Analysis of High-Risk Pedigrees Identifies 12 Candidate Variants for Alzheimer\u27s Disease

INTRODUCTION: Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants. METHODS: Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer\u27s disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co-segregation to additional affected relatives of the original sequenced pedigree members. RESULTS: AD-affected high-risk cousin pairs contained 564 shared rare variants. Eleven variants spanning 10 genes were prioritized in external datasets: rs201665195 (ABCA7), and rs28933981 (TTR) were previously implicated in AD pathology; rs141402160 (NOTCH3) and rs140914494 (NOTCH3) were previously reported; rs200290640 (PIDD1) and rs199752248 (PIDD1) were present in more than one cousin pair; rs61729902 (SNAP91), rs140129800 (COX6A2, AC026471), and rs191804178 (MUC16) were not present in a longevity cohort; and rs148294193 (PELI3) and rs147599881 (FCHO1) approached significance from analysis of AD-related phenotypes. Three variants were validated via evidence of co-segregation to additional relatives (PELI3, ABCA7, and SNAP91). DISCUSSION: These analyses support ABCA7 and TTR as AD risk genes, expand on previously reported NOTCH3 variant identification, and prioritize seven additional candidate variants

Assessing the Effects of Recent Immigration on Serious Property Crime in Austin, Texas

In this article the authors examine the impact of recent immigration on rates of serious property crime across communities in Austin, Texas. The greater Austin foreign-born population has increased by more than 580 percent since 1980, and Austin is considered a "preemerging" immigrant gateway city to the United States. The changing population dynamics in Austin provide an excellent opportunity to study the effect of recent immigration on crime in a target destination for recent immigrants. Although interest in the relationship between violent crime and immigration to new locales is evidenced by recent studies that show less favorable outcomes for Latinos in new destinations, little attention has been directed to the relationship of recent immigration with serious property crime in new destinations. Negative binomial regression models with corrections for spatial autocorrelation indicate that recent immigration is not associated with an increased rate of burglary, larceny, or motor vehicle theft once important structural predictors of crime are controlled for. © 2013 by Pacific Sociological Association. All rights reserved