Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer’s dementia

Transcriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, traditional two-stage TWAS methods first impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on reference transcriptome. Traditional TWAS methods then employ a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTL’s estimated effect on reference transcriptome. To increase TWAS robustness to this assumption, we propose a novel Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding reference cis-eQTL effects) rather than fixed. VC-TWAS is applicable to both continuous and dichotomous phenotypes, as well as individual-level and summary-level GWAS data. Using simulated data, we show VC-TWAS is more powerful than traditional TWAS methods based on a two-stage Burden test, especially when eQTL genetic effects on test phenotype are no longer a linear function of their eQTL genetic effects on reference transcriptome. We further applied VC-TWAS to both individual-level (N = ~3.4K) and summary-level (N = ~54K) GWAS data to study Alzheimer’s dementia (AD). With the individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by traditional TWAS methods. With the summary-level data, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs, which also validated our findings with the individual-level GWAS data. Our VC-TWAS method is implemented in the TIGAR tool for public use.

Download Full-text

Powerful Variance-Component TWAS method identifies novel and known risk genes for clinical and pathologic Alzheimer’s dementia phenotypes

10.1101/2020.05.26.117515 ◽

2020 ◽

Author(s):

Shizhen Tang ◽

Aron S. Buchman ◽

Philip L. De Jager ◽

David A. Bennett ◽

Michael P. Epstein ◽

...

Keyword(s):

Gene Expression ◽

Variance Component ◽

Association Studies ◽

Alzheimer’S Dementia ◽

Effect Sizes ◽

Reference Dataset ◽

Alzheimer's Dementia ◽

Risk Genes ◽

Test Dataset ◽

Reference Transcriptome

AbstractTranscriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, existing TWAS methods impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on transcriptome estimated from reference datasets. Existing TWAS methods then apply a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTL’s estimated effect on reference transcriptome. Thus, existing TWAS methods make a strong assumption that cis-eQTL effect sizes on reference transcriptome are reflective of their corresponding SNP effect sizes on test phenotype. To increase TWAS robustness to this assumption, we propose a Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding cis-eQTL effects in reference dataset) rather than fixed. By doing so, we show VC-TWAS is more powerful than traditional TWAS when cis-eQTL SNP effects on test phenotype truly differ from their eQTL effects within reference dataset. We further applied VC-TWAS using cis-eQTL effect sizes estimated by a nonparametric Bayesian method to study Alzheimer’s dementia (AD) related phenotypes and detected 13 genes significantly associated with AD, including 6 known GWAS risk loci. All significant loci are proximal to the major known risk loci APOE for AD. Further, we add this VC-TWAS function into our previously developed tool TIGAR for public use.

Download Full-text

Missing Data in Research on Youth and Family Programs

Psychological Reports ◽

10.1177/00332941211026851 ◽

2021 ◽

pp. 003329412110268

Author(s):

Jaime Ballard ◽

Adeya Richmond ◽

Suzanne van den Hoogenhof ◽

Lynne Borden ◽

Daniel Francis Perkins

Keyword(s):

Missing Data ◽

Statistical Methods ◽

Self Report ◽

Program Participation ◽

Multilevel Data ◽

Individual Level ◽

Level Data ◽

Before And After ◽

Post Test ◽

The Individual

Background Multilevel data can be missing at the individual level or at a nested level, such as family, classroom, or program site. Increased knowledge of higher-level missing data is necessary to develop evaluation design and statistical methods to address it. Methods Participants included 9,514 individuals participating in 47 youth and family programs nationwide who completed multiple self-report measures before and after program participation. Data were marked as missing or not missing at the item, scale, and wave levels for both individuals and program sites. Results Site-level missing data represented a substantial portion of missing data, ranging from 0–46% of missing data at pre-test and 35–71% of missing data at post-test. Youth were the most likely to be missing data, although site-level data did not differ by the age of participants served. In this dataset youth had the most surveys to complete, so their missing data could be due to survey fatigue. Conclusions Much of the missing data for individuals can be explained by the site not administering those questions or scales. These results suggest a need for statistical methods that account for site-level missing data, and for research design methods to reduce the prevalence of site-level missing data or reduce its impact. Researchers can generate buy-in with sites during the community collaboration stage, assessing problematic items for revision or removal and need for ongoing site support, particularly at post-test. We recommend that researchers conducting multilevel data report the amount and mechanism of missing data at each level.

Download Full-text

Is Suicidality Increased in Covid-19 Pandemic? A Scoping Review and Quality Assessment

10.47363/jmhc/2021(4)170 ◽

2021 ◽

pp. 1-8

Author(s):

Kimberly Virginin Cruz Correia da Silva ◽

Keyword(s):

Scoping Review ◽

Web Of Science ◽

Significant Risk ◽

Stressful Situation ◽

Confounding Variable ◽

Individual Level ◽

Level Data ◽

Study Population ◽

Coronavirus Infection ◽

Risk Of Exposure

Background: There are emerging concerns that the COVID-19 pandemic may specifically increase suicide. Methods: Scoping Review in the MEDLINE/PubMed, SCOPUS, Web of Science, PsycINFO, Science Direct databases and in the medRxiv, bioRxiv and PsyArXiv preprint servers, using the descriptors “Covid-19”, “coronavirus infection”, “coronavirus”, “2019-nCoV”, “2019 new coronavirus disease”, “SARS-CoV-2”, “Suicide”, “General Public” and “Mental Health”. Results: A total of 62 studies were included in this review, where 10 studies were reported to have been conducted between March and May 2021; 39 in 2020; 4 in 2019; 3 in 2018; 1 in 2015; 2 in 2014; 2 in 2010 and 1 in 2004, all were conducted via online platforms. Limitations: We have interpreted our study findings in the context of the overall significant risk of exposure to suicide in our study population, while recognizing that individual level data of exposure to COVID-19 is a significant confounding variable. Conclusions: Being one of the first reviews in this context, the findings are anticipated to be helpful to predict the possible solutions for reducing the number of suicides in and facilitate further studies on strategies of how to alleviate such a stressful situation in COVID-19.

Download Full-text

Cohort Profile: The China Multi-Ethnic Cohort (CMEC) Study

10.1101/2020.02.14.20022970 ◽

2020 ◽

Author(s):

Xing Zhao ◽

Feng Hong ◽

Jianzhong Yin ◽

Wenge Tang ◽

Gang Zhang ◽

...

Keyword(s):

Clinical Laboratory ◽

Disease Incidence ◽

Data Access ◽

Population Based ◽

Baseline Survey ◽

Individual Level ◽

Long Term Storage ◽

Level Data ◽

The Individual ◽

Study Participants

AbstractCohort purposeThe China Multi-Ethnic Cohort (CMEC) is a community population-based prospective observational study aiming to address the urgent need for understanding NCD prevalence, risk factors and associated conditions in resource-constrained settings for ethnic minorities in China.Cohort BasicsA total of 99 556 participants aged 30 to 79 years (Tibetan populations include those aged 18 to 30 years) from the Tibetan, Yi, Miao, Bai, Bouyei, and Dong ethnic groups in Southwest China were recruited between May 2018 and September 2019.Follow-up and attritionAll surviving study participants will be invited for re-interviews every 3-5 years with concise questionnaires to review risk exposures and disease incidence. Furthermore, the vital status of study participants will be followed up through linkage with established electronic disease registries annually.Design and MeasuresThe CMEC baseline survey collected data with an electronic questionnaire and face-to-face interviews, medical examinations and clinical laboratory tests. Furthermore, we collected biological specimens, including blood, saliva and stool, for long-term storage. In addition to the individual level data, we also collected regional level data for each investigation site.Collaboration and data accessCollaborations are welcome. Please send specific ideas to corresponding author at: [email protected].

Download Full-text

Welsh Government Flying Start Programme Evaluation Using Linked Data

International Journal for Population Data Science ◽

10.23889/ijpds.v3i2.517 ◽

2018 ◽

Vol 3 (2) ◽

Author(s):

Sarah Lowe ◽

Laura McGinn ◽

Marcos Quintela ◽

Luke Player ◽

Karen Tingay

Keyword(s):

Evidence Base ◽

Development Project ◽

Early Years ◽

Local Authorities ◽

Parenting Support ◽

Individual Level ◽

Level Data ◽

Part Time ◽

The Individual ◽

Families With Children

BackgroundFlying Start (FS) is the Welsh Government’s (WG) flagship Early Years programme for families with children aged less than 4 years of age. Running since 2006, the four entitlements are: Free part-time childcare for 2-3 year olds Enhanced Health Visiting Parenting support Speech, language, and communication support ObjectivesCurrently, while we know which areas in Wales are receiving FS support, individual-level data on which child received what entitlements is not available. Area-level outcomes can be used as proxy indicators but the individual impact of receiving FS support cannot be examined.The project aims to evaluate FS by linking the FS cohort to a range of outcomes including health, education and social care. MethodsA Dataflow Development Project (DDP) has been launched to install SAIL (Secure Anonymised Information Linkage) appliances into 6 pilot Local Authorities in Wales which will test acquiring and linking the individual level FS data from pilot Local Authorities with other datasets in SAIL. FindingsThe project will report some emerging findings from the analysis of pilot data. ImplicationsThere is a growing interest in using linked administrative data to evaluate government initiatives, and mounting enthusiasm in Local Government. If successful, this model is likely to be adopted by related WG programmes; improving the evidence base, facilitating effective evaluation, and adding to the data available for re-use in Wales.

Download Full-text

Agricultural entrepreneurship orientation: is academic training a missing link?

Education + Training ◽

10.1108/et-10-2016-0156 ◽

2017 ◽

Vol 59 (7/8) ◽

pp. 856-870 ◽

Cited By ~ 3

Author(s):

Soodeh Mohammadinezhad ◽

Maryam Sharifzadeh

Keyword(s):

Content Type ◽

Individual Level ◽

Configuration Theory ◽

University Courses ◽

Level Data ◽

Academic Courses ◽

The Individual ◽

Agricultural Entrepreneurship ◽

Hierarchy Process ◽

Practical Implications

Purpose The purpose of this paper is to investigate the importance of academic courses on agricultural entrepreneurship. Design/methodology/approach Modified global entrepreneurship and development index (GEDI) was used to determine entrepreneurial dimensions among 19 graduated students of agricultural colleges resided in Iran. Fuzzy analytical hierarchy process was applied to understand agricultural graduates’ preferences on effectiveness of university courses (core, free elective and restricted elective). Findings Results suggested the importance of professional restricted elective courses to provide students with necessary skills. These courses were successful in providing a context for entrepreneurial profile. Research limitations/implications Innate talent or acquired skills were always the place of debate on entrepreneurial development. The paper builds on the premise that entrepreneurs are made through education and continuing reconstruction of experience, further research is required as the field develops in experience and complexity. Practical implications The paper provides strategies to effectively modify practical route in higher education to enhance entrepreneurial orientation among students. Originality/value The paper is innovative at a conceptual level in modifying GEDI elements in individual-level variables based on GEDI configuration theory. This approach is particularly useful in addressing the bottleneck problems of entrepreneurship profile and focusses on the information interpreted at weights of the individual-level data.

Download Full-text

On the Issues Surrounding Economic Voting

Comparative Political Studies ◽

10.1177/0010414087020001001 ◽

1987 ◽

Vol 20 (1) ◽

pp. 3-33 ◽

Cited By ~ 7

Author(s):

JOHN R. HIBBING

Keyword(s):

United States ◽

United Kingdom ◽

Voting Behavior ◽

Economic Voting ◽

The United States ◽

Individual Level ◽

The United Kingdom ◽

Level Data ◽

Election Results ◽

The Individual

This is an analysis of the effects of economic factors on voting behavior in the United Kingdom. Aggregate- and individual-level data are used. When the results are compared to findings generated by the United States case, some intriguing differences appear. To mention just two examples, unemployment and inflation seem to be much more important in the United Kingdom than in the United States, and changes in real per capita income are positively related to election results in the United States and negatively related in the United Kingdom. More generally, while the aggregate results are strong and the individual-level results weak in the United States, in the United Kingdom the situation is practically reversed.

Download Full-text

Area-level relative deprivation and alcohol use in Denmark: Is there a relationship?

Scandinavian Journal of Public Health ◽

10.1177/1403494818787101 ◽

2018 ◽

Vol 47 (4) ◽

pp. 428-438 ◽

Cited By ~ 2

Author(s):

Kim Bloomfield ◽

Gabriele Berg-Beckhoff ◽

Abdu Kedir Seid ◽

Christiane Stock

Keyword(s):

Alcohol Use ◽

Relative Deprivation ◽

Health Behaviours ◽

Area Deprivation ◽

Individual Level ◽

Level Data ◽

Housing Component ◽

Disorder Identification ◽

The Individual ◽

The Impact

Aims: Greater area-level relative deprivation has been related to poorer health behaviours, but studies specifically on alcohol use and abuse have been equivocal. The main purpose of the present study was to investigate how area-level relative deprivation in Denmark relates to alcohol use and misuse in the country. Methods: As individual-level data, we used the national alcohol and drug survey of 2011 ( n= 5133). Data were procured from Statistics Denmark to construct an index of relative deprivation at the parish level ( n=2119). The deprivation index has two components, which were divided into quintiles. Multilevel linear and logistic regressions analysed the influence of area deprivation on mean alcohol use and hazardous drinking, as measured by the Alcohol Use Disorder Identification Test. Results: Men who lived in parishes designated as ‘very deprived’ on the socioeconomic component were more likely to consume less alcohol; women who lived in parishes designated as ‘deprived’ on the housing component were less likely to drink hazardously. But at the individual level, education was positively related to mean alcohol consumption, and higher individual income was positively related to mean consumption for women. Higher-educated men were more likely to drink hazardously. Conclusions: Area-level measures of relative deprivation were not strongly related to alcohol use, yet in the same models individual-level socioeconomic variables had a more noticeable influence. This suggests that in a stronger welfare state, the impact of area-level relative deprivation may not be as great. Further work is needed to develop more sensitive measures of relative deprivation.

Download Full-text

Partisanship, Militarized International Conflict, and Electoral Support for the Incumbent

Political Research Quarterly ◽

10.1177/1065912917727369 ◽

2017 ◽

Vol 71 (1) ◽

pp. 172-183 ◽

Cited By ~ 2

Author(s):

Shane P. Singh ◽

Jaroslav Tir

Keyword(s):

Political Behavior ◽

Comparative Politics ◽

International Conflict ◽

Vote Choice ◽

Individual Level ◽

Interstate Disputes ◽

Electoral Support ◽

Level Data ◽

The Individual ◽

Militarized Interstate Disputes

Comparative politics scholarship often neglects to consider how militarized interstate disputes (MIDs) shape political behavior. In this project, we advance an argument that considers voter responses to international conflict at the individual level. In particular, we consider how the well-known conditioning effects of partisanship manifest in relation to militarized international conflict. Examining individual- and macro-level data across ninety-seven elections in forty-two countries over the 1996–2011 period, we find consistent evidence of militarized conflict impacting vote choice. This relationship is, however, moderated by partisanship, conflict side (initiator or target), and conflict hostility level. Among non-copartisan voters, the incumbent benefits the most electorally from initiating low-hostility MIDs or when the country is a target of a high-hostility MID; the opposite scenarios (initiator of a high-hostility MID or target of a low-hostility MID) lead to punishment among this voter group. Copartisans, meanwhile, tend to either maintain or intensify their support in most scenarios we examine; when a country is targeted in a low-hostility MID, copartisan support erodes mildly.

Download Full-text

Examining the Impact of Individual, Community, and Market Factors on Methamphetamine Use: A Tale of Two Cities

Journal of Drug Issues ◽

10.1177/002204260503500402 ◽

2005 ◽

Vol 35 (4) ◽

pp. 665-693 ◽

Cited By ~ 27

Author(s):

Nancy Rodriguez ◽

Charles Katz ◽

Vincent J. Webb ◽

David R. Schaefer

Keyword(s):

Drug Market ◽

Community Level ◽

Policy Implications ◽

Individual Level ◽

Methamphetamine Use ◽

Level Data ◽

Two Cities ◽

Market Factors ◽

The Individual ◽

The Impact

Although prior studies have monitored the trends in methamphetamine use and reported its increase over the years, few studies have considered how community-level characteristics affect the use of methamphetamine. In this study, we utilize data from the Arrestee Drug Abuse Monitoring (ADAM) program from two cities to examine how individual-level, community-level, and drug market factors influence methamphetamine use. Results indicate that both individual and community-level data significantly influence methamphetamine use. Also, findings show that predictors of methamphetamine use (at the individual and community-level) differ significantly from marijuana, cocaine, and opiate use. Policy implications regarding law enforcement suppression and the treatment of methamphetamine users are discussed.

Download Full-text