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Article ; Online: Hierarchicell: an R-package for estimating power for tests of differential expression with single-cell data.

Zimmerman, Kip D / Langefeld, Carl D

2021 Volume 22, Issue 1, Page(s) 319

Abstract: Background: Study design is a critical aspect of any experiment, and sample size calculations for statistical power that are consistent with that study design are central to robust and reproducible results. However, the existing power calculators for ... ...

Abstract	Background: Study design is a critical aspect of any experiment, and sample size calculations for statistical power that are consistent with that study design are central to robust and reproducible results. However, the existing power calculators for tests of differential expression in single-cell RNA-seq data focus on the total number of cells and not the number of independent experimental units, the true unit of interest for power. Thus, current methods grossly overestimate the power. Results: Hierarchicell is the first single-cell power calculator to explicitly simulate and account for the hierarchical correlation structure (i.e., within sample correlation) that exists in single-cell RNA-seq data. Hierarchicell, an R-package available on GitHub, estimates the within sample correlation structure from real data to simulate hierarchical single-cell RNA-seq data and estimate power for tests of differential expression. This multi-stage approach models gene dropout rates, intra-individual dispersion, inter-individual variation, variable or fixed number of cells per individual, and the correlation among cells within an individual. Without modeling the within sample correlation structure and without properly accounting for the correlation in downstream analysis, we demonstrate that estimates of power are falsely inflated. Hierarchicell can be used to estimate power for binary and continuous phenotypes based on user-specified number of independent experimental units (e.g., individuals) and cells within the experimental unit. Conclusions: Hierarchicell is a user-friendly R-package that provides accurate estimates of power for testing hypotheses of differential expression in single-cell RNA-seq data. This R-package represents an important addition to single-cell RNA analytic tools and will help researchers design experiments with appropriate and accurate power, increasing discovery and improving robustness and reproducibility.
MeSH term(s)	Gene Expression Profiling ; Humans ; RNA/genetics ; RNA-Seq ; Reproducibility of Results ; Research Design ; Sequence Analysis, RNA ; Single-Cell Analysis ; Software
Chemical Substances	RNA (63231-63-0)
Language	English
Publishing date	2021-05-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2041499-7
ISSN	1471-2164 ; 1471-2164
ISSN (online)	1471-2164
ISSN	1471-2164
DOI	10.1186/s12864-021-07635-w
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Article ; Online: Validation of Epigenetic Markers for the Prediction of Response to Topical Corticosteroid Treatment in Eosinophilic Esophagitis.

Jensen, Elizabeth T / Langefeld, Carl D / Howard, Timothy D / Dellon, Evan S

Clinical and translational gastroenterology

2023 Volume 14, Issue 9, Page(s) e00622

Abstract: Introduction: We previously identified 18 CpG methylation biomarkers associated with treatment response to topical corticosteroids (tCS) in eosinophilic esophagitis (EoE). In this study, in an independent cohort, we assessed the validity of these CpG ... ...

Abstract	Introduction: We previously identified 18 CpG methylation biomarkers associated with treatment response to topical corticosteroids (tCS) in eosinophilic esophagitis (EoE). In this study, in an independent cohort, we assessed the validity of these CpG sites as treatment response biomarkers. Methods: DNA was extracted from prospectively biobanked esophageal biopsies from patients with newly diagnosed EoE enrolled in a randomized trial of 2 tCS formulations. Histologic response was defined as <15 eosinophils per high-power field. Pretreatment DNA methylation was assayed on the Illumina Human MethylationEPIC BeadChip. Logistic regression and area under the receiver operating characteristic curve analyses, adjusting for chip, position on the chip, age, sex, and baseline eosinophil count, were computed to test for an association between DNA methylation and treatment response at the 18 previously identified CpG sites. Results: We analyzed 88 patients (58 histologic responders, 30 nonresponders), with a mean age of 38 ± 16 years, 64% male, 97% White race. Of the 18 CpG sites, 13 met quality control criteria, and 3 were associated with responder status ( P < 0.012), including sites within UNC5B (cg26152017), ITGA6 (cg01044293), and LRRC8A (cg13962589). All 3 showed evidence of reduced methylation in treatment responders, consistent with the original discovery associations. The predictive probability for nonresponse with all 3 CpG sites was strong (area under the receiver operating characteristic curve = 0.79). Discussion: We validated epigenetic biomarkers (CpG methylation sites) for the prediction of tCS response in patients with EoE in an independent population. While not all previously identified markers replicated, 3 demonstrated a relatively high predictive probability for response to treatment and hold promise for guiding tCS treatment in EoE.
MeSH term(s)	Humans ; Male ; Young Adult ; Adult ; Middle Aged ; Female ; Eosinophilic Esophagitis/diagnosis ; Eosinophilic Esophagitis/drug therapy ; Eosinophilic Esophagitis/genetics ; Glucocorticoids ; Biomarkers/analysis ; Epigenesis, Genetic ; Membrane Proteins ; Netrin Receptors
Chemical Substances	Glucocorticoids ; Biomarkers ; LRRC8A protein, human ; Membrane Proteins ; UNC5B protein, human ; Netrin Receptors
Language	English
Publishing date	2023-09-01
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2581516-7
ISSN	2155-384X ; 2155-384X
ISSN (online)	2155-384X
ISSN	2155-384X
DOI	10.14309/ctg.0000000000000622
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Article ; Online: Identification of influential rare variants in aggregate testing using random forest importance measures.

Blumhagen, Rachel Z / Schwartz, David A / Langefeld, Carl D / Fingerlin, Tasha E

Annals of human genetics

2023 Volume 87, Issue 4, Page(s) 184–195

Abstract: Aggregate tests of rare variants are often employed to identify associated regions compared to sequentially testing each individual variant. When an aggregate test is significant, it is of interest to identify which rare variants are "driving" the ... ...

Abstract	Aggregate tests of rare variants are often employed to identify associated regions compared to sequentially testing each individual variant. When an aggregate test is significant, it is of interest to identify which rare variants are "driving" the association. We recently developed the rare variant influential filtering tool (RIFT) to identify influential rare variants and showed RIFT had higher true positive rates compared to other published methods. Here we use importance measures from the standard random forest (RF) and variable importance weighted RF (vi-RF) to identify influential variants. For very rare variants (minor allele frequency [MAF] < 0.001), the vi-RF:Accuracy method had the highest median true positive rate (TPR = 0.24; interquartile range [IQR]: 0.13, 0.42) followed by the RF:Accuracy method (TPR = 0.16; IQR: 0.07, 0.33) and both were superior to RIFT (TPR = 0.05; IQR: 0.02, 0.15). Among uncommon variants (0.001 < MAF < 0.03), the RF methods had higher true positive rates than RIFT while observing comparable false positive rates. Finally, we applied the RF methods to a targeted resequencing study in idiopathic pulmonary fibrosis (IPF), in which the vi-RF approach identified eight and seven variants in TERT and FAM13A, respectively. In summary, the vi-RF provides an improved, objective approach to identifying influential variants following a significant aggregate test. We have expanded our previously developed R package RIFT to include the random forest methods.
MeSH term(s)	Humans ; Random Forest ; Gene Frequency ; Idiopathic Pulmonary Fibrosis ; Sequence Analysis, DNA ; GTPase-Activating Proteins
Chemical Substances	FAM13A protein, human ; GTPase-Activating Proteins
Language	English
Publishing date	2023-05-23
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	333-5
ISSN	1469-1809 ; 0003-4800
ISSN (online)	1469-1809
ISSN	0003-4800
DOI	10.1111/ahg.12509
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Article ; Online: Reply to: A balanced measure shows superior performance of pseudobulk methods in single-cell RNA-sequencing analysis.

Zimmerman, Kip D / Evans, Ciaran / Langefeld, Carl D

Nature communications

2022 Volume 13, Issue 1, Page(s) 7852

Language	English
Publishing date	2022-12-22
Publishing country	England
Document type	Letter
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-35520-x
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Article ; Online: A practical solution to pseudoreplication bias in single-cell studies.

Zimmerman, Kip D / Espeland, Mark A / Langefeld, Carl D

Nature communications

2021 Volume 12, Issue 1, Page(s) 738

Abstract: Cells from the same individual share common genetic and environmental backgrounds and are not statistically independent; therefore, they are subsamples or pseudoreplicates. Thus, single-cell data have a hierarchical structure that many current single- ... ...

Abstract	Cells from the same individual share common genetic and environmental backgrounds and are not statistically independent; therefore, they are subsamples or pseudoreplicates. Thus, single-cell data have a hierarchical structure that many current single-cell methods do not address, leading to biased inference, highly inflated type 1 error rates, and reduced robustness and reproducibility. This includes methods that use a batch effect correction for individual as a means of accounting for within-sample correlation. Here, we document this dependence across a range of cell types and show that pseudo-bulk aggregation methods are conservative and underpowered relative to mixed models. To compute differential expression within a specific cell type across treatment groups, we propose applying generalized linear mixed models with a random effect for individual, to properly account for both zero inflation and the correlation structure among measures from cells within an individual. Finally, we provide power estimates across a range of experimental conditions to assist researchers in designing appropriately powered studies.
MeSH term(s)	Computer Simulation ; Quality Control ; Sequence Analysis, RNA/methods ; Transcriptome/genetics
Language	English
Publishing date	2021-02-02
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-021-21038-1
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Article ; Online: Factors Associated With Participation in Clinical Trials Among Patients With Lupus.

Harry, Onengiya / Langefeld, Carl D / Crosby, Lori E / Modi, Avani C

Journal of clinical rheumatology : practical reports on rheumatic & musculoskeletal diseases

2022 Volume 28, Issue 3, Page(s) 132–136

Abstract: Background/objective: Participation rates for clinical trials, including lupus trials, in the United States are low, but are even lower for underrepresented minorities. The impact of underrepresentation in trials can be far-reaching and is problematic ... ...

Abstract	Background/objective: Participation rates for clinical trials, including lupus trials, in the United States are low, but are even lower for underrepresented minorities. The impact of underrepresentation in trials can be far-reaching and is problematic because female subjects of color with lupus experience greater morbidity and mortality. As such, the overarching goal of this study was to characterize the factors that influence participation in lupus clinical trials. Methods: The Lupus and Allied Diseases Association, the Lupus Foundation of America, and the Lupus Research Alliance collected data for their externally led Patient-Focused Drug Development Initiative-for the purpose of understanding and improving the rates of participation in lupus-related clinical trials. Participants completed a 46-question survey (in English or Spanish) electronically or on paper, which was distributed online or at lupus events. Logistic regression was used to test whether demographic and disease characteristics were associated with participation in past lupus trials. Results: Data were available for 2220 respondents. Black respondents with lupus were more likely, than their White and Hispanic counterparts, to have participated in past clinical trials (p < 0.05). Although not statistically significant, Hispanic respondents were also more likely to have participated than their White counterparts (odds ratio, 1.40; 95% confidence interval, 0.96-2.11). Both demographic (ie, race/ethnicity) and medical (ie, disease severity defined as more organ involvement) factors seem to be important determinants of participation in clinical trials (p < 0.05). Conclusions: Combining the results from this study and prior research provides insight into recruitment strategies to increase participation rates of historically underrepresented minorities.
MeSH term(s)	Female ; Humans ; Clinical Trials as Topic ; Minority Groups ; Surveys and Questionnaires ; United States ; Lupus Erythematosus, Systemic/epidemiology ; Patient Participation
Language	English
Publishing date	2022-01-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	1283266-2
ISSN	1536-7355 ; 1076-1608
ISSN (online)	1536-7355
ISSN	1076-1608
DOI	10.1097/RHU.0000000000001821
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Article ; Online: Intrinsic DNA topology as a prioritization metric in genomic fine-mapping studies.

Ainsworth, Hannah C / Howard, Timothy D / Langefeld, Carl D

Nucleic acids research

2020 Volume 48, Issue 20, Page(s) 11304–11321

Abstract: In genomic fine-mapping studies, some approaches leverage annotation data to prioritize likely functional polymorphisms. However, existing annotation resources can present challenges as many lack information for novel variants and/or may be uninformative ...

Abstract	In genomic fine-mapping studies, some approaches leverage annotation data to prioritize likely functional polymorphisms. However, existing annotation resources can present challenges as many lack information for novel variants and/or may be uninformative for non-coding regions. We propose a novel annotation source, sequence-dependent DNA topology, as a prioritization metric for fine-mapping. DNA topology and function are well-intertwined, and as an intrinsic DNA property, it is readily applicable to any genomic region. Here, we constructed and applied Minor Groove Width (MGW) as a prioritization metric. Using an established MGW-prediction method, we generated a MGW census for 199 038 197 SNPs across the human genome. Summarizing a SNP's change in MGW (ΔMGW) as a Euclidean distance, ΔMGW exhibited a strongly right-skewed distribution, highlighting the infrequency of SNPs that generate dissimilar shape profiles. We hypothesized that phenotypically-associated SNPs can be prioritized by ΔMGW. We tested this hypothesis in 116 regions analyzed by a Massively Parallel Reporter Assay and observed enrichment of large ΔMGW for functional polymorphisms (P = 0.0007). To illustrate application in fine-mapping studies, we applied our MGW-prioritization approach to three non-coding regions associated with systemic lupus erythematosus. Together, this study presents the first usage of sequence-dependent DNA topology as a prioritization metric in genomic association studies.
MeSH term(s)	African Continental Ancestry Group/genetics ; Base Sequence ; Bayes Theorem ; Chromosome Mapping/methods ; DNA/chemistry ; DNA-Binding Proteins/genetics ; Databases, Genetic ; European Continental Ancestry Group/genetics ; Genome, Human ; Genome-Wide Association Study/methods ; Genomics/methods ; Hispanic Americans/genetics ; Humans ; Lupus Erythematosus, Systemic/genetics ; Molecular Sequence Annotation/methods ; Polymorphism, Single Nucleotide ; Proteins/genetics ; Quantitative Trait Loci ; STAT4 Transcription Factor/genetics ; src-Family Kinases/genetics
Chemical Substances	DNA-Binding Proteins ; FAM167A protein, human ; Proteins ; STAT4 Transcription Factor ; STAT4 protein, human ; TNIP1 protein, human ; DNA (9007-49-2) ; BLK protein, human (EC 2.7.10.2) ; src-Family Kinases (EC 2.7.10.2)
Language	English
Publishing date	2020-11-10
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkaa877
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Article ; Online: Identification of Influential Variants in Significant Aggregate Rare Variant Tests.

Blumhagen, Rachel Z / Schwartz, David A / Langefeld, Carl D / Fingerlin, Tasha E

Human heredity

2021 , Page(s) 1–13

Abstract: Introduction: Studies that examine the role of rare variants in both simple and complex disease are increasingly common. Though the usual approach of testing rare variants in aggregate sets is more powerful than testing individual variants, it is of ... ...

Abstract	Introduction: Studies that examine the role of rare variants in both simple and complex disease are increasingly common. Though the usual approach of testing rare variants in aggregate sets is more powerful than testing individual variants, it is of interest to identify the variants that are plausible drivers of the association. We present a novel method for prioritization of rare variants after a significant aggregate test by quantifying the influence of the variant on the aggregate test of association. Methods: In addition to providing a measure used to rank variants, we use outlier detection methods to present the computationally efficient Rare Variant Influential Filtering Tool (RIFT) to identify a subset of variants that influence the disease association. We evaluated several outlier detection methods that vary based on the underlying variance measure: interquartile range (Tukey fences), median absolute deviation, and SD. We performed 1,000 simulations for 50 regions of size 3 kb and compared the true and false positive rates. We compared RIFT using the Inner Tukey to 2 existing methods: adaptive combination of p values (ADA) and a Bayesian hierarchical model (BeviMed). Finally, we applied this method to data from our targeted resequencing study in idiopathic pulmonary fibrosis (IPF). Results: All outlier detection methods observed higher sensitivity to detect uncommon variants (0.001 < minor allele frequency, MAF > 0.03) compared to very rare variants (MAF <0.001). For uncommon variants, RIFT had a lower median false positive rate compared to the ADA. ADA and RIFT had significantly higher true positive rates than that observed for BeviMed. When applied to 2 regions found previously associated with IPF including 100 rare variants, we identified 6 polymorphisms with the greatest evidence for influencing the association with IPF. Discussion: In summary, RIFT has a high true positive rate while maintaining a low false positive rate for identifying polymorphisms influencing rare variant association tests. This work provides an approach to obtain greater resolution of the rare variant signals within significant aggregate sets; this information can provide an objective measure to prioritize variants for follow-up experimental studies and insight into the biological pathways involved.
Language	English
Publishing date	2021-02-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2424-7
ISSN	1423-0062 ; 0001-5652
ISSN (online)	1423-0062
ISSN	0001-5652
DOI	10.1159/000513290
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Article ; Online: Genomics in Rheumatic Diseases: Hope for the Future.

Bridges, S Louis / Langefeld, Carl D

Rheumatic diseases clinics of North America

2017 Volume 43, Issue 3, Page(s) xv–xvi

MeSH term(s)	Genomics/methods ; Genomics/trends ; Humans ; Rheumatic Diseases/genetics
Language	English
Publishing date	2017-08-07
Publishing country	United States
Document type	Editorial ; Introductory Journal Article
ZDB-ID	92118-x
ISSN	1558-3163 ; 0889-857X
ISSN (online)	1558-3163
ISSN	0889-857X
DOI	10.1016/j.rdc.2017.05.001
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Article ; Online: Social Determinants of Health and Cerebral Small Vessel Disease: Is Epigenetics a Key Mediator?

Parodi, Livia / Mayerhofer, Ernst / Narasimhalu, Kaavya / Yechoor, Nirupama / Comeau, Mary E / Rosand, Jonathan / Langefeld, Carl D / Anderson, Christopher D

Journal of the American Heart Association

2023 Volume 12, Issue 13, Page(s) e029862

Abstract: Cerebral small vessel disease is highly prevalent, particularly in marginalized communities, and its incidence is expected to increase given the aging global population. Cerebral small vessel disease contributes to risk for stroke, vascular cognitive ... ...

Abstract	Cerebral small vessel disease is highly prevalent, particularly in marginalized communities, and its incidence is expected to increase given the aging global population. Cerebral small vessel disease contributes to risk for stroke, vascular cognitive impairment and dementia, late-life depression, and gait disorders. A growing body of evidence suggests that adverse outcomes, including cerebral small vessel disease, caused by traditional cardiovascular risk factors are at least partly mediated by epigenetic changes, some of them already beginning during fetal development. Societal and health care access inequities, summarized under the umbrella term social determinants of health, put a higher burden of cardiovascular risk factors on marginalized populations and expose them to an increased risk for adverse outcomes. Social epigenetics has begun to deliver solid evidence that social determinants of health lead to distinct epigenetic signatures that potentially mediate the biological effect of environmental exposures on cardiovascular risk factors. Here, we provide a review of the most recent advances in the epigenetics of cerebral small vessel disease risk factors and social determinants of health and call for research efforts combining insights from both fields to reach a deeper understanding of the causal pathways, ultimately facilitating discovery of new treatment targets for a disease whose burden is magnified by existing health disparities.
MeSH term(s)	Humans ; Social Determinants of Health ; Cerebral Small Vessel Diseases/epidemiology ; Cerebral Small Vessel Diseases/genetics ; Stroke ; Cognitive Dysfunction ; Risk Factors
Language	English
Publishing date	2023-06-22
Publishing country	England
Document type	Journal Article ; Review ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2653953-6
ISSN	2047-9980 ; 2047-9980
ISSN (online)	2047-9980
ISSN	2047-9980
DOI	10.1161/JAHA.123.029862
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