PedHunter 2.0 and its usage to characterize the founder structure of the Old Order Amish of Lancaster County

<p>Abstract</p> <p>Background</p> <p>Because they are a closed founder population, the Old Order Amish (OOA) of Lancaster County have been the subject of many medical genetics studies. We constructed four versions of Anabaptist Genealogy Database (AGDB) using three sources of genealogies and multiple updates. In addition, we developed PedHunter, a suite of query software that can solve pedigree-related problems automatically and systematically.</p> <p>Methods</p> <p>We report on how we have used new features in PedHunter to quantify the number and expected genetic contribution of founders to the OOA. The queries and utility of PedHunter programs are illustrated by examples using AGDB in this paper. For example, we calculated the number of founders expected to be contributing genetic material to the present-day living OOA and estimated the mean relative founder representation for each founder. New features in PedHunter also include pedigree trimming and pedigree renumbering, which should prove useful for studying large pedigrees.</p> <p>Results</p> <p>With PedHunter version 2.0 querying AGDB version 4.0, we identified 34,160 presumed living OOA individuals and connected them into a 14-generation pedigree descending from 554 founders (332 females and 222 males) after trimming. From the analysis of cumulative mean relative founder representation, 128 founders (78 females and 50 males) accounted for over 95% of the mean relative founder contribution among living OOA descendants.</p> <p>Discussion/Conclusions</p> <p>The OOA are a closed founder population in which a modest number of founders account for the genetic variation present in the current OOA population. Improvements to the PedHunter software will be useful in future studies of both the OOA and other populations with large and computerized genealogies.</p

αA-crystallin R49Cneo mutation influences the architecture of lens fiber cell membranes and causes posterior and nuclear cataracts in mice

<p>Abstract</p> <p>Background</p> <p>αA-crystallin (CRYAA/HSPB4), a major component of all vertebrate eye lenses, is a small heat shock protein responsible for maintaining lens transparency. The R49C mutation in the αA-crystallin protein is linked with non-syndromic, hereditary human cataracts in a four-generation Caucasian family.</p> <p>Methods</p> <p>This study describes a mouse cataract model generated by insertion of a neomycin-resistant (neo^r) gene into an intron of the gene encoding mutant R49C αA-crystallin. Mice carrying the neo^rgene and wild-type <it>Cryaa </it>were also generated as controls. Heterozygous knock-in mice containing one wild type gene and one mutated gene for αA-crystallin (WT/R49C^neo) and homozygous knock-in mice containing two mutated genes (R49C^neo/R49C^neo) were compared.</p> <p>Results</p> <p>By 3 weeks, WT/R49C^neomice exhibited large vacuoles in the cortical region 100 μm from the lens surface, and by 3 months posterior and nuclear cataracts had developed. WT/R49C^neomice demonstrated severe posterior cataracts at 9 months of age, with considerable posterior nuclear migration evident in histological sections. R49C^neo/R49C^neomice demonstrated nearly complete lens opacities by 5 months of age. In contrast, R49C mice in which the neo^rgene was deleted by breeding with CreEIIa mice developed lens abnormalities at birth, suggesting that the neo^rgene may suppress expression of mutant R49C αA-crystallin protein.</p> <p>Conclusion</p> <p>It is apparent that modification of membrane and cell-cell interactions occurs in the presence of the αA-crystallin mutation and rapidly leads to lens cell pathology <it>in vivo</it>.</p

Using a community-based definition of poverty for targeting poor households for premium subsidies in the context of a community health insurance in Burkina Faso

Background: One of the biggest challenges in subsidizing premiums of poor households for community health insurance is the identification and selection of these households. Generally, poverty assessments in developing countries are based on monetary terms. The household is regarded as poor if its income or consumption is lower than a predefined poverty cut-off. These measures fail to recognize the multi-dimensional character of poverty, ignoring community members? perception and understanding of poverty, leaving them voiceless and powerless in the identification process. Realizing this, the steering committee of Nouna's health insurance devised a method to involve community members to better define `perceived? poverty, using this as a key element for the poor selection. The community-identified poor were then used to effectively target premium subsidies for the insurance scheme. Methods: The study was conducted in the Nouna's Health District located in northwest Burkina Faso. Participants in each village were selected to take part in focus-group discussions (FGD) organized in 41 villages and 7 sectors of Nouna's town to discuss criteria and perceptions of poverty. The discussions were audio recorded, transcribed and analyzed in French using the software NVivo 9. Results: From the FGD on poverty and the subjective definitions and perceptions of the community members, we found that poverty was mainly seen as scarcity of basic needs, vulnerability, deprivation of capacities, powerlessness, voicelessness, indecent living conditions, and absence of social capital and community networks for support in times of need. Criteria and poverty groups as described by community members can be used to identify poor who can then be targeted for subsidies. Conclusion: Policies targeting the poorest require the establishment of effective selection strategies. These policies are well-conditioned by proper identification of the poor people. Community perceptions and criteria of poverty are grounded in reality, to better appreciate the issue. It is crucial to take these perceptions into account in undertaking community development actions which target the poor. For most community-based health insurance schemes with limited financial resources, using a community-based definition of poverty in the targeting of the poorest might be a less costly alternative