Biostatistics Commons^™

Measurement Of Bystander Actions In Violence Intervention Evaluation: Opportunities And Challenges, Heather M. Bush, Samuel C. Bell, Ann L. Coker

Biostatistics Faculty Publications

Purpose of Review

This review discusses design and methodological challenges specific to measuring bystander actions in the evaluation of bystander-based violence prevention programming. “Bystanders” are defined as people who are present immediately before, during and/or after a violent event, but are not a perpetrator nor the intended victim. Bystander-based violence prevention programs seek to prevent or mitigate violent events by empowering bystanders to intervene on acts of violence and social norms that promulgate violence.

Recent Findings

Effective bystander-based violence prevention programs demonstrate increased bystander intentions, actions, and attitudes [Bringing in the Bystander: Banyard et al. J Community Psychol. 2007;35:463-481; iSCREAM: …

Incorporating Pathway Information Into Feature Selection Towards Better Performed Gene Signatures, Suyan Tian, Chi Wang, Bing Wang

Biostatistics Faculty Publications

To analyze gene expression data with sophisticated grouping structures and to extract hidden patterns from such data, feature selection is of critical importance. It is well known that genes do not function in isolation but rather work together within various metabolic, regulatory, and signaling pathways. If the biological knowledge contained within these pathways is taken into account, the resulting method is a pathway-based algorithm. Studies have demonstrated that a pathway-based method usually outperforms its gene-based counterpart in which no biological knowledge is considered. In this article, a pathway-based feature selection is firstly divided into three major categories, namely, pathway-level selection, …

Feature Selection For Longitudinal Data By Using Sign Averages To Summarize Gene Expression Values Over Time, Suyan Tian, Chi Wang

Biostatistics Faculty Publications

With the rapid evolution of high-throughput technologies, time series/longitudinal high-throughput experiments have become possible and affordable. However, the development of statistical methods dealing with gene expression profiles across time points has not kept up with the explosion of such data. The feature selection process is of critical importance for longitudinal microarray data. In this study, we proposed aggregating a gene’s expression values across time into a single value using the sign average method, thereby degrading a longitudinal feature selection process into a classic one. Regularized logistic regression models with pseudogenes (i.e., the sign average of genes across time as predictors) …

Dichotomous Scoring Of Tdp-43 Proteinopathy From Specific Brain Regions In 27 Academic Research Centers: Associations With Alzheimer's Disease And Cerebrovascular Disease Pathologies, Yuriko Katsumata, David W. Fardo, Walter A. Kukull, Peter T. Nelson

Biostatistics Faculty Publications

TAR-DNA binding protein 43 (TDP-43) proteinopathy is a common brain pathology in elderly persons, but much remains to be learned about this high-morbidity condition. Published stage-based systems for operationalizing disease severity rely on the involvement (presence/absence) of pathology in specific anatomic regions. To examine the comorbidities associated with TDP-43 pathology in aged individuals, we studied data from the National Alzheimer’s Coordinating Center (NACC) Neuropathology Data Set. Data were analyzed from 929 included subjects with available TDP-43 pathology information, sourced from 27 different American Alzheimer’s Disease Centers (ADCs). Cases with relatively unusual diseases including autopsy-proven frontotemporal lobar degeneration (FTLD-TDP or FTLD-tau) …

Serum Nutrient Levels And Aging Effects On Periodontitis, Jeffrey L Ebersole, Joshua Lambert, Heather Bush, Pinar Emecen Huja, Arpita Basu

Biostatistics Faculty Publications

Periodontal disease damages tissues as a result of dysregulated host responses against the chronic bacterial biofilm insult and approximately 50% of US adults > 30 years old exhibit periodontitis. The association of five blood nutrients and periodontitis were evaluated due to our previous findings regarding a potential protective effect for these nutrients in periodontal disease derived from the US population sampled as part of the National Health and Nutrition Examination Survey (1999–2004). Data from over 15,000 subjects was analyzed for blood levels of cis-β-carotene, β-cryptoxanthin, folate, vitamin D, and vitamin E, linked with analysis of the presence and severity of periodontitis. …

A Logitudinal Feature Selection Method Identifies Relevant Genes To Distinguish Complicated Injury And Uncomplicated Injury Over Time, Suyan Tian, Chi Wang, Howard H. Chang

Biostatistics Faculty Publications

Background: Feature selection and gene set analysis are of increasing interest in the field of bioinformatics. While these two approaches have been developed for different purposes, we describe how some gene set analysis methods can be utilized to conduct feature selection.

Methods: We adopted a gene set analysis method, the significance analysis of microarray gene set reduction (SAMGSR) algorithm, to carry out feature selection for longitudinal gene expression data.

Results: Using a real-world application and simulated data, it is demonstrated that the proposed SAMGSR extension outperforms other relevant methods. In this study, we illustrate that a gene’s expression profiles over …

Interrupted Time Series Design To Evaluate The Effect Of The Icd-9-Cm To Icd-10-Cm Coding Transition On Injury Hospitalization Trends, Svetla Slavova, Julia F. Costich, Huong Luu, Judith Fields, Barbara A. Gabella, Sergey Tarima, Terry L. Bunn

Biostatistics Faculty Publications

Background: Implementation of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) in the U.S. on October 1, 2015 was a significant policy change with the potential to affect established injury morbidity trends. This study used data from a single state to demonstrate 1) the use of a statistical method to estimate the effect of this coding transition on injury hospitalization trends, and 2) interpretation of significant changes in injury trends in the context of the structural and conceptual differences between ICD-9-CM and ICD-10-CM, the new ICD-10-CM-specific coding guidelines, and proposed ICD-10-CM-based framework for reporting of injuries by intent …

Gaw20: Methods And Strategies For The New Frontiers Of Epigenetics And Pharmacogenomics, Nathan L. Tintle, David W. Fardo, Marzia De Andrade, Stella Aslibekyan, Julia N. Bailey, Justo Lorenzo Bermejo, Rita M. Cantor, Saurabh Ghosh, Philip Melton, Xuexua Wang, Jean W. Maccluer, Laura Almasy

Biostatistics Faculty Publications

GAW20 provided a platform for developing and evaluating statistical methods to analyze human lipid-related phenotypes, DNA methylation, and single-nucleotide markers in a study involving a pharmaceutical intervention. In this article, we present an overview of the data sets and the contributions analyzing these data. The data, donated by the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) investigators, included data from 188 families (N = 1105) which included genome-wide DNA methylation data before and after a 3-week treatment with fenofibrate, single-nucleotide polymorphisms, metabolic syndrome components before and after treatment, and a variety of covariates. The contributions from individual …

Association Analyses Of Repeated Measures On Triglyceride And High-Density Lipoprotein Levels: Insights From Gaw20, Saurabh Ghosh, David W. Fardo

Biostatistics Faculty Publications

Background: The GAW20 group formed on the theme of methods for association analyses of repeated measures comprised 4sets of investigators. The provided “real” data set included genotypes obtained from a human whole-genome association study based on longitudinal measurements of triglycerides (TGs) and high-density lipoprotein in addition to methylation levels before and after administration of fenofibrate. The simulated data set contained 200 replications of methylation levels and posttreatment TGs, mimicking the real data set.

Results: The different investigators in the group focused on the statistical challenges unique to family-based association analyses of phenotypes measured longitudinally and applied a wide spectrum of …

Treatment And Outcomes Of Non-Small-Cell Lung Cancer Patients With High Comorbidity, Jorge Rios, Rahul Gosain, Bernardo H. L. Goulart, Bin Huang, Margaret N. Oechsli, Jaclyn K. Mcdowell, Quan Chen, Thomas Tucker, Goetz H. Kloecker

Biostatistics Faculty Publications

Background: The life expectancy of untreated non-small-cell lung cancer (NSCLC) is dismal, while treatment for NSCLC improves survival. The presence of comorbidities is thought to play a significant role in the decision to treat or not treat a given patient. We aim to evaluate the association of comorbidities with the survival of patients treated for NSCLC.

Methods: We performed a retrospective study of patients aged ≥66 years with invasive NSCLC between the years 2007 and 2011 in the Surveillance, Epidemiology, and End Results Kentucky Cancer Registry. Comorbidity was measured using the Klabunde Comorbidity Index (KCI), and univariate and multivariate logistic …

Bayesian Prediction Intervals For Assessing P-Value Variability In Prospective Replication Studies, Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri Zaykin

Biostatistics Faculty Publications

Increased availability of data and accessibility of computational tools in recent years have created an unprecedented upsurge of scientific studies driven by statistical analysis. Limitations inherent to statistics impose constraints on the reliability of conclusions drawn from data, so misuse of statistical methods is a growing concern. Hypothesis and significance testing, and the accompanying P-values are being scrutinized as representing the most widely applied and abused practices. One line of critique is that P-values are inherently unfit to fulfill their ostensible role as measures of credibility for scientific hypotheses. It has also been suggested that while P-values …

Systems Biology Approach To Late-Onset Alzheimer's Disease Genome-Wide Association Study Identifies Novel Candidate Genes Validated Using Brain Expression Data And Caenorhabditis Elegans Experiments, Shubhabrata Mukherjee, Joshua C. Russell, Daniel T. Carr, Jeremy D. Burgess, Mariet Allen, Daniel J. Serie, Kevin L. Boehme, John S. K. Kauwe, Adam C. Naj, David W. Fardo, Dennis W. Dickson, Thomas J. Montine, Nilufer Ertekin-Taner, Matt R. Kaeberlein, Paul K. Crane

Biostatistics Faculty Publications

Introduction—We sought to determine whether a systems biology approach may identify novel late-onset Alzheimer's disease (LOAD) loci.

Methods—We performed gene-wide association analyses and integrated results with human protein-protein interaction data using network analyses. We performed functional validation on novel genes using a transgenic Caenorhabditis elegans Aβ proteotoxicity model and evaluated novel genes using brain expression data from people with LOAD and other neurodegenerative conditions.

Results—We identified 13 novel candidate LOAD genes outside chromosome 19. Of those, RNA interference knockdowns of the C. elegans orthologs of UBC, NDUFS3, EGR1, and ATP5H were associated with Aβ …

Judging The Neonatal Abstinence Syndrome Assessment Tools To Guide Future Tool Development: The Use Of Clinimetrics As Opposed To Psychometrics, Philip M. Westgate, Enrique Gomez-Pomar

Biostatistics Faculty Publications

In the face of the current Neonatal Abstinence Syndrome (NAS) epidemic, there is considerable variability in the assessment and management of infants with NAS. In this manuscript, we particularly focus on NAS assessment, with special attention given to the popular Finnegan Neonatal Abstinence Score (FNAS). A major instigator of the problem of variable practices is that multiple modified versions of the FNAS exist and continue to be proposed, including shortened versions. Furthermore, the validity of such assessment tools has been questioned, and as a result, the need for better tools has been suggested. The ultimate purpose of this manuscript, therefore, …

Impact Of Home Visit Capacity On Genetic Association Studies Of Late-Onset Alzheimer's Disease, David W. Fardo, Laura E. Gibbons, Shubhabrata Mukherjee, M. Maria Glymour, Wayne Mccormick, Susan M. Mccurry, James D. Bowen, Eric B. Larson, Paul K. Crane

Biostatistics Faculty Publications

INTRODUCTION—Findings for genetic correlates of late-onset Alzheimer's disease (LOAD) in studies that rely solely on clinic visits may differ from those with capacity to follow participants unable to attend clinic visits.

METHODS—We evaluated previously identified LOAD-risk single nucleotide variants in the prospective Adult Changes in Thought study, comparing hazard ratios (HRs) estimated using the full data set of both in-home and clinic visits (n = 1697) to HRs estimated using only data that were obtained from clinic visits (n = 1308). Models were adjusted for age, sex, principal components to account for ancestry, and additional health indicators.

RESULTS …

Peripheral Inflammation, Apolipoprotein E4, And Amyloid-Β Interact To Induce Cognitive And Cerebrovascular Dysfunction, Felecia M. Marottoli, Yuriko Katsumata, Kevin P. Koster, Riya Thomas, David W. Fardo, Leon M. Tai

Biostatistics Faculty Publications

Cerebrovascular dysfunction is rapidly reemerging as a major process of Alzheimer’s disease (AD). It is, therefore, crucial to delineate the roles of AD risk factors in cerebrovascular dysfunction. While apolipoprotein E4 (APOE4), Amyloid-β (Aβ), and peripheral inflammation independently induce cerebrovascular damage, their collective effects remain to be elucidated. The goal of this study was to determine the interactive effect of APOE4, Aβ, and chronic repeated peripheral inflammation on cerebrovascular and cognitive dysfunction in vivo. EFAD mice are a well-characterized mouse model that express human APOE3 (E3FAD) or APOE4 (E4FAD) and overproduce human Aβ42 via expression of …

Estimated Probability Of Becoming A Case Of Drug Dependence In Relation To Duration Of Drug-Taking Experience: A Functional Analysis Approach, Olga A. Vsevolozhskaya, James C. Anthony

Biostatistics Faculty Publications

Measured as elapsed time from first use to dependence syndrome onset, the estimated "induction interval" for cocaine is thought to be short relative to the cannabis interval, but little is known about risk of becoming dependent during first months after onset of use. Virtually all published estimates for this facet of drug dependence epidemiology are from life histories elicited years after first use. To improve estimation, we turn to new month-wise data from nationally representative samples of newly incident drug users identified via probability sampling and confidential computer-assisted self-interviews for the United States National Surveys on Drug Use and Health, …

Tuberculosis And Risk Of Acute Myocardial Infarction: A Propensity Score-Matched Analysis, Moises A. Huaman, Richard J. Kryscio, Carl J. Fichtenbaum, David Henson, Elizabeth G. Salt, Timothy R. Sterling, Beth A. Garvy

Biostatistics Faculty Publications

Several pathogens have been associated with increased cardiovascular disease (CVD) risk. Whether this occurs with Mycobacterium tuberculosis infection is unclear. We assessed if tuberculosis disease increased the risk of acute myocardial infarction (AMI). We identified patients with tuberculosis index claims from a large de-identified database of ~15 million adults enrolled in a U.S. commercial insurance policy between 2008 and 2010. Tuberculosis patients were 1:1 matched to patients without tuberculosis claims using propensity scores. We compared the occurrence of index AMI claims between the tuberculosis and non-tuberculosis cohorts using Kaplan–Meier curves and Cox Proportional Hazard models. Data on 2026 patients with …

Identification Of Prognostic Genes And Gene Sets For Early-Stage Non-Small Cell Lung Cancer Using Bi-Level Selection Methods, Suyan Tian, Chi Wang, Howard H. Chang, Jianguo Sun

Biostatistics Faculty Publications

In contrast to feature selection and gene set analysis, bi-level selection is a process of selecting not only important gene sets but also important genes within those gene sets. Depending on the order of selections, a bi-level selection method can be classified into three categories – forward selection, which first selects relevant gene sets followed by the selection of relevant individual genes; backward selection which takes the reversed order; and simultaneous selection, which performs the two tasks simultaneously usually with the aids of a penalized regression model. To test the existence of subtype-specific prognostic genes for non-small cell lung cancer …

Level Of Patient-Physician Agreement In Assessment Of Change Following Conservative Rehabilitation For Shoulder Pain, Stephanie D. Moore-Reed, W. Ben Kibler, Heather M. Bush, Timothy L. Uhl

Biostatistics Faculty Publications

Background Assessment of health-related status has been shown to vary between patients and physicians, although the degree of patient–physician discordance in the assessment of the change in status is unknown.

Methods Ninety-nine patients with shoulder dysfunction underwent a standardized physician examination and completed several self-reported questionnaires. All patients were prescribed the same physical therapy intervention. Six weeks later, the patients returned to the physician, when self-report questionnaires were re-assessed and the Global Rating of Change (GROC) was completed by the patient. The physician completed the GROC retrospectively. To determine agreement between patient and physician, intra-class correlation (ICC) coefficient and Pearson’s …

Inter-Relationships Linking Probability Of Becoming A Case Of Nicotine Dependence With Frequency Of Tobacco Cigarette Smoking, Olga A. Vsevolozhskaya, James C. Anthony

Biostatistics Faculty Publications

INTRODUCTION: Once smoking starts, some tobacco cigarette smokers (TCS) can make very rapid transitions into tobacco dependence syndromes (TCD). With adjustment for smoking frequency, we posit female excess risk for this rapid-onset TCD. In a novel application of functional analysis for tobacco research, we estimate four Hill function parameters and plot TCD risk against a gradient of smoking frequency, as observed quite soon after smoking onset.

METHODS: In aggregate, the National Surveys of Drug Use and Health, 2004-2013, identified 1546 newly incident TCS in cross-sectional research, each with standardized TCD assessment.

RESULTS: Hill function estimates contradict our apparently over-simplistic hypothesis. …

On Combining Family- And Population- Based Sequencing Data, Yuriko Katsumata, David W. Fardo

Biostatistics Faculty Publications

Several statistical group-based approaches have been proposed to detect effects of variation within a gene for each of the population- and family-based designs. However, unified tests to combine gene-phenotype associations obtained from these 2 study designs are not yet well established. In this study, we investigated the efficient combination of population-based and family-based sequencing data to evaluate best practices using the Genetic Analysis Workshop 19 (GAW19) data set. Because one design employed whole genome sequencing and the other whole exome sequencing, we examined variants overlapping both data sets. We used the family-based sequence kernel association test (famSKAT) to analyze the …

Causal Effect Estimation In Sequencing Studies: A Bayesian Method To Account For Confounder Adjustment Uncertainty, Chi Wang, Jinpeng Liu, David W. Fardo

Biostatistics Faculty Publications

Estimating the causal effect of a single nucleotide variant (SNV) on clinical phenotypes is of interest in many genetic studies. The effect estimation may be confounded by other SNVs as a result of linkage disequilibrium as well as demographic and clinical characteristics. Because a large number of these other variables, which we call potential confounders, are collected, it is challenging to select and adjust for the variables that truly confound the causal effect. The Bayesian adjustment for confounding (BAC) method has been proposed as a general method to estimate the average causal effect in the presence of a large number …

Weighted-Samgsr: Combining Significance Analysis Of Microarray-Gene Set Reduction Algorithm With Pathway Topology-Based Weights To Select Relevant Genes, Suyan Tian, Howard H. Chang, Chi Wang

Biostatistics Faculty Publications

Background: It has been demonstrated that a pathway-based feature selection method that incorporates biological information within pathways during the process of feature selection usually outperforms a gene-based feature selection algorithm in terms of predictive accuracy and stability. Significance analysis of microarray-gene set reduction algorithm (SAMGSR), an extension to a gene set analysis method with further reduction of the selected pathways to their respective core subsets, can be regarded as a pathway-based feature selection method.

Methods: In SAMGSR, whether a gene is selected is mainly determined by its expression difference between the phenotypes, and partially by the number of pathways to …

Uncovering Local Trends In Genetic Effects Of Multiple Phenotypes Via Functional Linear Models, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, David A. Barondess, Xiaoren Tong, Sneha Jadhav, Qing Lu

Biostatistics Faculty Publications

Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear …

Motorcycle Helmet Effectiveness In Reducing Head, Face And Brain Injuries By State And Helmet Law, Cody S. Olsen, Andrea M. Thomas, Michael Singleton, Anna M. Gaichas, Tracy J. Smith, Gary A. Smith, Justin Peng, Michael J. Bauer, Ming Qu, Denise Yeager, Timothy Kerns, Cynthia Burch, Lawrence J. Cook

Biostatistics Faculty Publications

Background: Despite evidence that motorcycle helmets reduce morbidity and mortality, helmet laws and rates of helmet use vary by state in the U.S.

Methods: We pooled data from eleven states: five with universal laws requiring all motorcyclists to wear a helmet, and six with partial laws requiring only a subset of motorcyclists to wear a helmet. Data were combined in the Crash Outcome Data Evaluation System's General Use Model and included motorcycle crash records probabilistically linked to emergency department and inpatient discharges for years 2005-2008. Medical outcomes were compared between partial and universal helmet law settings. We estimated adjusted relative …

Patient-Specific Variations In Biomarkers Across Gingivitis And Periodontitis, Radhakrishnan Nagarajan, Craig S. Miller, Dolph Dawson, Mohanad Al-Sabbagh, J. L. Ebersole

Biostatistics Faculty Publications

This study investigates the use of saliva, as an emerging diagnostic fluid in conjunction with classification techniques to discern biological heterogeneity in clinically labelled gingivitis and periodontitis subjects (80 subjects; 40/group) A battery of classification techniques were investigated as traditional single classifier systems as well as within a novel selective voting ensemble classification approach (SVA) framework. Unlike traditional single classifiers, SVA is shown to reveal patient-specific variations within disease groups, which may be important for identifying proclivity to disease progression or disease stability. Salivary expression profiles of IL-1ß, IL-6, MMP-8, and MIP-1α from 80 patients were analyzed using four classification …

Test On Existence Of Histology Subtype-Specific Prognostic Signatures Among Early Stage Lung Adenocarcinoma And Squamous Cell Carcinoma Patients Using A Cox-Model Based Filter, Suyan Tian, Chi Wang, Ming-Wen An

Biostatistics Faculty Publications

BACKGROUND: Non-small cell lung cancer (NSCLC) is the predominant histological type of lung cancer, accounting for up to 85% of cases. Disease stage is commonly used to determine adjuvant treatment eligibility of NSCLC patients, however, it is an imprecise predictor of the prognosis of an individual patient. Currently, many researchers resort to microarray technology for identifying relevant genetic prognostic markers, with particular attention on trimming or extending a Cox regression model. Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are two major histology subtypes of NSCLC. It has been demonstrated that fundamental differences exist in their underlying mechanisms, which motivated us …

Impact Of Population Stratification On Family-Based Association In An Admixed Population, T. B. Mersha, L. Ding, H. He, E. S. Alexander, X. Zhang, B. G. Kurowski, V. Pilipenko, L. Kottyan, L. J. Martin, David W. Fardo

Biostatistics Faculty Publications

Population substructure is a well-known confounder in population-based case-control genetic studies, but its impact in family-based studies is unclear. We performed population substructure analysis using extended families of admixed population to evaluate power and Type I error in an association study framework. Our analysis shows that power was improved by 1.5% after principal components adjustment. Type I error was also reduced by 2.2% after adjusting for family substratification. The presence of population substructure was underscored by discriminant analysis, in which over 92% of individuals were correctly assigned to their actual family using only 100 principal components. This study demonstrates the …

Characteristics Associated With Willingness To Participate In A Randomized Controlled Behavioral Clinical Trial Using Home-Based Personal Computers And A Webcam, Hiroko H. Dodge, Yuriko Katsumata, Jian Zhu, Nora Mattek, Molly Bowman, Mattie Gregor, Katherine Wild, Jeffrey A Kaye

Biostatistics Faculty Publications

BACKGROUND: Trials aimed at preventing cognitive decline through cognitive stimulation among those with normal cognition or mild cognitive impairment are of significant importance in delaying the onset of dementia and reducing dementia prevalence. One challenge in these prevention trials is sample recruitment bias. Those willing to volunteer for these trials could be socially active, in relatively good health, and have high educational levels and cognitive function. These participants' characteristics could reduce the generalizability of study results and, more importantly, mask trial effects. We developed a randomized controlled trial to examine whether conversation-based cognitive stimulation delivered through personal computers, a webcam …

Identifying Genetic Variants For Heart Rate Variability In The Acetylcholine Pathway, Harriëtte Riese, Loretto M. Muñoz, Catharina A. Hartman, Xiuhua Ding, Shaoyong Su, Albertine J. Oldehinkel, Arie M. Van Roon, Peter J. Van Der Most, Joop Lefrandt, Ron T. Gansevoort, Pim Van Der Harst, Niek Verweij, Carmilla M. M. Licht, Dorret I. Boomsma, Jouke-Jan Hottenga, Gonneke Willemsen, Brenda W. J. H. Penninx, Ilja M. Nolte, Eco J. C. De Geus, Xiaoling Wang, Harold Snieder

Biostatistics Faculty Publications

Heart rate variability is an important risk factor for cardiovascular disease and all-cause mortality. The acetylcholine pathway plays a key role in explaining heart rate variability in humans. We assessed whether 443 genotyped and imputed common genetic variants in eight key genes (CHAT, SLC18A3, SLC5A7, CHRNB4, CHRNA3, CHRNA, CHRM2 and ACHE) of the acetylcholine pathway were associated with variation in an established measure of heart rate variability reflecting parasympathetic control of the heart rhythm, the root mean square of successive differences (RMSSD) of normal RR intervals. The association was studied in a …