Publications by authors named "Matthew O Goodman"

Polygenic risk scores (PRSs) depend on genetic ancestry due to differences in allele frequencies between ancestral populations. This leads to implementation challenges in diverse populations. We propose a framework to calibrate PRS based on ancestral makeup.

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Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, and together may provide a more complete picture of sleep health, while also illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches.

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Background: Excessive daytime sleepiness (EDS), experienced in 10% to 20% of the population, has been associated with cardiovascular disease and death. However, the condition is heterogeneous and is prevalent in individuals having short and long sleep duration. We sought to clarify the relationship between sleep duration subtypes of EDS with cardiovascular outcomes, accounting for these subtypes.

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Article Synopsis
  • * Sleep patterns were categorized into "regular-optimal" (7 hours of consistent sleep) and "irregular-insufficient" (5.8 hours of inconsistent sleep), using wrist actigraphy and other measurements.
  • * Findings revealed that participants with "regular-optimal" sleep had a 39% lower risk of death compared to those with "irregular-insufficient" sleep, emphasizing the importance of maintaining consistent sleep habits for better health and longevity.
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Introduction: Polygenic Risk Scores (PRSs) are summaries of genetic risk alleles for an outcome.

Methods: We used summary statistics from five GWASs of AD to construct PRSs in 4,189 diverse Hispanics/Latinos (mean age 63 years) from the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA). We assessed the PRS associations with MCI in the combined set of people and in diverse subgroups, and when including and excluding the APOE gene region.

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As suggested by previous research, sleep health is assumed to be a key determinant of future morbidity and mortality. In line with this, recent studies have found that poor sleep is associated with impaired cognitive function. However, to date, little is known about brain structural abnormalities underlying this association.

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Article Synopsis
  • The study evaluates the effectiveness and shortcomings of polygenic risk scores (PRSs) in predicting various blood pressure (BP) phenotypes among different population groups, focusing on methods like "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2).
  • It utilizes datasets from several biobanks, including MGB Biobank and UK Biobank, to train and validate PRSs based on self-reported race/ethnic backgrounds such as Asian, Black, Hispanic/Latino, and White.
  • Findings indicate that the PRS-CSx method, which combines weighted PRSs from multiple GWAS, provides the most accurate predictions across all racial/ethnic groups, with better effectiveness in females
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We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet ∼20× faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds.

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Background: Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia, may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (eg, inflammatory) and protective (eg, increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner.

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In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS.

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Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Iron and heme metabolism, implicated in ventilatory control and OSA comorbidities, was associated with OSA phenotypes in recent admixture mapping and gene enrichment analyses. However, its causal contribution was unclear.

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Commonly in biomedical research, studies collect data in which an outcome measure contains informative excess zeros; for example, when observing the burden of neuritic plaques (NPs) in brain pathology studies, those who show none contribute to our understanding of neurodegenerative disease. The outcome may be characterized by a mixture distribution with one component being the "structural zero" and the other component being a Poisson distribution. We propose a novel variance components score test of genetic association between a set of genetic markers and a zero-inflated count outcome from a mixture distribution.

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