Among all the software packages available for discriminant analyses based on projection to latent structures (PLS-DA) or orthogonal projection to latent structures (OPLS-DA), SIMCA (Umetrics, Umeå Sweden) is the more widely used in the metabolomics field. SIMCA proposes many parameters or tests to assess the quality of the computed model (the number of significant components, R², Q², p_CV-ANOVA, and the permutation test). Significance thresholds for these parameters are strongly application-dependent. Concerning the Q² parameter, a significance threshold of 0.5 is generally admitted. However, during the last few years, many PLS-DA/OPLS-DA models built using SIMCA have been published with Q² values lower than 0.5. The purpose of this opinion note is to point out that, in some circumstances frequently encountered in metabolomics, the values of these parameters strongly depend on the individuals that constitute the validation subsets. As a result of the way in which the software selects members of the calibration and validation subsets, a simple permutation of dataset rows can, in several cases, lead to contradictory conclusions about the significance of the models when a K-fold cross-validation is used. We believe that, when Q² values lower than 0.5 are obtained, SIMCA users should at least verify that the quality parameters are stable towards permutation of the rows in their dataset.

The incidence of hepatocellular carcinoma (HCC) is increasing in Western countries. Although several clinical factors have been identified, many individuals never develop HCC, suggesting a genetic susceptibility. However, to date, only a few single-nucleotide polymorphisms have been reproducibly shown to be linked to HCC onset. A variant (rs738409 C>G, encoding for p.I148M) in the PNPLA3 gene is associated with liver damage in chronic liver diseases. Interestingly, several studies have reported that the minor rs738409[G] allele is more represented in HCC cases in chronic hepatitis C (CHC) and alcoholic liver disease (ALD). However, a significant association with HCC related to CHC has not been consistently observed, and the strength of the association between rs738409 and HCC remains unclear. We performed a meta-analysis of individual participant data including 2,503 European patients with cirrhosis to assess the association between rs738409 and HCC, particularly in ALD and CHC. We found that rs738409 was strongly associated with overall HCC (odds ratio [OR] per G allele, additive model = 1.77; 95% confidence interval [CI]: 1.42-2.19; P = 2.78 × 10⁻⁷). This association was more pronounced in ALD (OR = 2.20; 95% CI: 1.80-2.67; P = 4.71 × 10⁻¹⁵) than in CHC patients (OR = 1.55; 95% CI: 1.03-2.34; P = 3.52 × 10⁻²). After adjustment for age, sex, and body mass index, the variant remained strongly associated with HCC. Conclusion: Overall, these results suggest that rs738409 exerts a marked influence on hepatocarcinogenesis in patients with cirrhosis of European descent and provide a strong argument for performing further mechanistic studies to better understand the role of PNPLA3 in HCC development. (Hepatology 2014;59:2170–2177)