Statistical power analysis of health, physical education, and recreation research.
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Health Surveys↗
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Statistical power in physical anthropology: a technical report.
A statistical power analysis of The American Journal of Physical Anthropology (Volume 44, 1976) was conducted. Twenty-five articles, which included 3,304 major significance tests, constituted the final sample. Resultant power estimates of 0.38, 0.62, and 0.81, corresponding to small, medium, and large population effects respectively, were obtained. Although the medium effect size estimate falls short of the recommended 0.80 level, the statistical power of physical anthropological research fares well relative to several of the social scientific fields of inquiry.
Anthropology, Physical↗
An Updated Polygenic Index Repository: Expanded Phenotypes, New Cohorts, and Improved Causal Inference.
Polygenic indexes (PGIs) - DNA-based predictors of individual phenotypes - have become essential tools across biomedical and social sciences. We introduce Version 2 of the Polygenic Index Repository, which expands phenotype coverage from 47 to 61, increases the number of participating datasets from 11 to 20, and adopts a more consistent and improved methodology for PGI construction. For 16 phenotypes, we leverage summary statistics from an updated GWAS meta-analysis with greater statistical power compared to the original release, thereby improving the PGI's predictive power. To improve power for family-based analyses, we provide imputed parental PGIs in all datasets with first-degree relatives and offer a framework for interpreting results from analyses that control for parental PGIs. We illustrate the utility of parental PGIs using two applications: (1) comparing PGI associations with and without parental PGI controls for all phenotypes in two Repository datasets with family data, and (2) for BMI and diastolic blood pressure, exploring the contribution of causal versus non-causal components of PGI associations to the imperfect portability of PGIs across subgroups within a genetic ancestry. Collectively, the updates enhance predictive performance, broaden the Repository's scope, and introduce novel resources that reduce confounding bias and improve interpretability.
Journal Article↗
Statistical problems in the analysis of comparative pharmaco-EEG trials.
Assuming already condensed data from the EEG power spectra, problems arising with the statistical analysis of such data in comparative pharmaco-EEG trials are discussed. Since, in general, there is only a limited number of subjects available in a study to evaluate and compare the effects of a number of drugs by means of the EEG, the experimental design is usually of the cross-over type. With respect to this design, the requirements for the application and for the appropriate analysis are stated. Further, the problems are indicated which arise when the number of subjects is not a multiple of the number of drugs and/or when there are missing values. Finally, the topic of repeated null hypothesis testing and the inflation of the overall significance level is treated. Suggestions are made how to at least partly avoid the indicated problems at the present stage of methodological statistical research.
Analysis of Variance↗
Asymmetric integration of various cancer datasets for identifying risk-associated variants and genes.
MOTIVATION: Cancer genomic research provides an opportunity to identify cancer risk-associated genes, but often suffers from undesirable low statistical power due to a limited sample size. Integrated analysis with different cancers has the potential to enhance statistical power for identifying pan-cancer risk genes. However, substantial heterogeneity across various cancers makes this challenging. RESULTS: Recently, a novel asymmetric integration method was developed that can deal with data heterogeneity and exclude unhelpful datasets from the analysis. We adapted and applied this method to integrate genotype datasets with matched case and control individuals from the Michigan Genomics Initiative, using each cancer as the primary dataset of interest and the other cancers as auxiliary datasets, respectively. Conditional logistic regression models were coupled with the asymmetric integrated framework to handle the matched case-control study design and permutation tests were performed to control for false discovery rates (FDRs). At the same FDR level, the integrated analysis found more potential genetic variants and genes that are associated with the risks of various cancers, showcasing the promise of the proposed approach for integrated analysis of cancer datasets. AVAILABILITY AND IMPLEMENTATION: Our method is available as source code at https://github.com/rxxwang/integrate_cancer.
Journal Article↗
PoweREST: Statistical Power Estimation for Spatial Transcriptomics Experiments to Detect Differentially Expressed Genes Between Two Conditions.
Recent advancements in Spatial Transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost of current ST data generation techniques restricts its application in large-scale population studies. Consequently, there is a pressing need to maximize the use of available resources to achieve robust statistical power. One fundamental question in ST analysis is to detect differentially expressed genes (DEGs) among different conditions using ST data. Such DEG analysis is often performed but the associated power calculation is rarely discussed in the literature. To address this gap, we introduce, PoweREST (https://github.com/lanshui98/PoweREST), a power estimation tool designed to support power calculation of DEG detection with 10X Genomics Visium data. PoweREST enables power estimation both before any ST experiments or after preliminary data are collected, making it suitable for a wide variety of power analyses in ST studies. We also provide a user-friendly, program-free web application (https://lanshui.shinyapps.io/PoweREST/), allowing users to interactively calculate and visualize the study power along with relevant the parameters.
Differentially expressed genes↗
Standardised method of determining vibratory perception thresholds for diagnosis and screening in neurological investigation.
Vibration threshold determinations were made by means of an electromagnetic vibrator at three sites (carpal, tibial, and tarsal), which were primarily selected for examining patients with polyneuropathy. Because of the vast variation demonstrated for both vibrator output and tissue damping, the thresholds were expressed in terms of amplitude of stimulator movement measured by means of an accelerometer, instead of applied voltage which is commonly used. Statistical analysis revealed a higher power of discimination for amplitude measurements at all three stimulus sites. Digital read-out gave the best statistical result and was also most practical. Reference values obtained from 110 healthy males, 10 to 74 years of age, were highly correlated with age for both upper and lower extremities. The variance of the vibration perception threshold was less than that of the disappearance threshold, and determination of the perception threshold alone may be sufficient in most cases.
Adolescent↗
Meta-analysis of over 8,000 individuals from Hawai'i and Samoa for genetic associations to cardiometabolic phenotypes.
Although genome-wide association studies (GWAS) now routinely reveal genetic associations and biological insights in millions of individuals, underrepresentation of global populations, such as those from Polynesia, continue to persist. These exclusions, often driven by logistical challenges and lack of data, prevent systematic identification of population-enriched associations, such as the association of the missense variant at the CREBRF locus to BMI and type 2 diabetes discovered commonly occurring in Polynesian populations due to its rarity in global populations. Armed with the recently updated TOPMed imputation panel that could benefit studies in diverse populations that previously had poorer imputation performance, we performed the first GWAS of Native Hawaiians and largest to date of Polynesian-ancestry populations (combined N up to 8,461) to identify population-enriched associations for 13 adiposity and cardiometabolic traits available across both cohorts: BMI, fasting glucose, fasting insulin, HDL, height, hip circumference, HOMA-IR, LDL, T2D, total cholesterol, triglycerides, waist circumference, and waist-hip ratio. We found 25 trait-loci associations that met genome-wide significance: 20 previously reported or known associations and 5 associations newly confirmed via meta-analysis. In particular, with improved statistical power, we were able to confirm the suspected association between the missense CREBRF variant with fasting glucose levels. The remaining 4 potentially novel loci-trait associations for BMI, LDL, and waist-hip ratio, however, were not replicated in multi-ethnic datasets from All-of-Us despite having reasonable power to replicate. The lack of Polynesian-enriched findings outside of the CREBRF locus informs the bounds of the effect sizes or frequency of any enriched variants, and suggests that further expansion of cohort sizes from this region of the world and improved imputation references specific to these populations are needed to identify more population-enriched associations.
Journal Article↗
Genetically-predicted placental gene expression links to uterine fibroids and endometriosis.
INTRODUCTION: Mother-to-child disease transmission begins in utero, with the placenta playing a critical role in pregnancy and offspring health. Uterine leiomyomata (fibroids, UFs) and endometriosis (ENDO) are common gynecologic diseases that have substantial overlaps in symptomology and risk factors, however drivers of disease risk remain unclear. The objective of this study was to investigate shared placental genetic associations across ENDO and UFs. METHODS: Genome-wide association study (GWAS) summary statistics were utilized from a published study of UFs (PMID: 40050615) and meta-analyzed for ENDO (24,092 cases and 548,255 controls). To improve our statistical power, we applied Multi-Trait Analysis of GWAS to the ENDO and UF GWAS. We estimated genetically predicted gene expression using S-PrediXcan across 49 tissues using GTEx v7 and a placental tissue expression model. RESULTS: We identified 54 and 14 genes where predicted expression in the placenta was significantly associated with UFs and ENDO, respectively. Twenty-one of these genes were shared between UFs and ENDO. Significant gene associations in placenta tissue were compared to the other 48 GTEx v7 tissue types to identify placenta specific associations. There were 40 and 13 significant gene-tissue associations specific to the placenta across UFs and ENDO, respectively. Eight of the placenta-specific genes were shared across UFs and ENDO. The strongest shared placenta-specific associations included PRKCI and HRH1. CONCLUSIONS: Our findings demonstrate a shared genetic relationship between UFs and ENDO in the placenta. The placenta specific associations suggest that dysregulation of early developmental pathways may contribute to a shared genetic origin of these diseases.
Female↗
Cardiac pacing and pacemakers IX. Statistical analysis of pacemaker data.
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Aged↗
The Chatham Blood Pressure Study. An application of Bayesian growth curve models to a longitudinal study of blood pressure in children.
Recent developments in statistics have produced powerful methods that facilitate the analysis of longitudinal studies. These methods are illustrated by an analysis of a longitudinal study of blood pressure in children. The results of the study show a clear tendency for blood pressure to increase with age, and Asian children tend to have lower blood pressures than their Caucasian counterparts of the same age. There is evidence to support the hypothesis that blood pressures track.
Age Factors↗
Computerized EEG analysis for studying the effect of drugs on the central nervous system.
Samples of our experience in quantitative pharmaco-EEG are reviewed to discuss and define its applicability and limits. Simple processing systems, such as the computation of Hjorth's descriptors, are useful for on-line monitoring of drug-induced EEG modifications which are evident also at the visual visual analysis. Power spectral analysis is suitable to identify and quantify EEG effects not evident at the visual inspection. It demonstrated how the EEG effects of compounds in a long-acting formulation vary according to the sampling time and the explored cerebral area. EEG modifications not detected by power spectral analysis can be defined by comparing statistically (F test) the spectral values of the EEG from a single lead at the different samples (longitudinal comparison), or the spectral values from different leads at any sample (intrahemispheric comparison). The presently available procedures of quantitative pharmaco-EEG are effective when applied to the study of mutltilead EEG recordings in a statistically significant sample of population. They do not seem reliable in the monitoring of directing of neuropyschiatric therapies in single patients, due to individual variability of drug effects.
Alcoholic Intoxication↗
Research on multi-trait genome association study method based on Shannon information entropy.
BACKGROUND: Genetic analysis of complex traits is crucial for elucidating disease mechanisms and biological inheritance processes. However, traditional Genome-wide Association Study (GWAS) for single trait often fail to capture the synergistic effects of genetic loci on multiple traits. METHODS: This study proposes a method for analyzing the association between multiple traits and gene regions based on Shannon information entropy. Innovatively, Shannon information entropy is introduced to integrate gene region information as genetic entropy, thereby constructing an Inverse Shannon Entropy-Multi-Trait Association Analysis of Gene Region genetic model (InvSE-MTAGR). Furthermore, a partial regression test is applied to the model to establish the Inverse Partial Shannon Entropy-Multi-Trait Association Analysis of Gene Region method (InvPSE-MTAGR). When performing multi-trait analysis with InvSE-MTAGR, the method achieved statistical significance by accumulating minor effects, thereby enhancing the ability to identify pleiotropic gene regions. RESULTS: The simulation results showed that the proposed multi-trait gene region association analysis method performed well in terms of both Type I error rate control and statistical power. Leveraging tomato and sorghum datasets for validation, the proposed multi-trait gene region association analysis method based on Shannon information entropy accurately pinpointed most of the gene regions harboring candidate genes. CONCLUSION: The study reveals the advantage of multi-trait method in integrating weak-effect pleiotropic signals and capturing the correlation among traits, which provides an efficient theoretical tool for dynamic analysis of complex multi-trait genetic networks and multi-target collaborative breeding of crops.
Genome-Wide Association Study↗
Communication disorders: a power analytic assessment of recent research.
This study assessed the relative statistical power of contemporary research in communication disorders. Results of the analysis, based upon an evaluation of two major journals, revealed overall mean power figures of 0.16, 0.44, and 0.73 for small, medium, and large effect sizes, respectively. Interdisciplinary comparisons indicated that low statistical power is not unique to research in communication disorders, but is apparent in other behavioral science areas as well. Several alternatives are offered to the researcher who will want to ensure sufficient power for his investigation on an a priori basis. The implications of this study are discussed in reference to the experimenter/clinician model.
Audiology↗
Clinical experience with the isotopic cardiac pacemaker.
Clinical experience with isotopic pacemakers in 59 patients is compared with that in 77 control patients having conventional chemical battery-powered pulse generators. The review covers a 51/2-year period. Statistical analysis of the two series is impossible because of the numerous variables such as age, type of disease, number of controls, types of test and control pulse generators, dates of insertion, and protocol regulations. However, there were pulse generator failures in the control group, but not in the test group. Though not proven in this study, the isotopic cardiac pacer is likely to last longer than conventional chemical battery-powered units, and could provide lifetime pacing for many patients. The risk of carcinogenesis is minimal and seems negligible in older patients. The isotopic cardiac pacer, in spite of restrictions of the Nuclear Regulatory Commission, should be considered for any patient with a life expectancy of 10 or more years. Paradoxically, it might be indicated in older rather than younger patients.
Adult↗
Physiological effects of dynamic work on a bicycle ergometer combined with different types of static contraction.
The effects on heart rate, oxygen uptake, and pulmonary ventilation of muscular exercises, including both dynamic contractions, either simple or combined, were studied in 4 male subjects, aged 21 to 23 years. The dynamic work consisted in cycling on an ergometric bicycle at three power levels: 40, 80, and 100 W. The static work consisted in pushing against, pulling and holding with the arms a 6, 9, 12, or 18 kg load. The physiological effects are expressed as cardiac cost (delta HR), oxygen cost (delta VO2) and ventilation cost (delta V). The physiological cost of the combined work increases according to the cycling power and to the isometric load developed. A statistical analysis shows that the costs of combined work are not different from the sum of the costs of the static and dynamic contractions measured separately. Thus, the physiological responses to the combinations investigated are of an additive type.
Adult↗
Network Interactions of Circulating FGF23, HRG-HMGB1, and Cardiac Disease in CKD.
KEY POINTS: Multitrait analysis of genome-wide association study boosts the statistical power to identify novel genetic traits for fibroblast growth factor 23. A functional genomics approach aided network discovery to identify histidine-rich glycoprotein (HRG) and high-mobility group protein box 1 (HMGB1) as key regulators of cardiac disease in CKD. Integration of clinical and genetic data enhances the discovery power and is crucial for understanding the genetic underpinnings of mineral bone disorder related to CKD. BACKGROUND: Genome-wide association studies (GWAS) have identified numerous genetic loci associated with mineral metabolism markers but have exclusively focused on single-trait analysis. In this study, we performed a multitrait analysis of GWAS (MTAG) of mineral metabolism, exploring overlapping genetic architecture between traits to identify novel genetic associations for fibroblast growth factor 23 (FGF23). METHODS: We applied MTAG to variants common to GWAS of five genetically correlated mineral metabolism markers in participants of European ancestry. We integrated UK Biobank GWAS for blood levels for phosphate, 25-hydroxyvitamin D, and calcium (n=366,484) and Cohorts for Heart and Aging Research in Genetic Epidemiology GWAS for parathyroid hormone (n=29,155) and FGF23 (n=13,716). We then used supervised and unsupervised deep machine learning to identify novel associations between genetic traits and FGF23. RESULTS: MTAG increased the effective sample size for mineral metabolism markers to n=50,325 for FGF23. After clumping, MTAG identified independent genome-wide significant single-nucleotide polymorphisms for all traits, including 62 loci for FGF23. Many of these loci have not been previously reported in single-trait analyses. Through a functional genomics approach, we identified histidine-rich glycoprotein (HRG) and high-mobility group box 1 (HMGB1) as master regulators of downstream canonical pathways associated with circulating FGF23, and both genes were highly enriched in hypertrophied cardiac tissue of deceased hemodialysis patients. In addition, we found that DNMT3A was associated with uremic toxin, 8-hydroxy-2-deoxyguanosine, a biomarker of DNA damage. In silico gene perturbation analysis revealed that DNMT3A is protective in patients with heart failure caused by hypertrophied or dilated cardiomyopathy. CONCLUSIONS: Our findings highlight the importance of MTAG analysis of mineral metabolism markers to boost the number of genome-wide significant loci for FGF23 to identify novel genetic traits. Functional genomics revealed novel networks that inform unique cellular functions and identified HRG and HMGB1 as key master regulators of FGF23 and cardiovascular disease in CKD.
bones, stones, and mineral metabolism↗
PYRAMA: an open-source tool for advanced meta-analysis of genome wide association studies.
MOTIVATION: Genome-wide association study (GWAS) meta-analysis tools are essential for integrating summary statistics across multiple cohorts, thereby increasing statistical power and validating genetic associations. Widely cited tools, such as METAL, PLINK, and GWAMA, have facilitated numerous significant discoveries in the field of GWAS. Nevertheless, these tools offer a limited set of meta-analysis methods and typically require users to have prior experience with command-line tools to be executed. RESULTS: We present here PYRAMA, an open-source tool which is designed for meta-analysis of genome wide association studies. This work introduces an easy-to-use software package that includes several meta-analysis methods that are absent in similar software packages. PYRAMA is faster compared to other tools, supports robust methods for analysis and meta-analysis, fixed-effects, random-effects and Bayesian meta-analysis and it is currently the only tool that supports meta-analysis with imputation of summary statistics. It is available both as a standalone tool and as a freely available web server. AVAILABILITY AND IMPLEMENTATION: https://github.com/pbagos/PYRAMA, https://doi.org/10.5281/zenodo.17830449.
Genome-Wide Association Study↗