Lateralized declarative-like memory for conditional spatial information in domestic chicks (Gallus gallus)

Declarative memory is an explicit, long-term memory system, used in generalization and categorization processes and to make inferences and to predict probable outcomes in novel situations. Animals have been proven to possess a similar declarative-like memory system. Here, we investigated declarative-like memory representations in young chicks, assessing the roles of the two hemispheres in memory recollection. Chicks were exposed for three consecutive days to two different arenas (blue/yellow), where they were presented with two panels, each depicting a different stimulus (cross/square). Only one of the two stimuli was rewarded, i.e., it hid a food reward. The position (left/right) of the rewarded stimulus remained constant within the same arena, but it differed between the two arenas (e.g., reward always on the left in the blue context and on the right in the yellow one). At test, both panels depicted the rewarded stimulus, thus chicks had to remember food position depending on the previously experienced contextual rule. Both binocular and right-eye monocularly-tested chicks correctly located the reward, whereas left-eye monocularly-tested chicks performed at the chance level. We showed that declarative-like memory of integrated information is available at early stages of development, and it is associated with a left hemisphere dominance

Caught you: threats to confidentiality due to the public release of large-scale genetic data sets

<p>Abstract</p> <p>Background</p> <p>Large-scale genetic data sets are frequently shared with other research groups and even released on the Internet to allow for secondary analysis. Study participants are usually not informed about such data sharing because data sets are assumed to be anonymous after stripping off personal identifiers.</p> <p>Discussion</p> <p>The assumption of anonymity of genetic data sets, however, is tenuous because genetic data are intrinsically self-identifying. Two types of re-identification are possible: the "Netflix" type and the "profiling" type. The "Netflix" type needs another small genetic data set, usually with less than 100 SNPs but including a personal identifier. This second data set might originate from another clinical examination, a study of leftover samples or forensic testing. When merged to the primary, unidentified set it will re-identify all samples of that individual.</p> <p>Even with no second data set at hand, a "profiling" strategy can be developed to extract as much information as possible from a sample collection. Starting with the identification of ethnic subgroups along with predictions of body characteristics and diseases, the asthma kids case as a real-life example is used to illustrate that approach.</p> <p>Summary</p> <p>Depending on the degree of supplemental information, there is a good chance that at least a few individuals can be identified from an anonymized data set. Any re-identification, however, may potentially harm study participants because it will release individual genetic disease risks to the public.</p

Public preferences for digital health data sharing: Discrete choice experiment study in 12 european countries

Background: With new technologies, health data can be collected in a variety of different clinical, research, and public health contexts, and then can be used for a range of new purposes. Establishing the public s views about digital health data sharing is essential for policy makers to develop effective harmonization initiatives for digital health data governance at the European level. Objective: This study investigated public preferences for digital health data sharing. Methods: A discrete choice experiment survey was administered to a sample of European residents in 12 European countries (Austria, Denmark, France, Germany, Iceland, Ireland, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) from August 2020 to August 2021. Respondents answered whether hypothetical situations of data sharing were acceptable for them. Each hypothetical scenario was defined by 5 attributes ("data collector," "data user," "reason for data use," "information on data sharing and consent," and "availability of review process"), which had 3 to 4 attribute levels each. A latent class model was run across the whole data set and separately for different European regions (Northern, Central, and Southern Europe). Attribute relative importance was calculated for each latent class s pooled and regional data sets. Results: A total of 5015 completed surveys were analyzed. In general, the most important attribute for respondents was the availability of information and consent during health data sharing. In the latent class model, 4 classes of preference patterns were identified. While respondents in 2 classes strongly expressed their preferences for data sharing with opposing positions, respondents in the other 2 classes preferred not to share their data, but attribute levels of the situation could have had an impact on their preferences. Respondents generally found the following to be the most acceptable: A national authority or academic research project as the data user; being informed and asked to consent; and a review process for data transfer and use, or transfer only. On the other hand, collection of their data by a technological company and data use for commercial communication were the least acceptable. There was preference heterogeneity across Europe and within European regions. Conclusions: This study showed the importance of transparency in data use and oversight of health-related data sharing for European respondents. Regional and intraregional preference heterogeneity for "data collector," "data user," "reason," "type of consent," and "review" calls for governance solutions that would grant data subjects the ability to control their digital health data being shared within different contexts. These results suggest that the use of data without consent will demand weighty and exceptional reasons. An interactive and dynamic informed consent model combined with oversight mechanisms may be a solution for policy initiatives aiming to harmonize health data use across Europe

Genetic Testing in Parkinson's Disease

Genetic testing for persons with Parkinson's disease is becoming increasingly common. Significant gains have been made regarding genetic testing methods, and testing is becoming more readily available in clinical, research, and direct-to-consumer settings. Although the potential utility of clinical testing is expanding, there are currently no proven gene-targeted therapies, but clinical trials are underway. Furthermore, genetic testing practices vary widely, as do knowledge and attitudes of relevant stakeholders. The specter of testing mandates financial, ethical, and physician engagement, and there is a need for guidelines to help navigate the myriad of challenges. However, to develop guidelines, gaps and controversies need to be clearly identified and analyzed. To this end, we first reviewed recent literature and subsequently identified gaps and controversies, some of which were partially addressed in the literature, but many of which are not well delineated or researched. Key gaps and controversies include: (1) Is genetic testing appropriate in symptomatic and asymptomatic individuals without medical actionability? (2) How, if at all, should testing vary based on ethnicity? (3) What are the long-term outcomes of consumer- and research-based genetic testing in presymptomatic PD? (4) What resources are needed for clinical genetic testing, and how is this impacted by models of care and cost-benefit considerations? Addressing these issues will help facilitate the development of consensus and guidelines regarding the approach and access to genetic testing and counseling. This is also needed to guide a multidisciplinary approach that accounts for cultural, geographic, and socioeconomic factors in developing testing guidelines.</p

Sharing health-related data:A privacy test?

Greater sharing of potentially sensitive data raises important ethical, legal and social issues (ELSI), which risk hindering and even preventing useful data sharing if not properly addressed. One such important issue is respecting the privacy-related interests of individuals whose data are used in genomic research and clinical care. As part of the Global Alliance for Genomics and Health (GA4GH), we examined the ELSI status of health-related data that are typically considered ‘sensitive’ in international policy and data protection laws. We propose that ‘tiered protection’ of such data could be implemented in contexts such as that of the GA4GH Beacon Project to facilitate responsible data sharing. To this end, we discuss a Data Sharing Privacy Test developed to distinguish degrees of sensitivity within categories of data recognised as ‘sensitive’. Based on this, we propose guidance for determining the level of protection when sharing genomic and health-related data for the Beacon Project and in other international data sharing initiatives

The genetic study of three population microisolates in South Tyrol (MICROS): study design and epidemiological perspectives

<p>Abstract</p> <p>Background</p> <p>There is increasing evidence of the important role that small, isolated populations could play in finding genes involved in the etiology of diseases. For historical and political reasons, South Tyrol, the northern most Italian region, includes several villages of small dimensions which remained isolated over the centuries.</p> <p>Methods</p> <p>The MICROS study is a population-based survey on three small, isolated villages, characterized by: old settlement; small number of founders; high endogamy rates; slow/null population expansion. During the stage-1 (2002/03) genealogical data, screening questionnaires, clinical measurements, blood and urine samples, and DNA were collected for 1175 adult volunteers. Stage-2, concerning trait diagnoses, linkage analysis and association studies, is ongoing. The selection of the traits is being driven by expert clinicians. Preliminary, descriptive statistics were obtained. Power simulations for finding linkage on a quantitative trait locus (QTL) were undertaken.</p> <p>Results</p> <p>Starting from participants, genealogies were reconstructed for 50,037 subjects, going back to the early 1600s. Within the last five generations, subjects were clustered in one pedigree of 7049 subjects plus 178 smaller pedigrees (3 to 85 subjects each). A significant probability of familial clustering was assessed for many traits, especially among the cardiovascular, neurological and respiratory traits. Simulations showed that the MICROS pedigree has a substantial power to detect a LOD score ≥ 3 when the QTL specific heritability is ≥ 20%.</p> <p>Conclusion</p> <p>The MICROS study is an extensive, ongoing, two-stage survey aimed at characterizing the genetic epidemiology of Mendelian and complex diseases. Our approach, involving different scientific disciplines, is an advantageous strategy to define and to study population isolates. The isolation of the Alpine populations, together with the extensive data collected so far, make the MICROS study a powerful resource for the study of diseases in many fields of medicine. Recent successes and simulation studies give us confidence that our pedigrees can be valuable both in finding new candidates loci and to confirm existing candidate genes.</p

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets