Alpha-1 Antitrypsin PI M Heterozygotes with Rare Variants: Do They Need a Clinical and Functional Follow-Up?

(1) Background: Few data are available on the risk of airway dysfunction in protease inhibitor (PI*) M heterozygotes carrying rare null or deficient allelic variants of the gene SERPINA-1 (PI*MR). (2) Methods: In this observational study, in a cohort of PI*MR heterozygotes, we evaluated respiratory functional parameters at baseline and at one-year follow-up. Moreover, we compared such parameters with those of the PI*MZ and PI*MS patients. (3) Results: A total of 60 patients were recruited; 35 PI*MR, 11 PI*MZ and 14 PI*MS. At the annual follow-up, the PI*MR and PI*MZ patients demonstrated a significantly higher FEV1 decline than the PI*MS group (p = 0.04 and p = 0.018, respectively). The PI*MR patients showed a significant increase in DLCO annual decline in comparison with the PI*MS group (p = 0.02). At baseline, the PI*MR smoking patients, compared with nonsmokers, showed statistically significant lower values of FEV1, FEV1/FVC and DLCO (p = 0.0004, p < 0.0001, p = 0.007, respectively) and, at the one-year follow-up, they displayed a significantly higher FEV1 and DLCO decline (p = 0.0022, p = 0.011, respectively). PI*MR heterozygotes with COPD showed a significantly higher FEV1, FEV1/FVC and DLCO annual decline in comparison with healthy PI*MR (p = 0.0083, p = 0.043, p = 0.041). (4) Conclusions: These results suggest that PI*MR heterozygotes, particularly smokers with COPD, have a greater annual decline in respiratory functional parameters and need to be monitored.

From genetic associations to functional studies in multiple sclerosis

Genetic screens steadily reveal more loci that show robust associations to complex human diseases, including multiple sclerosis (MS). Although some of the identified genetic variants are easily interpreted into a biological function, most of the genetic associations are frequently challenging to interpret. Underlying these difficulties is the fact that chip-based assays typically detect single nucleotide polymorphisms (SNPs) representative of a stretch of DNA containing many genomic variants in linkage disequilibrium. Furthermore, a large proportion of the SNPs with strongest association to MS are located in regions of the DNA that do not directly code for proteins. Here we discuss challenges faced by MS researchers to follow up the large-scale genetic screens that have been published over the past years in search of functional consequences of the identified MS-associated SNPs. We discuss experimental design, tools and methods that may provide the much-needed biological insights in both disease etiology and disease manifestations.

Functional annotation of putative regulatory elements at cancer susceptibility Loci

Most cancer-associated genetic variants identified from genome-wide association studies (GWAS) do not obviously change protein structure, leading to the hypothesis that the associations are attributable to regulatory polymorphisms. Translating genetic associations into mechanistic insights can be facilitated by knowledge of the causal regulatory variant (or variants) responsible for the statistical signal. Experimental validation of candidate functional variants is onerous, making bioinformatic approaches necessary to prioritize candidates for laboratory analysis. Thus, a systematic approach for recognizing functional (and, therefore, likely causal) variants in noncoding regions is an important step toward interpreting cancer risk loci. This review provides a detailed introduction to current regulatory variant annotations, followed by an overview of how to leverage these resources to prioritize candidate functional polymorphisms in regulatory regions.