Genetic Population Structure Analysis in New Hampshire Reveals Eastern European Ancestry

Genetic structure due to ancestry has been well documented among many divergent human populations. However, the ability to associate ancestry with genetic substructure without using supervised clustering has not been explored in more presumably homogeneous and admixed US populations. The goal of this study was to determine if genetic structure could be detected in a United States population from a single state where the individuals have mixed European ancestry. Using Bayesian clustering with a set of 960 single nucleotide polymorphisms (SNPs) we found evidence of population stratification in 864 individuals from New Hampshire that can be used to differentiate the population into six distinct genetic subgroups. We then correlated self-reported ancestry of the individuals with the Bayesian clustering results. Finnish and Russian/Polish/ Lithuanian ancestries were most notably found to be associated with genetic substructure. The ancestral results were further explained and substantiated using New Hampshire census data from 1870 to 1930 when the largest waves of European immigrants came to the area. We also discerned distinct patterns of linkage disequilibrium (LD) between the genetic groups in the growth hormone receptor gene (GHR). To our knowledge, this is the first time such an investigation has uncovered a strong link between genetic structure and ancestry in what would otherwise be considered a homogenous US population

Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort

Abstract A genome-wide, whole brain approach to investigate genetic effects on neuroimaging phenotypes for identifying quantitative trait loci is described. The Alzheimer's Disease Neuroimaging Initiative 1.5 T MRI and genetic dataset was investigated using voxel-based morphometry (VBM) and FreeSurfer parcellation followed by genome-wide association studies (GWAS). One hundred fortytwo measures of grey matter (GM) density, volume, and cortical thickness were extracted from baseline scans. GWAS, using PLINK, were performed on each phenotype using quality-controlled 1 Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (http://www.loni.ucla.edu/ADNI). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. ADNI investigators include (complete listing available at http://www.loni.ucla.edu/ADNI/Collaboration/ADNI_Authorship_list.pdf). NIH Public Access Author Manuscript Neuroimage. Author manuscript; available in PMC 2010 November 1. Published in final edited form as: Neuroimage. maps were used to analyze the GWAS results and associations are reported at two significance thresholds (p<10 −7 and p<10 −6 ). As expected, SNPs in the APOE and TOMM40 genes were confirmed as markers strongly associated with multiple brain regions. Other top SNPs were proximal to the EPHA4, TP63 and NXPH1 genes. Detailed image analyses of rs6463843 (flanking NXPH1) revealed reduced global and regional GM density across diagnostic groups in TT relative to GG homozygotes. Interaction analysis indicated that AD patients homozygous for the T allele showed differential vulnerability to right hippocampal GM density loss. NXPH1 codes for a protein implicated in promotion of adhesion between dendrites and axons, a key factor in synaptic integrity, the loss of which is a hallmark of AD. A genome-wide, whole brain search strategy has the potential to reveal novel candidate genes and loci warranting further investigation and replication

Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort

ABSTRACT A genome-wide, whole brain approach to investigate genetic effects on neuroimaging phenotypes for identifying quantitative trait loci is described. The Alzheimer's Disease Neuroimaging Initiative 1.5T MRI and genetic dataset was investigated using voxel-based morphometry (VBM) and FreeSurfer parcellation followed by genome wide association studies (GWAS). 142 measures of grey matter (GM) density, volume, and cortical thickness were extracted from baseline scans. GWAS, using PLINK, were performed on each phenotype using quality controlled genotype and scan data including 530,992 of 620,903 single nucleotide polymorphisms (SNPs) and 733 of 818 participants (175 AD, 354 amnestic mild cognitive impairment, MCI, and 204 healthy controls, HC). Hierarchical clustering and heat maps were used to analyze the GWAS results and associations are reported at two significance thresholds (p<10 -7 and p<10 -6 ). As expected, SNPs in the APOE and TOMM40 genes were confirmed as markers strongly associated with multiple brain regions. Other top SNPs were proximal to the EPHA4, TP63 and NXPH1 genes. Detailed image analyses of rs6463843 (flanking NXPH1) revealed reduced global and regional GM density across diagnostic groups in TT relative to GG homozygotes. Interaction analysis indicated that AD patients homozygous for the T allele showed differential vulnerability to right hippocampal GM density loss. NXPH1 codes for a protein implicated in promotion of adhesion between dendrites and axons, a key factor in synaptic integrity, the loss of which is a hallmark of AD. A genome wide, whole brain search strategy has the potential to reveal novel candidate genes and loci warranting further investigation and replication. Shen et al.

Modeling the effects of atmospheric pressure on suicide rates in the USA using geographically weighted regression.

Low atmospheric pressure may increase depression and suicide through inducing hypoxia. Previous studies have not evaluated the geographic variation of this relationship across the United States. Analyses were based on three groupings of age-adjusted completed suicide rates (all suicide, firearm-related suicide, non-firearm-related suicide) from 2286 counties in the United States. Multiple regression was used to determine the overall relationship between atmospheric pressure and completed suicide rates. Geographically weighted regression (GWR) models were used to obtain local coefficient estimates. A negative correlation between atmospheric pressure and completed suicide rates was observed for all three suicide groupings (p-value <0.0001). Significant, negative GWR coefficient estimates were located in the West and Northeast for the all suicides and firearm-related suicides, and in the Midwest for non-firearm-related suicides

Geospatial and Temporal Associations between Increases in Opioid Deaths, Socioeconomics, and Rates of Sexually Transmitted Infections in the Northeast United States 2012–2017

With the introduction of fentanyl to illegal markets in 2013 and an overall rise in rates of synthetic opioid use, opioid-related deaths have increased significantly. A similar trend has been observed for sexually transmitted infections, homicides, and poor mental health outcomes. In this paper, we explore the spatiotemporal relationship between opioid death rates and sexually transmitted infection (STI) rates in counties from the Northeast region of the United States between the years 2012&ndash;2017. We hypothesized that rates for gonorrhea, chlamydia, and human immunodeficiency virus (HIV) would all be positively associated with opioid death rates and that there would be a similar association between the STI rates and later time periods relative to earlier time periods. A negative binomial mixed-effects regression model was employed to assess these associations. Contrary to the study hypothesis, opioid death rates were not found to be significantly associated with the STI rates after accounting for other demographic and socioeconomic variables, with the exception of opioid deaths and gonorrhea in urban counties. Additionally, the regression demonstrated a significant association between infection rate and time period beyond the included socioeconomic variables and opioid deaths. Overall, this study indicates that declining sexual health outcomes may parallel rising opioid death, though both trends may be explained by similar underlying factors related to time period

Political and personal reactions to COVID-19 during initial weeks of social distancing in the United States.

ObjectiveTo examine perceptions, behaviors, and impacts surrounding COVID-19 early in the pandemic response.Materials and methodsA cross-sectional survey of 1,030 U.S. adults was administered on March 31st, 2020. This survey examined attitudes toward media, government, and community responses to COVID-19 by political ideology and sociodemographic factors. Knowledge, anxieties, and impacts of COVID-19 were also assessed.ResultsConservatives were more likely to report that COVID-19 was receiving too much media coverage and people were generally overreacting; liberals were more likely to report the government had not done enough in response to the pandemic. Females and those with lower income experienced more COVID-19 related economic anxieties. Those working and with children at home reported higher social, home, and work disruption. Social distancing behaviors were more common among liberals and were associated with increases in depressive symptoms. General knowledge about COVID-19 was widely exhibited across the sample, however, Black and Hispanic respondents were less likely to correctly answer questions about the availability of a vaccine and modes of transmission.ConclusionsPublic health experts should consider the political climate in crafting messaging that appeals to the values of those across the political spectrum. Research on the COVID-19 pandemic should continue to monitor the effects of social distancing on mental health and among vulnerable populations

Personal exposure to fine particulate air pollution while commuting: An examination of six transport modes on an urban arterial roadway.

Traffic-related air pollution in urban areas contributes significantly to commuters' daily PM2.5 exposures, but varies widely depending on mode of commuting. To date, studies show conflicting results for PM2.5 exposures based on mode of commuting, and few studies compare multiple modes of transportation simultaneously along a common route, making inter-modal comparisons difficult. In this study, we examined breathing zone PM2.5 exposures for six different modes of commuting (bicycle, walking, driving with windows open and closed, bus, and light-rail train) simultaneously on a single 2.7 km (1.68 mile) arterial urban route in Salt Lake City, Utah (USA) during peak "rush hour" times. Using previously published minute ventilation rates, we estimated the inhaled dose and exposure rate for each mode of commuting. Mean PM2.5 concentrations ranged from 5.20 μg/m3 for driving with windows closed to 15.21 μg/m3 for driving with windows open. The estimated inhaled doses over the 2.7 km route were 6.83 μg for walking, 2.78 μg for cycling, 1.28 μg for light-rail train, 1.24 μg for driving with windows open, 1.23 μg for bus, and 0.32 μg for driving with windows closed. Similarly, the exposure rates were highest for cycling (18.0 μg/hr) and walking (16.8 μg/hr), and lowest for driving with windows closed (3.7 μg/hr). Our findings support previous studies showing that active commuters receive a greater PM2.5 dose and have higher rates of exposure than commuters using automobiles or public transportation. Our findings also support previous studies showing that driving with windows closed is protective against traffic-related PM2.5 exposure

Characteristics of Study Population.

<p>Testicular cancer cases diagnosed 1991–2003, and age-matched controls.</p