The Parkinson's disease variant rs356182 regulates neuronal differentiation independently from alpha-synuclein.

One of the most significant risk variants for Parkinson's disease (PD), rs356182, is located at the PD-associated locus near the alpha-synuclein (α-syn) encoding gene, SNCA. SNCA-proximal variants, including rs356182, are thought to function in PD risk through enhancers via allele-specific regulatory effects on SNCA expression. However, this interpretation discounts the complex activity of genetic enhancers and possible non-conical functions of α-syn. Here we investigated a novel risk mechanism for rs356182. We use CRISPR-Cas9 in LUHMES cells, a model for dopaminergic midbrain neurons, to generate precise hemizygous lesions at rs356182. The PD-protective (A/-), PD-risk (G/-) and wild-type (A/G) clones were neuronally differentiated and then compared transcriptionally and morphologically. Among the affected genes was SNCA, whose expression was promoted by the PD-protective allele (A) and repressed in its absence. In addition to SNCA, hundreds of genes were differentially expressed and associated with neurogenesis and axonogenesis-an effect not typically ascribed to α-syn. We also found that the transcription factor FOXO3 specifically binds to the rs356182 A-allele in differentiated LUHMES cells. Finally, we compared the results from the rs356182-edited cells to our previously published knockouts of SNCA and found only minimal overlap between the sets of significant differentially expressed genes. Together, the data implicate a risk mechanism for rs356182 in which the risk-allele (G) is associated with abnormal neuron development, independent of SNCA expression. We speculate that these pathological effects manifest as a diminished population of dopaminergic neurons during development leading to the predisposition for PD later in life.

DNA strand asymmetry generated by CpG hemimethylation has opposing effects on CTCF binding.

CpG methylation generally occurs on both DNA strands and is essential for mammalian development and differentiation. Until recently, hemimethylation, in which only one strand is methylated, was considered to be simply a transitory state generated during DNA synthesis. The discovery that a subset of CCCTC-binding factor (CTCF) binding sites is heritably hemimethylated suggests that hemimethylation might have an unknown biological function. Here we show that the binding of CTCF is profoundly altered by which DNA strand is methylated and by the specific CTCF binding motif. CpG methylation on the motif strand can inhibit CTCF binding by up to 7-fold, whereas methylation on the opposite strand can stimulate binding by up to 4-fold. Thus, hemimethylation can alter binding by up to 28-fold in a strand-specific manner. The mechanism for sensing methylation on the opposite strand requires two critical residues, V454 and S364, within CTCF zinc fingers 7 and 4. Similar to methylation, CpG hydroxymethylation on the motif strand can inhibit CTCF binding by up to 4-fold. However, hydroxymethylation on the opposite strand removes the stimulatory effect. Strand-specific methylation states may therefore provide a mechanism to explain the transient and dynamic nature of CTCF-mediated chromatin interactions.

Alpha-synuclein negatively controls cell proliferation in dopaminergic neurons.

As researchers grapple with the mechanisms and implications of alpha-synuclein (α-syn) in neuropathology, it is often forgotten that the function(s) of α-syn in healthy cells remain largely elusive. Previous work has relied on observing α-syn localization in the cell or using knockout mouse models. Here, we address the specific role of α-syn in human dopaminergic neurons by disrupting its gene (SNCA) in the human dopaminergic neuron cell line, LUHMES. SNCA-null cells were able to differentiate grossly normally and showed modest effects on gene expression. The effects on gene expression were monodirectional, resulting primarily in the significant decrease of expression for 401 genes, implicating them as direct, or indirect positive targets of α-syn. Gene ontological analysis of these genes showed enrichment in terms associated with proliferation, differentiation, and synapse activity. These results add to the tapestry of α-syn biological functions. SIGNIFICANCE STATEMENT: The normal functions of α-syn have remained controversial, despite its clear importance in Parkinson's Disease pathology, where it accumulates in Lewy bodies and contributes to neurodegeneration. Its name implies synaptic and nuclear functions, but how it participates at these locations has not been resolved. Via knock-out experiments in dopaminergic neurons, we implicate α-syn as a functional participant in synapse activity and in proliferation/differentiation, the latter being novel and provide insight into α-syn's role in neuronal development.

Changing the Criminal Justice System Response to Sexual Assault: An Empirical Study of a Participatory Action Research Project.

In jurisdictions throughout the United States, thousands of sexual assault kits (SAKs; also known as a "rape kits") have not been submitted by the police for forensic DNA testing. DNA evidence may be helpful to sexual assault investigations and prosecutions by identifying perpetrators, revealing serial offenders through DNA matches across cases, and exonerating those who have been wrongly accused. This paper describes a longitudinal action research project conducted in Detroit, Michigan after that city discovered approximately 11,000 untested sexual assault kits in a police department storage facility. We conducted a root cause analysis to examine individual, organizational, community, and societal factors that contributed to the development of the rape kit backlog in Detroit. Based on those findings, we implemented and evaluated structural changes to increase staffing, promote kit testing, and retrain police and prosecutors so that cases could be reopened for investigation and prosecution. As we conducted this work, we also studied how this action research project impacted the Detroit criminal justice system. Participating in this project changed stakeholders' attitudes about the utility of research to address community problems, the usefulness of DNA evidence in sexual assault cases, and the impact of trauma on survivors. The results led to new protocols for SAK testing and police investigations, and new state legislation mandating SAK forensic DNA testing.

Predicting physical activity among urban adolescent girls: A test of the health promotion model.

The purpose of this study was to test hypothesized relationships of the health promotion model (HPM) as a means of predicting moderate-to-vigorous physical activity (MVPA) among urban, adolescent girls. A secondary analysis of baseline data from a group randomized controlled trial was conducted. The study involved eight urban schools in the Midwestern United States. The sample included girls (N = 517) in the 5th-8th grades. Data were collected on age, body mass index, pubertal status, enjoyment, self-efficacy, social support, options for physical activity (PA), and commitment to PA. MVPA was measured via accelerometers worn by the girls for 7 days. Structural equation modeling was used to analyze study aims. Mean age of the sample was 11.8 years (standard deviation [SD] = 1.0). Girls attained an average of 3.0 (SD = 1.2) minutes per hour of MVPA. Self-efficacy had a positive direct (ß = .337; p < .001) and total effect (ß = .310; p < .001) on MVPA. Social support and options for PA were not significant predictors of commitment to PA or MVPA. Commitment to PA had a negative but nonsignificant effect (ß = -.056; p = .357) on MVPA. The model predicted 10.1% of the variance in MVPA with 9.6% of the variance predicted by self-efficacy. Limitations include lack of longitudinal analysis and inability to generalize the results to other populations such as boys. PA self-efficacy continues to emerge as a significant predictor of MVPA in the HPM. Continued theory testing is needed to better understand the correlates and determinants of PA among adolescent girls before designing theory-based interventions to promote PA.

How to Right a Wrong: Empirically Evaluating Whether Victim, Offender, and Assault Characteristics can Inform Rape Kit Testing Policies.

Hundreds of thousands of previously untested sexual assault kits (SAKs) have been uncovered in police property storage facilities across the United States, representing a national failure in institutional response to sexual assault. Faced with this discovery, jurisdictions must now decide if and how they should test these kits. Some stakeholders have suggested prioritizing kits for testing by victim, offender, or assault characteristics, based on the belief that these characteristics can predict the likely utility of DNA testing. However, little research has examined the empirical merits of such prioritization. To address this gap in the literature and inform SAK testing policies, we randomly sampled 900 previously untested SAKs from Detroit, MI. The sampled SAKs were submitted for DNA testing, and eligible DNA profiles were entered into Combined DNA Index System (CODIS), the federal DNA database. Police records associated with each SAK were coded for victim, offender, and assault characteristics, and logistic regression analyses were conducted to test whether these characteristics predict which SAKs yield DNA profiles that match ("hit") to other criminal offenses in CODIS. Testing this sample of previously-untested SAKs produced a substantial number of CODIS hits, but few of the tested variables were significant predictors of CODIS hit rate. These findings suggest that testing all previously-unsubmitted kits may generate information that is useful to the criminal justice system, while also potentially addressing the institutional betrayal victims experienced when their kits were ignored.

Parkinson's disease genetic risk in a midbrain neuronal cell line.

In genome-wide association studies of complex diseases, many risk polymorphisms are found to lie in non-coding DNA and likely confer risk through allele-dependent differences in gene regulatory elements. However, because distal regulatory elements can alter gene expression at various distances on linear DNA, the identity of relevant genes is unknown for most risk loci. In Parkinson's disease, at least some genetic risk is likely intrinsic to a neuronal subpopulation of cells in the brain regions affected. In order to compare neuron-relevant methods of pairing risk polymorphisms to target genes as well as to further characterize a single-cell model of a neurodegenerative disease, we used the portionally-dopaminergic, neuronal, mesencephalic-derived cell line LUHMES to dissect differentiation-specific mechanisms of gene expression. We compared genome-wide gene expression in undifferentiated and differentiated cells with genome-wide histone H3K27ac and CTCF-bound regions. Whereas promoters and CTCF binding were largely consistent between differentiated and undifferentiated cells, enhancers were mostly unique. We matched the differentiation-specific appearance or disappearance of enhancers with changes in gene expression and identified 22,057 enhancers paired with 6388 differentially expressed genes by proximity. These enhancers are enriched with at least 13 transcription factor response elements, driving a cluster of genes involved in neurogenesis. We show that differentiated LUHMES cells, but not undifferentiated cells, show enrichment for PD-risk SNPs. Candidate genes for these loci are largely unrelated, though a subset is linked to synaptic vesicle cycling and transport, implying that PD-related disruption of these pathways is intrinsic to dopaminergic neurons.

EATI Island - A virtual-reality-based elder abuse and neglect educational intervention.

Despite high prevalence rates of elder abuse and neglect (EA/N), compliance with mandatory reporting remains low. A lack of practical training on EA/N has been identified as a barrier. This article describes the development, implementation, and evaluation of an innovative virtual-reality-based educational intervention intended to improve EA/N recognition and reporting among nurses and social workers providing in-home services. The educational intervention consisted of two parts, including an introductory course and advanced assessment training in virtual reality. The advanced assessment training was focused on learning to use the QualCare Scale, an instrument used to assess quality of family caregiving. Data was evaluated in terms of user satisfaction, changes in knowledge, and changes in practice. Results indicate that participants were satisfied with the content and format of the training program. Participants made gains in knowledge in identification and had 99% accuracy in their mandatory reporting decisions. Importantly, professionals reported making changes in their daily practice based on knowledge and skills learnt. Evaluation data indicate that this interdisciplinary training program was a satisfactory way to learn that produced changes in knowledge and impacted clinical practice. Few implementation barriers were encountered during this project suggesting it would be replicable.

Physical and genetic-interaction density reveals functional organization and informs significance cutoffs in genome-wide screens.

Genome-wide experiments often measure quantitative differences between treated and untreated cells to identify affected strains. For these studies, statistical models are typically used to determine significance cutoffs. We developed a method termed "CLIK" (Cutoff Linked to Interaction Knowledge) that overlays biological knowledge from the interactome on screen results to derive a cutoff. The method takes advantage of the fact that groups of functionally related interacting genes often respond similarly to experimental conditions and, thus, cluster in a ranked list of screen results. We applied CLIK analysis to five screens of the yeast gene disruption library and found that it defined a significance cutoff that differed from traditional statistics. Importantly, verification experiments revealed that the CLIK cutoff correlated with the position in the rank order where the rate of true positives drops off significantly. In addition, the gene sets defined by CLIK analysis often provide further biological perspectives. For example, applying CLIK analysis retrospectively to a screen for cisplatin sensitivity allowed us to identify the importance of the Hrq1 helicase in DNA crosslink repair. Furthermore, we demonstrate the utility of CLIK to determine optimal treatment conditions by analyzing genome-wide screens at multiple rapamycin concentrations. We show that CLIK is an extremely useful tool for evaluating screen quality, determining screen cutoffs, and comparing results between screens. Furthermore, because CLIK uses previously annotated interaction data to determine biologically informed cutoffs, it provides additional insights into screen results, which supplement traditional statistical approaches.

Activation of rectus capitis posterior major muscles during voluntary retraction of the head in asymptomatic subjects.

OBJECTIVE: The purpose of this study was to assess levels of electromyographic activity measured from rectus capitis posterior major (RCPM) muscles of asymptomatic subjects as their heads moved from a self-defined neutral position to a retracted position. METHODS: A 2 × 2 within-subjects factorial research design was used. Disposable, intramuscular electrodes were used to collect electromyographic data from asymptomatic subjects between the ages of 20 and 40 years old. Data analysis was performed using mixed effects ß regression models. RESULTS: Activation of RCPM muscles was found to significantly increase (P < .0001) as the head moved from a self-defined neutral position to a retracted position. Rectus capitis posterior major muscle activation levels, measured as a function of head position, have not been previously reported. CONCLUSIONS: The findings from this study showed that RCPM muscle activation significantly increases during voluntary retraction of the head.

Gene expression asymmetry in Parkinson's Disease; variation of CCT and BEX gene expression levels are correlated with hemisphere specific severity.

Parkinson's Disease (PD) develops unilaterally, which may be related to brain hemispheric differences in gene expression. Here we measured bulk RNA-seq levels in neuronal nuclei obtained from prefrontal cortex postmortem brain samples from males and females with PD and from healthy controls. Left and right hemispheres from each brain were related the side of symptom onset and compared. We employed two a priori approaches; first we identified genes differentially expressed between PD and controls and between left vs right PD brain hemispheres. Second, we examined the presence of, and correlates to, variable asymmetry seen in candidate PD differentially expressed genes. We found large variation among individuals with PD, and PD stratification by gene expression similarity was required for patterns of genetic asymmetry to emerge. For a subset of PD brains, hemispherical variation of CCT and BEX gene levels correlated with the side of PD symptom onset.

Parkinson's disease risk enhancers in microglia.

Genome-wide association studies have identified thousands of single nucleotide polymorphisms that associate with increased risk for Parkinson's disease (PD), but the functions of most of them are unknown. Using assay for transposase-accessible chromatin (ATAC) and H3K27ac chromatin immunoprecipitation (ChIP) sequencing data, we identified 73 regulatory elements in microglia that overlap PD risk SNPs. To determine the target genes of a "risk enhancer" within intron two of SNCA, we used CRISPR-Cas9 to delete the open chromatin region where two PD risk SNPs reside. The loss of the enhancer led to reduced expression of multiple genes including SNCA and the adjacent gene MMRN1. It also led to expression changes of genes involved in glucose metabolism, a process that is known to be altered in PD patients. Our work expands the role of SNCA in PD and provides a connection between PD-associated genetic variants and underlying biology that points to a risk mechanism in microglia.

A Proposed Cost-Benefit Analysis of Adult EFNEP Utilizing Biomarkers of Chronic Disease Risk.

OBJECTIVE: To assess whether the adult Expanded Food and Nutrition Education Program (EFNEP) is a cost-effective intervention that generates sustained improvement in biomarkers of chronic disease risk. DESIGN: A longitudinal quasi-experimental design with 2 parallel arms (untreated comparison vs EFNEP) and 4 waves of data collection (pretest, posttest, 6 months, and 12 months after completion). SETTING: Eligible adult EFNEP community settings in Colorado, Florida, Maryland, and Washington. PARTICIPANTS: Free-living adults (n = 500) aged 18-50 years, with income ≤ 185% of the Federal Poverty Line. INTERVENTION(S): Adult EFNEP delivered using an evidence-based curriculum, Eating Smart • Being Active. MAIN OUTCOME MEASURE(S): Chronic disease biomarkers (body mass index, blood pressure, and HbA1c), food and physical activity behaviors, dietary intake, health status, and demographics will be measured using objective biometric indicators, the Adult EFNEP Questionnaire, a 24-hour dietary recall, a health questionnaire, and demographic forms. ANALYSIS: Linear mixed models will be used to assess whether adult EFNEP has a significant (P < 0.01) impact on 3 chronic disease biomarkers. The program's estimated impact on chronic disease biomarkers will be incorporated into a cost-benefit analysis framework to assess the economic value generated by adult EFNEP through chronic disease risk reduction.

Sex determination of human skeletal populations using latent profile analysis.

Accurately estimating biological sex from the human skeleton can be especially difficult for fragmentary or incomplete remains often encountered in bioarchaeological contexts. Where typical anatomically dimorphic skeletal regions are incomplete or absent, observers often take their best guess to classify biological sex. Latent profile analysis (LPA) is a mixture modeling technique which uses observed continuous data to estimate unobserved categorical group membership using posterior probabilities. In this study, sex is the latent variable (male and female are the two latent classes), and the indicator variables used here were eight standard linear measurements (long bone lengths, diaphyseal and articular breadths, and circumferences). Mplus (Muthén and Muthén: Mplus user's guide, 6th ed. Los Angeles: Muthén & Muthén, 2010) was used to obtain maximum likelihood estimates for latent class membership from a known sample of individuals from the forensic data bank (FDB) (Jantz and Moore-Jansen: Database for forensic anthropology in the United States 1962-1991, Ann Arbor, MI: Interuniversity Consortium for Political and Social Research, 2000) (n = 1,831), yielding 87% of correct classification for sex. Then, a simulation extracted 5,000 different random samples of 206 complete cases each from the FDB (these cases also had known sex). We then artificially imposed patterns of missing data similar to that observed in a poorly preserved bioarchaeological sample from Medieval Asturias, Spain (n = 206), and ran LPA on each sample. This tested the efficacy of LPA under extreme conditions of poor preservation (missing data, 42%). The simulation yielded an average of 82% accuracy, indicating that LPA is robust to large amounts of missing data when analyzing incomplete skeletons.

An investigation of the dynamic processes promoting citizen participation.

This study expanded the citizen participation literature by examining the dynamic nature of citizen participation and the extent to which the factors associated with citizen participation may be moderated by resident leadership status. Longitudinal survey data collected from 542 residents in one small Midwestern city implementing a community change initiative provide some insight into the challenges surrounding the promotion of an active citizenry. Within this one community, citizenship behaviors of emergent resident leaders and residents uninterested in a leadership role were influenced, to some extent, by different factors and the importance of these factors shifted in only a 2 years time span. Future research is needed to determine if the dynamics uncovered in this study were due to the initiative or to the nature of citizen participation processes.

Cutting edge: SWI/SNF mediates antisense Igh transcription and locus-wide accessibility in B cell precursors.

The stepwise process of Ag receptor gene assembly, termed V(D)J recombination, is coordinated during lymphocyte development by sweeping changes in chromatin that permit or deny access to a single recombinase enzyme. We now show that switching/sucrose nonfermenting (SWI/SNF) chromatin remodeling complexes are recruited to the Igh locus by an enhancer-dependent process and that these complexes are essential for generating recombinase accessibility throughout the locus. Depletion of SWI/SNF in pro-B cells also inhibits antisense transcription through all clusters of Igh gene segments, a pioneering process that has been implicated in the initial opening of chromatin. We conclude that SWI/SNF complexes play multiple roles in Igh gene assembly, ranging from initial locus activation to the spreading and maintenance of chromatin accessibility over large V(H), D(H), and J(H) domains.

Post-GWAS knowledge gap: the how, where, and when.

Genetic risk for complex diseases very rarely reflects only Mendelian-inherited phenotypes where single-gene mutations can be followed in families by linkage analysis. More commonly, a large set of low-penetrance, small effect-size variants combine to confer risk; they are normally revealed in genome-wide association studies (GWAS), which compare large population groups. Whereas Mendelian inheritance points toward disease mechanisms arising from the mutated genes, in the case of GWAS signals, the effector proteins and even general risk mechanism are mostly unknown. Instead, the utility of GWAS currently lies primarily in predictive and diagnostic information. Although an amazing body of GWAS-based knowledge now exists, we advocate for more funding towards the exploration of the fundamental biology in post-GWAS studies; this research will bring us closer to causality and risk gene identification. Using Parkinson's Disease as an example, we ask, how, where, and when do risk loci contribute to disease?

Who participates and why: building a process model of citizen participation.

Initiating and sustaining sufficient levels of participation among residents in low-income and urban neighborhoods have become significant focuses of many initiatives that strive to develop healthy communities. This study examines the factors associated with citizen participation levels in resident leaders and followers in seven low-income neighborhoods in one community. Overall, the findings suggest that different factors facilitate participation in leaders and followers. Leaders are more likely to actively participate in neighborhood and community affairs if they perceive themselves as having the skills needed to organize others and make change happen. Whereas perceived skill levels also matter for followers, these residents are strongly influenced by the norms for activism within their neighborhood. These norms mediate the impact of neighborhood readiness and capacity for change on citizen participation levels. Implications for funders and practitioners interested in promoting healthy communities are discussed.

MCF-7 as a Model for Functional Analysis of Breast Cancer Risk Variants.

BACKGROUND: Breast cancer genetic predisposition is governed by more than 142 loci as revealed by genome-wide association studies (GWAS). The functional contribution of these risk loci to breast cancer remains unclear, and additional post-GWAS analyses are required. METHODS: We identified active regulatory elements (enhancers, promoters, and chromatin organizing elements) by histone H3K27 acetylation and CTCF occupancy and determined the enrichment of risk variants at these sites. We compared these results with previously published data and for other cell lines, including human mammary epithelial cells, and related these data to gene expression. RESULTS: In terms of mapping accuracy and resolution, our data augment previous annotations of the MCF-7 epigenome. After intersection with GWAS risk variants, we found 39 enhancers and 15 CTCF occupancy sites that, between them, overlapped 96 breast cancer credible risk variants at 42 loci. These risk enhancers likely regulate the expression of dozens of genes, which are enriched for GO categories, including estrogen and prolactin signaling. CONCLUSIONS: Ten (of 142) breast cancer risk loci likely function via enhancers that are active in MCF-7 and are well suited to targeted manipulation in this system. In contrast, risk loci cannot be mapped to specific CTCF-binding sites, and the genes linked to risk CTCF sites did not show functional enrichment. The identity of risk enhancers and their associated genes suggests that some risk may function during later processes in cancer progression. IMPACT: Here, we report how the ER+ cell line MCF-7 can be used to dissect risk mechanisms for breast cancer.

Prospects for predictive modeling of transition cow diseases.

Transition cow diseases can negatively impact animal welfare and reduce dairy herd profitability. Transition cow disease incidence has remained relatively stable over time despite monitoring and management efforts aimed to reduce the risk of developing diseases. Dairy cattle disease risk is monitored by assessing multiple factors, including certain biomarker test results, health records, feed intake, body condition score, and milk production. However, these factors, which are used to make herd management decisions, are often reviewed separately without considering the correlation between them. In addition, the biomarkers that are currently used for monitoring may not be representative of the complex physiological changes that occur during the transition period. Predictive modeling, which uses data to predict future or current outcomes, is a method that can be used to combine the most predictive variables and their interactions efficiently. The use of an effective predictive model with relevant predictors for transition cow diseases will result in better targeted interventions, and therefore lower disease incidence. This review will discuss predictive modeling methods and candidate variables in the context of transition cow diseases. The next step is to investigate novel biomarkers and statistical methods that are best suited for the prediction of transition cow diseases.