Evolutionary genetics of lactase persistence in Eurasian human populations

Although ability to digest lactose generally declines after weaning in all mammals, in some human populations it persists also in adult individuals, a condition named lactase persistence (LP). Studies on the prevalence of the LP phenotype in worldwide human populations have shown that the frequency of this trait is highly variable in different ethnic groups, appearing to be positively correlated with the importance of milk in the diet. In particular, several single-nucleotide polymorphisms (SNPs) in the proximity of the LCT gene have been proved to be associated with LP. Nevertheless, few studies have till now analyzed genetic variation underlying LP in a wide set of Eurasian populations and, especially, in the Italian one. In the present study, we thus typed 40 SNPs surrounding the LCT gene in more than 1,000 samples from Italian and Arabic peninsulas to investigate patterns of LP-related genetic diversity in two regions which have played a pivotal role in the recent human evolutionary history according to their geographical position and historical/archaeological records. Our results underline a high and complex variability of the explored genomic region in both studied populations. In particular, a clear diversification of Northern Italian groups from the rest of the peninsula, was observed, with the formers being genetically more similar to Northern European populations than to Southern Italians. These observation are consistent with known decreasing pattern of LP from Northern to Southern Italy and suggest the possibility of an independent evolution of LP-associated genotypes in Northern Italy. A similar scenario was observed in the Arabian peninsula, with Dhofari Arabs from Southern Oman and Yemeni clustering together with respect to Arabs from Northern Oman and the subgroup of Omanis of Asian origin which appeared instead to be genetically closer to Europeans than to the rest of Arabic groups.

Molecular genetics of inherited cystic kidney diseases: new diagnostic approaches

Background. Hhereditary cystic kidney diseases are a heterogeneous spectrum of disorders leading to renal failure. Clinical features and family history can help to distinguish the recessive from dominant diseases but the differential diagnosis is difficult due the phenotypic overlap. The molecular diagnosis is often the only way to characterize the different forms. A conventional molecular screening is suitable for small genes but is expensive and time-consuming for large size genes. Next Generation Sequencing (NGS) technologies enables massively parallel sequencing of nucleic acid fragments. Purpose. The first purpose was to validate a diagnostic algorithm useful to drive the genetic screening. The second aim was to validate a NGS protocol of PKHD1 gene. Methods. DNAs from 50 patients were submitted to conventional screening of NPHP1, NPHP5, UMOD, REN and HNF1B genes. 5 patients with known mutations in PKHD1 were submitted to NGS to validate the new method and a not genotyped proband with his parents were analyzed for a diagnostic application. Results. The conventional molecular screening detected 8 mutations: 1) the novel p.E48K of REN in a patient with cystic nephropathy, hyperuricemia, hyperkalemia and anemia; 2) p.R489X of NPHP5 in a patient with Senior Loken Syndrome; 3) pR295C of HNF1B in a patient with renal failure and diabetes.; 4) the NPHP1 deletion in 3 patients with medullar cysts; 5) the HNF1B deletion in a patient with medullar cysts and renal hypoplasia and in a diabetic patient with liver disease. The NGS of PKHD1 detected all known mutations and two additional variants during the validation. The diagnostic NGS analysis identified the patient’s compound heterozygosity with a maternal frameshift mutation and a paternal missense mutation besides a not transmitted paternal missense mutation. Conclusions. The results confirm the validity of our diagnostic algorithm and suggest the possibility to introduce this NGS protocol to clinical practice.

Data management and data analysis in the large European projects GEHA (GEnetics of Healthy Aging) and NU-AGE (NUtrition and AGEing): a bioinformatic approach

The aging process is characterized by the progressive fitness decline experienced at all the levels of physiological organization, from single molecules up to the whole organism. Studies confirmed inflammaging, a chronic low-level inflammation, as a deeply intertwined partner of the aging process, which may provide the “common soil” upon which age-related diseases develop and flourish. Thus, albeit inflammation per se represents a physiological process, it can rapidly become detrimental if it goes out of control causing an excess of local and systemic inflammatory response, a striking risk factor for the elderly population. Developing interventions to counteract the establishment of this state is thus a top priority. Diet, among other factors, represents a good candidate to regulate inflammation. Building on top of this consideration, the EU project NU-AGE is now trying to assess if a Mediterranean diet, fortified for the elderly population needs, may help in modulating inflammaging. To do so, NU-AGE enrolled a total of 1250 subjects, half of which followed a 1-year long diet, and characterized them by mean of the most advanced –omics and non –omics analyses. The aim of this thesis was the development of a solid data management pipeline able to efficiently cope with the results of these assays, which are now flowing inside a centralized database, ready to be used to test the most disparate scientific hypotheses. At the same time, the work hereby described encompasses the data analysis of the GEHA project, which was focused on identifying the genetic determinants of longevity, with a particular focus on developing and applying a method for detecting epistatic interactions in human mtDNA. Eventually, in an effort to propel the adoption of NGS technologies in everyday pipeline, we developed a NGS variant calling pipeline devoted to solve all the sequencing-related issues of the mtDNA.