vitro lymphocyte proliferation were studied in all patients by flow cytometry. Of 130,903 newborns screened, 30 tested positive, 15 of which were male. During the study period, one patient was diagnosed with SCID: incidence, 1 in 130,903 births in Catalonia. Thirteen patients had clinically significant T-cell lymphopenia (non-SCID) with an incidence of 1 in 10,069 newborns (43% of positive detections). Nine patients were considered false-positive cases because of an initially normal lymphocyte count with normalization of TRECs between 3 and 6 months of life, four infants had transient lymphopenia due to an initially low lymphocyte count with recovery in the following months, and three patients are still under study. The results obtained provide further evidence of the benefits of including this disease in newborn screening programs. Longer follow-up is needed to define the exact incidence of SCID in Catalonia.

Background and AimsUlcerative colitis [UC] is a chronic inflammatory disease of the colon. Colonoscopy remains the gold standard for evaluating disease activity, as clinical symptoms are not sufficiently accurate. The aim of this study is to identify new accurate non-invasive biomarkers based on whole-blood transcriptomics that can predict mucosal lesions and response to treatment in UC patients.MethodsWhole-blood samples were collected for a total of 152 UC patients at endoscopy. Blood RNA from 25 UC individuals and 20 controls was analysed using microarrays. Genes that correlated with endoscopic activity were validated using real-time polymerase chain reaction in an independent group of 111 UC patients, and a prediction model for mucosal lesions was evaluated. Responsiveness to treatment was assessed in a longitudinal cohort of 16 UC patients who started anti-tumour necrosis factor [TNF] therapy and were followed up for 14 weeks.ResultsMicroarray analysis identified 122 genes significantly altered in the blood of endoscopically active UC patients. A significant correlation with the degree of endoscopic activity was observed in several genes, including HP, CD177, GPR84, and S100A12. Using HP as a predictor of endoscopic disease activity, an accuracy of 67.3% was observed, compared with 52.4%, 45.2%, and 30.3% for C-reactive protein, erythrocyte sedimentation rate, and platelet count, respectively. Finally, at 14 weeks of treatment, response to anti-TNF therapy induced alterations in blood HP, CD177, GPR84, and S100A12 transcripts that correlated with changes in endoscopic activity.ConclusionsTranscriptional changes in UC patients are sensitive to endoscopic improvement and appear to be an effective tool to monitor patients over time.

In our cohort CE was significantly superior to MRE for detecting SB lesions, mainly superficial and proximal lesions. CE is useful for a appropriate patients' classification according to Montreal classification.