Exome sequencing utility in defining the genetic landscape of hearing loss and novel-gene discovery in Iran

Hearing loss (HL) is one of the most common sensory defects affecting more than 466 million individuals worldwide. It is clinically and genetically heterogeneous with over 120 genes causing non-syndromic HL identified to date. Here, we performed exome sequencing (ES) on a cohort of Iranian families with no disease-causing variants in known deafness-associated genes after screening with a targeted gene panel. We identified likely causal variants in 20 out of 71 families screened. Fifteen families segregated variants in known deafness-associated genes. Eight families segregated variants in novel candidate genes for HL: DBH, TOP3A, COX18, USP31, TCF19, SCP2, TENM1, and CARMIL1. In the three of these families, intrafamilial locus heterogeneity was observed with variants in both known and novel candidate genes. In aggregate, we were able to identify the underlying genetic cause of HL in nearly 30 of our study cohort using ES. This study corroborates the observation that high-throughput DNA sequencing in populations with high rates of consanguineous marriages represents a more appropriate strategy to elucidate the genetic etiology of heterogeneous conditions such as HL. © 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Lt

I Piani di Comunicazione nei progetti di Educazione Sanitaria lombardi 2003-2004

Qualsiasi modello di progettazione di qualità prevede un piano di comunicazione riconducibile genericamente ad aspetti di: a) comunicazione esterna e di marketing = destinatari: opinione pubblica, portatori d’interesse, clienti effettivi e potenziali; obiettivo: far conoscere missioni ed azioni, creare goodwill, stabilire relazioni durature con i clienti; b) comunicazione interna = destinatari: dirigenza, operatori, collaboratori; obiettivo: promuovere coinvolgimento, cooperazione, miglioramento, riorientamento culturale. Tale visione, declinata con le dovute specificità di contesto, risulta essenziale anche nel campo della Educazione Sanitaria, intesa come strumento di comunicazione nell’ambito di processi di Promozione della Salute. L’Università di Pavia ha curato, per la DG Sanità di Regione Lombardia, il censimento e la valutazione dei progetti 2003-2004 di Educazione Sanitaria realizzati dalle ASL lombarde. E’ stata valutata la presenza/ assenza/correttezza/completezza dei seguenti aspetti: anagrafica; alleanze esterne; analisi contesto; criteri di scelta dei destinatari; obiettivi ed indicatori; pianificazione di: valutazione, programmazione, comunicazione; costi; risultati; materiali di approfondimento. Da una prima disamina dei dati rilevati si evidenziano criticità riferite ai Piani di Comunicazione. Nello strumento di rilevazione utilizzato nell’indagine, si richiedeva la descrizione di destinatari, strumenti e modalità di diffusione in riferimento al progetto. Nel 62 % dei progetti censiti sono presenti dati riferiti al Piano di Comunicazione. Una prima criticità è riferita ai destinatari che sono nel 87,5 % dei casi esterni (prevalentemente i destinatari del progetto di Educazione Sanitaria) e solo il 12,5 % li individua anche all’interno (azienda). Questo dato può essere letto come possibile segnale di una inadeguata cultura di confronto/condivisione, nonché di una bassa visibilità in ambito aziendale di quanto agito in tema di Educazione Sanitaria. Appare come ulteriore criticità che solo nel 38% si ritrovano indicate tutte e tre le componenti (destinatari, modalità e strumenti), dato che rende ipotizzabile una scarsa propensione ad un approccio pianificato di questo importante step progettuale

Competitive island cooperative neuro - evolution of feedforward networks for time series prediction

Problem decomposition, is vital in employing cooperative coevolution for neuro-evolution. Different problem decomposition methods have features that can be exploited through competition and collaboration. Competitive island cooperative coevolution (CICC) implements decomposition methods as islands that compete and collaborate at different phases of evolution. They have been used for training recurrent neural networks for time series problems. In this paper, we apply CICC for training feedforward networks for time series problems and compare their performance. The results show that the proposed approach has improved the results when compared to standalone cooperative coevolution and shows competitive results when compared to related methods from the literature

Coevolutionary feature selection and reconstruction in neuro - evolution for time series prediction

Feature reconstruction of time series problems produces reconstructed state-space vectors that are used for training machine learning methods such as neural networks. Recently, much consideration has been given to employing competitive methods in improving cooperative neuro-evolution of neural networks for time series predictions. This paper presents a competitive feature selection and reconstruction method that enforces competition in cooperative neuro-evolution using two different reconstructed feature vectors generated from single time series. Competition and collaboration of the two datasets are done using two different islands that exploit their strengths while eradicating their weaknesses. The proposed approach has improved results for some of the benchmark datasets when compared to standalone methods from the literature

Reverse neuron level decomposition for cooperative neuro - evolution of feedforward networks for time series prediction

A major challenge in cooperative neuro-evolution is to find an efficient problem decomposition that takes into account architectural properties of the neural network and the training problem. In the past, neuron and synapse Level decomposition methods have shown promising results for time series problems, howsoever, the search for the optimal method remains. In this paper, a problem decomposition method, that is based on neuron level decomposition is proposed that features a reverse encoding scheme. It is used for training feedforward networks for time series prediction. The results show that the proposed method has improved performance when compared to related problem decomposition methods and shows competitive results when compared to related methods in the literature

Characterising the spectrum of autosomal recessive hereditary hearing loss in Iran

Background Countries with culturally accepted consanguinity provide a unique resource for the study of rare recessively inherited genetic diseases. Although hereditary hearing loss (HHL) is not uncommon, it is genetically heterogeneous, with over 85 genes causally implicated in non-syndromic hearing loss (NSHL). This heterogeneity makes many gene-specific types of NSHL exceedingly rare. We sought to define the spectrum of autosomal recessive HHL in Iran by investigating both common and rarely diagnosed deafness-causing genes. Design Using a custom targeted genomic enrichment (TGE) panel, we simultaneously interrogated all known genetic causes of NSHL in a cohort of 302 GJB2- negative Iranian families. Results We established a genetic diagnosis for 67 of probands and their families, with over half of all diagnoses attributable to variants in five genes: SLC26A4, MYO15A, MYO7A, CDH23 and PCDH15. As a reflection of the power of consanguinity mapping, 26 genes were identified as causative for NSHL in the Iranian population for the first time. In total, 179 deafness-causing variants were identified in 40 genes in 201 probands, including 110 novel single nucleotide or small insertion-deletion variants and three novel CNV. Several variants represent founder mutations. Conclusion This study attests to the power of TGE and massively parallel sequencing as a diagnostic tool for the evaluation of hearing loss in Iran, and expands on our understanding of the genetics of HHL in this country. Families negative for variants in the genes represented on this panel represent an excellent cohort for novel gene discovery

Distinct genetic variation and heterogeneity of the Iranian population

Iran, despite its size, geographic location and past cultural influence, has largely been a blind spot for human population genetic studies. With only sparse genetic information on the Iranian population available, we pursued its genome-wide and geographic characterization based on 1021 samples from eleven ethnic groups. We show that Iranians, while close to neighboring populations, present distinct genetic variation consistent with long-standing genetic continuity, harbor high heterogeneity and different levels of consanguinity, fall apart into a cluster of similar groups and several admixed ones and have experienced numerous language adoption events in the past. Our findings render Iran an important source for human genetic variation in Western and Central Asia, will guide adequate study sampling and assist the interpretation of putative disease-implicated genetic variation. Given Iran�s internal genetic heterogeneity, future studies will have to consider ethnic affiliations and possible admixture. © 2019 Mehrjoo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited