Abstract

PurposeMutations in six genes have been associated with achromatopsia (ACHM): CNGA3, CNGB3, PDE6H, PDE6C, GNAT2, and ATF6. ATF6 is the most recent gene to be identified, though thorough phenotyping of this genetic subtype is lacking. Here, we sought to test the hypothesis that ATF6-associated ACHM is a structurally distinct form of congenital ACHM.MethodsSeven genetically confirmed subjects from five nonconsanguineous families were recruited. Foveal hypoplasia and the integrity of the ellipsoid zone (EZ) band (a.k.a., IS/OS) were graded from optical coherence tomography (OCT) images. Images of the photoreceptor mosaic were acquired using confocal and nonconfocal split-detection adaptive optics scanning light ophthalmoscopy (AOSLO). Parafoveal cone and rod density values were calculated and compared to published normative data as well as data from two subjects harboring CNGA3 or CNGB3 mutations who were recruited for comparative purposes. Additionally, nonconfocal dark-field AOSLO images of the retinal pigment epithelium were obtained, with quantitative analysis performed in one subject with ATF6-ACHM.ResultsFoveal hypoplasia was observed in all subjects with ATF6 mutations. Absence of the EZ band within the foveal region (grade 3) or appearance of a hyporeflective zone (grade 4) was seen in all subjects with ATF6 using OCT. There was no evidence of remnant foveal cone structure using confocal AOSLO, although sporadic cone-like structures were seen in nonconfocal split-detection AOSLO. There was a lack of cone structure in the parafovea, in direct contrast to previous reports.ConclusionsOur data demonstrate a near absence of cone structure in subjects harboring ATF6 mutations. This implicates ATF6 as having a major role in cone development and suggests that at least a subset of subjects with ATF6-ACHM have markedly fewer cellular targets for cone-directed gene therapies than do subjects with CNGA3- or CNGB3-ACHM.

Highlights

  • Recent trends in income and wealth distributions in advanced economies, as well as work by economists (e.g., Piketty (2014)) have refocused attention on increasing economic inequality

  • Our analysis of turnover or mobility over recent years, and its relation to the business cycle, is quite different than the approach of Arnott, Bernstein and Wu (2015). Those authors estimate that the wealth of the individuals in the Forbes 400 rose from 13,800 times US per capita GDP in 1982 to 108,000 times US per capita GDP in 2014, but they mostly emphasize the long run turnover in the list, “Instead, we find huge turnover in the names on the list: only 34 names on the inaugural 1982 list remain on the 2014 list, and only 24 names have appeared on all 33 lists.”

  • By analyzing a panel of 12 years of annual Forbes 400 data, spanning either side of the financial crisis, we are able to observe some interesting characteristics of the dynamics of membership in this group of the extremely wealthy

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Summary

Introduction

Recent trends in income and wealth distributions in advanced economies, as well as work by economists (e.g., Piketty (2014)) have refocused attention on increasing economic inequality. As one example of such sectoral differences, the share of wealth associated with real estate rises rapidly duing the boom period of the first part of the sample, and falls after the financial crisis, while the wealth share of technology and telecom as a sector has the opposite pattern Several such aspects of the data are discussed in the data overview section, and we believe this kind of analysis has not been conducted previously for the Forbes 400. Our results for the overall panel suggest mild wealth convergence among the group, business cycle effects in terms of the GDP growth rate, and some additional positive boom-year impacts of being self-made and having an advanced degree. We hope our analysis will point the way to further investigation of these complex dynamics at the extreme top of the wealth distribution

Data Overview
Wealth Inequality among the Wealthiest
Advanced Degrees
Sectors
Being “Self-Made”
Mobility
New Entrants
Turnover
Keeping Wealth
Wealth Dynamics
Econometric Modeling Approach
Estimation Results
Dealing with Truncation
Sectoral Results
Conclusion
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