Background:Fluoropyrimidine drugs are extensively used for the treatment of solid cancers. However, adverse drug reactions are a major clinical problem, often necessitating treatment discontinuation. The aim of this study was to identify pharmacogenetic markers predicting fluoropyrimidine toxicity.Methods:Toxicity in the first four cycles of 5-fluorouracil or capecitabine-based chemotherapy were recorded for a series of 430 patients. The association between demographic variables, DPYD, DPYS, TYMS, MTHFR, CDA genotypes, and toxicity were analysed using logistic regression models.Results:Four DPYD sequence variants (c.1905+1G>A, c.2846A>T, c.1601G>A and c.1679T>G) were found in 6% of the cohort and were significantly associated with grade 3–4 toxicity (P<0.0001). The TYMS 3′-untranslated region del/del genotype substantially increased the risk of severe toxicity (P=0.0123, odds ratio (OR)=3.08, 95% confidence interval (CI): 1.38–6.87). For patients treated with capecitabine, a MTHFR c.1298CC homozygous variant genotype predicted hand–foot syndrome (P=4.1 × 10−6, OR=9.99, 95% CI: 3.84–27.8). The linked CDA c.−92A>G and CDA c.−451C>T variants predicted grade 2–4 diarrhoea (P=0.0055, OR=2.3, 95% CI: 1.3–4.2 and P=0.0082, OR=2.3, 95% CI: 1.3–4.2, respectively).Conclusion:We have identified a panel of clinically useful pharmacogenetic markers predicting toxicity to fluoropyrimidine therapy. Dose reduction should be considered in patients carrying these sequence variants.

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

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These tables list both published and a number of unpublished mutations in genes associated with early onset defects in mitochondrial DNA (mtDNA) maintenance including C10orf2, SUCLG1, SUCLA2, TYMP, RRM2B, MPV17, DGUOK and TK2. The list should not be taken as evidence that any particular mutation is pathogenic. We have included genes known to cause mtDNA depletion, excluding POLG1, because of the existing database (http://tools.niehs.nih.gov/polg/). We have also excluded mutations in C10orf2 associated with dominant adult onset disorders.

Identification of polymorphisms that influence pemetrexed tolerability could lead to individualised treatment regimens and improve quality of life. Twenty-eight polymorphisms within eleven candidate genes were genotyped using the Illumina Human Exome v1.1 BeadChip and tested for their association with the clinical outcomes of non-small cell lung cancer and mesothelioma patients receiving pemetrexed/platinum doublet chemotherapy (n=136). GGH rs11545078 was associated with a reduced incidence of grade ⩾3 toxicity within the first four cycles of therapy (odds ratio (OR) 0.25, P=0.018), as well as reduced grade ⩾3 haematological toxicity (OR 0.13, P=0.048). DHFR rs1650697 conferred an increased risk of grade ⩾3 toxicity (OR 2.14, P=0.034). Furthermore, FOLR3 rs61734430 was associated with an increased likelihood of disease progression at mid-treatment radiological evaluation (OR 4.05, P=0.023). Polymorphisms within SLC19A1 (rs3788189, rs1051298 and rs914232) were associated with overall survival. This study confirms previous pharmacogenetic associations and identifies novel markers of pemetrexed toxicity.