Modeling and Testing for Joint Association Using a Genetic Random Field Model

Substantial progress has been made in identifying single genetic variants predisposing to common complex diseases. Nonetheless, the genetic etiology of human diseases remains largely unknown. Human complex diseases are likely influenced by the joint effect of a large number of genetic variants instead of a single variant. The joint analysis of multiple genetic variants considering linkage disequilibrium (LD) and potential interactions can further enhance the discovery process, leading to the identification of new disease-susceptibility genetic variants. Motivated by the recent development in spatial statistics, we propose a new statistical model based on the random field theory, referred to as a genetic random field model (GenRF), for joint association analysis with the consideration of possible gene-gene interactions and LD. Using a pseudo-likelihood approach, a GenRF test for the joint association of multiple genetic variants is developed, which has the following advantages: 1. considering complex interactions for improved performance; 2. natural dimension reduction; 3. boosting power in the presence of LD; 4. computationally efficient. Simulation studies are conducted under various scenarios. Compared with a commonly adopted kernel machine approach, SKAT, GenRF shows overall comparable performance and better performance in the presence of complex interactions. The method is further illustrated by an application to the Dallas Heart Study.Comment: 17 pages, 4 tables, the paper has been published on Biometric

Occupational welfare against the backdrop of the crisis of the modern welfare state: opportunities and limits of a different model of solidarity

Il presente elaborato analizza il complesso fenomeno del welfare occupazionale nell’ambito della conclamata crisi del moderno Stato sociale. Dapprima, ci si soffermerà sulla genesi del fenomeno, e, nello specifico, sul mutato contesto istituzionale e sociale da cui esso trae origine: allo studio dei principali modelli di welfare state e alla loro ricostruzione storica, si affiancherà l'osservazione delle possibili concause che hanno determinato, nel tempo, l’insorgere di forme di welfare integrativo, parallele, se non anche alternative, a quelle garantite, in via principale, dallo Stato centrale. Nel prosieguo si darà conto della crescente rilevanza assunta dal welfare occupazionale nel contesto politico e aziendale europeo e nazionale, attraverso l’analisi dei più recenti studi sul tema e dei provvedimenti adottati dal Legislatore italiano e dalle parti sociali nell’ultima stagione di rinnovo contrattuale. Al termine della ricostruzione normativa, si procederà alla lettura del fenomeno secondo tre differenti indirizzi interpretativi, con lo scopo di evidenziare le opportunità e i limiti derivanti dall’adozione di un diverso modello di solidarietà sociale e le sue possibili strategie di sviluppo nei diversi ambiti di applicazione. Sulla scorta di tali considerazioni, infine, si collocherà il fenomeno oggetto di studio nel più ampio processo di “innovazione sociale” che investe, pur con marcate criticità, le società contemporanee avanzate: in tal senso, dall’analisi di esempi virtuosi di collaborazione fra diversi attori istituzionali, pubblici e privati, si giungerà ad affermare l’importanza di inquadrare il welfare occupazionale in sistemi circolari e partecipati di gestione del rischio sociale per la creazione di un benessere diffuso e duraturo, che si sviluppi oltre il perimetro aziendale e con la collaborazione di tutta la comunità.This study aims to describe the phenomenon of occupational welfare against the backdrop of the crisis and the transformation of the modern Western welfare state. First of all, we will focus on the genesis of the phenomenon, and, specifically, on the emergence of new social risks that have deeply transformed the institutional and social pattern since the Fordist revolution: beside the study of the main welfare state models and their historical reconstruction, we will observe the possible contributing causes that have determined, over time, the gradual retrenchment of welfare state and the rise of different forms of supplementary welfare. Then, we will zoom in on the growing importance of occupational welfare in the European and national political and business context, through the analysis of the most recent studies on the issue and the measures adopted by the Italian legislator and the social partners in the last collective bargaining season. At the end of the normative reconstruction, the phenomenon will be read according to three different interpretative outlooks, with the aim of highlight limits and opportunities deriving from the adoption of a different model of social solidarity and its possible development strategies in the various fields of application. Ultimately, on the basis of these considerations, we will look at the phenomenon under a broader perspective of "social innovation": by this expression, we define the process encompassing socially innovative policies and actions aimed at overcoming poverty and social exclusion, through a reconfiguration of social and political relations. Moving from the analysis of some virtuous examples of dialectical interplay between public and private institutional actors, the paper concludes stating the importance of embedding occupational welfare in a broader circular and participatory systems of social risk management, through which develop and maximize social well-being, even beyond company policies

Tackling hepatocellular carcinoma with individual or combinatorial immunotherapy approaches.

Abstract Hepatocellular carcinoma (HCC) is the third leading cause of death from cancer globally. Indeed, there is a single drug approved as first-line systemic therapy in advanced unresectable HCC, providing a very limited survival benefit. In earlier stages, 5-year survival rates after surgical and loco-regional therapies are extremely variable depending on the stage of disease. Nevertheless, HCC is considered an immunogenic tumor arising in chronically inflamed livers. In such a scenario, immunotherapy strategies for HCC, in particular combinations including cancer vaccines, may represent a key therapeutic tool to improve clinical outcome in HCC patients. However, a lot of improvement is needed given the disappointing results obtained so far

Familial aggregation of atrial fibrillation in Iceland

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldAIMS: To examine the heritability of atrial fibrillation (AF) in Icelanders, utilizing a nationwide genealogy database and population-based data on AF. AF is a disorder with a high prevalence, which has been known to cluster in families, but the heritability of the common form has not been well defined. METHODS AND RESULTS: The study population included 5269 patients diagnosed since 1987 and age-sex-matched controls randomly selected from the genealogy database. Kinship coefficients (KC), expressed as genealogical index of familiality (GIF = average KC x 100,000), were calculated before and after exclusion of relatives separated by one to five meiotic events. Risk ratios (RR) were calculated for first- to fifth-degree relatives. The average pairwise GIF among patients with AF was 15.9 (mean GIF for controls 13.9, 95%CI = 13.3, 14.4); this declined to 15.4 (mean GIF for controls 13.6, 95%CI = 13.1, 14.2) after exclusion of relatives separated by one meiosis and to 13.7 (mean GIF for controls 12.6, 95%CI = 12.1, 13.2), 12.7 (mean GIF for controls 11.9, 95%CI = 11.4, 12.4), and 11.3 (mean GIF for controls 10.6, 95%CI = 10.1, 11.1) after exclusion of relatives within two, three, and four meioses, respectively (all P<0.00001). RRs among relative pairs also declined incrementally, from 1.77 in first-degree relatives to 1.36, 1.18, 1.10, and 1.05 in second- through fifth-degree relatives (all P<0.001), consistent with the declining proportion of alleles shared identically by descent. When the analysis was limited to subjects diagnosed with AF before the age of 60, first-degree relatives of the AF cases were nearly five times more likely to have AF than the general population. CONCLUSION: AF shows strong evidence of heritability among unselected patients in Iceland, suggesting that there may be undiscovered genetic variants underlying the risk of the common form of AF

Weighted pooling—practical and cost-effective techniques for pooled high-throughput sequencing

Motivation: Despite the rapid decline in sequencing costs, sequencing large cohorts of individuals is still prohibitively expensive. Recently, several sophisticated pooling designs were suggested that can identify carriers of rare alleles in large cohorts with a significantly smaller number of pools, thus dramatically reducing the cost of such large-scale sequencing projects. These approaches use combinatorial pooling designs where each individual is either present or absent from a pool. One can then infer the number of carriers in a pool, and by combining information across pools, reconstruct the identity of the carriers

Gene-based partial least-squares approaches for detecting rare variant associations with complex traits

Genome-wide association studies are largely based on single-nucleotide polymorphisms and rest on the common disease/common variants (single-nucleotide polymorphisms) hypothesis. However, it has been argued in the last few years and is well accepted now that rare variants are valuable for studying common diseases. Although current genome-wide association studies have successfully discovered many genetic variants that are associated with common diseases, detecting associated rare variants remains a great challenge. Here, we propose two partial least-squares approaches to aggregate the signals of many single-nucleotide polymorphisms (SNPs) within a gene to reveal possible genetic effects related to rare variants. The availability of the 1000 Genomes Project offers us the opportunity to evaluate the effectiveness of these two gene-based approaches. Compared to results from a SNP-based analysis, the proposed methods were able to identify some (rare) SNPs that were missed by the SNP-based analysis

Estimating heritability using family and unrelated individuals data

For the family data from Genetic Analysis Workshop 17, we obtained heritability estimates of quantitative traits Q1 and Q4 using the ASSOC program in the S.A.G.E. software package. ASSOC is a family-based method that estimates heritability through the estimation of variance components. The covariate-adjusted mean heritability was 0.650 for Q1 and 0.745 for Q4. For the unrelated individuals data, we estimated the heritability of Q1 as the proportion of total variance that can be accounted for by all single-nucleotide polymorphisms under an additive model. We examined a novel ordinary least-squares method, a naïve restricted maximum-likelihood method, and a calibrated restricted maximum-likelihood method. We applied the different methods to all 200 replicates for Q1. We observed that the ordinary least-squares method yielded many estimates outside the interval [0, 1]. The restricted maximum-likelihood estimates were more stable than the ordinary least-squares estimates. The naïve restricted maximum-likelihood method yielded an average estimate of 0.462 ± 0.1, and the calibrated restricted maximum-likelihood method yielded an average of 0.535 ± 0.121. Our results demonstrate discrepancies in heritability estimates using the family data and the unrelated individuals data

A statistical method for the detection of variants from next-generation resequencing of DNA pools

Motivation: Next-generation sequencing technologies have enabled the sequencing of several human genomes in their entirety. However, the routine resequencing of complete genomes remains infeasible. The massive capacity of next-generation sequencers can be harnessed for sequencing specific genomic regions in hundreds to thousands of individuals. Sequencing-based association studies are currently limited by the low level of multiplexing offered by sequencing platforms. Pooled sequencing represents a cost-effective approach for studying rare variants in large populations. To utilize the power of DNA pooling, it is important to accurately identify sequence variants from pooled sequencing data. Detection of rare variants from pooled sequencing represents a different challenge than detection of variants from individual sequencing