Biology subjects

Langefeld, C. D.

Publications and source records attributed to Langefeld, C. D..

7 recordsLinked to original sources

bioRxiv2023

A cis-regulatory element regulates ERAP2 expression through autoimmune disease risk SNPs

Single nucleotide polymorphisms (SNP) near the ERAP2 gene are associated with autoimmune conditions such as Crohns disease, and birdshot chorioretinopathy, as well as protection against lethal infections, including the Black Death. Due to high linkage disequilibrium (LD), a great number of trait-associated SNPs are correlated with ERAP2 expression, however their functional mechanisms remain unidentified. We used genome editing and functional genomics to identify causal variants that remain obscured by LD. We demonstrate by reciprocal allelic replacement that ERAP2 expression is directly controlled by the genotype of splice region SNP rs2248374. However, we demonstrate that autoimmune disease-risk SNPs located near the downstream LNPEP gene promoter are independently associated with ERAP2 expression. Allele-specific conformation capture assays revealed long-range chromatin contacts between the LNPEP promoter region and the ERAP2 promoter and showed that interactions were stronger in patients carrying the alleles that increase susceptibility to autoimmune diseases. Replacing the disease-associated SNPs in the LNPEP promoter by reference sequences lowered ERAP2 expression. These findings show that clustered GWAS signals associated with diverse autoimmune conditions and lethal infections act in concert to control ERAP2 expression and that disease-associated variants can convert a gene promoter region into a potent enhancer of a distal gene.

genomics↗

bioRxiv2021

Kidney pathological changes alter cell clustering features in single-cell RNA sequencing

Single cell RNA sequencing (scRNA-Seq) is useful to classify cell-specific gene expression profiles in kidney tissue. As viable cells are required, we report an optimized cell dissociation methodology and the necessity of screening tissue histology prior to scRNA-Seq. We demonstrate that glomerular injury can selectively reduce the appearance of groups of cells during analysis of cell clustering and we confirmed reductions in cell-specific markers among injured cells on kidney sections with fluorescence microscopy. Interpretation of scRNA-Seq results may be refined based upon these considerations.

cell biology↗

bioRxiv2020

Genetic Landscape of Gullah African Americans

ObjectivesGullah African Americans are descendants of formerly enslaved Africans living in the Sea Islands along the coast of the southeastern U.S., from North Carolina to Florida. Their relatively high numbers and geographic isolation were conducive to the development and preservation of a unique culture that retains deep African features. Although historical evidence supports a West and Central African ancestry for the Gullah, linguistic and cultural evidence of a connection to Sierra Leone has led to the suggestion of this country/region as their ancestral home. This study sought to elucidate the genetic structure and ancestry of the Gullah. Materials and MethodsWe leveraged whole-genome genotype data from Gullah, African Americans from Jackson, Mississippi, Sierra Leone Africans, and population reference panels from Africa and Europe, to infer population structure, ancestry proportions, and global estimates of admixture. ResultsRelative to southeastern non-Gullah African Americans, the Gullah exhibit higher mean African ancestry, lower European admixture, a similarly small Native American contribution, and stronger male-biased European admixture. A slightly tighter bottleneck in the Gullah 13 generations ago suggests a largely shared demographic history with non-Gullah African Americans. Despite a slightly higher relatedness to Sierra Leone, our data demonstrate that the Gullah are genetically related to many West African populations. DiscussionThis study confirms that subtle differences in African American population structure exist at finer regional levels. Such observations can help to inform medical genetics research in African Americans, and guide the interpretation of genetic data used by African Americans seeking to explore ancestral identities. Research HighlightsO_LIUsing genomic data, we show that the Gullah have lower European and higher West African genomic background compared to non-Gullah African Americans, confirming their diverse African ancestry and rejecting a model that asserts a predominant Sierra Leone origin. C_LIO_LIOur data reveal a largely shared demographic history with southeastern non-Gullah African Americans, but also subtle differences related to high African genetic ancestry due to isolation in the Sea Islands. C_LI

genetics↗

bioRxiv2020

Identification of Influential Variants in Significant Aggregate Rare Variant Tests

IntroductionStudies 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. MethodsIn 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 standard deviation. We performed 1000 simulations for 50 regions of size 3kb and compared the true and false positive rates. We compared RIFT using the Inner Tukey to two 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). ResultsAll outlier detection methods observed higher sensitivity to detect uncommon variants (0.001 < 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 two regions found previously associated with IPF including 100 rare variants, we identified six polymorphisms with the greatest evidence for influencing the association with IPF. DiscussionIn 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.

genetics↗

bioRxiv2020

Pseudoreplication bias in single-cell studies; a practical solution

Cells from the same individual share a common genetic and environmental background and are not 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 overly conservative and underpowered relative to mixed models. We propose applying two-part hurdle 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.

bioinformatics↗

bioRxiv2019

Intrinsic DNA topology as a prioritization metric in genomic fine-mapping studies

In genomic fine-mapping studies, some approaches leverage annotation data to prioritize likely functional polymorphisms. However, existing annotation sources often present challenges as many: lack data for novel variants, offer no context for noncoding regions, and/or are confounded with linkage disequilibrium. 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 an MGW census for 199,038,197 SNPs across the human genome. Summarizing a SNPs change in MGW ({Delta}MGW) as a Euclidean distance, {Delta}MGW 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 {Delta}MGW. We applied Bayesian and frequentist MGW-prioritization approaches to three non-coding regions associated with System Lupus Erythematosus in multiple ancestries. In two regions, including {Delta}MGW resolved the association to a single, trans-ancestral, SNP, corroborated by external functional data. Together, this study presents the first usage of sequence-dependent DNA topology as a prioritization metric in genomic association studies. Graphical AbstractWe hypothesize that SNPs imposing dissimilar minor groove width profiles ({Delta}MGW) are more likely to alter function. {Delta}MGW was interrogated genome-wide and then used as a weighting metric for fine-mapping associations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=153 SRC="FIGDIR/small/837245v2_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@d350adorg.highwire.dtl.DTLVardef@155a2cborg.highwire.dtl.DTLVardef@132e30aorg.highwire.dtl.DTLVardef@1d7b065_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2019

Complement component 4 genes contribute sex-specific vulnerability in diverse illnesses

Many common illnesses differentially affect men and women for unknown reasons. The autoimmune diseases lupus and Sjogrens syndrome affect nine times more women than men1,2, whereas schizophrenia affects men more frequently and severely3-5. All three illnesses have their strongest common-genetic associations in the Major Histocompatibility Complex (MHC) locus, an association that in lupus and Sjogrens syndrome has long been thought to arise from HLA alleles6-13. Here we show that the complement component 4 (C4) genes in the MHC locus, recently found to increase risk for schizophrenia14, generate 7-fold variation in risk for lupus (95% CI: 5.88-8.61; p < 10-117 in total) and 16-fold variation in risk for Sjogrens syndrome (95% CI: 8.59-30.89; p < 10-23 in total), with C4A protecting more strongly than C4B in both illnesses. The same alleles that increase risk for schizophrenia, greatly reduced risk for lupus and Sjogrens syndrome. In all three illnesses, C4 alleles acted more strongly in men than in women: common combinations of C4A and C4B generated 14-fold variation in risk for lupus and 31-fold variation in risk for Sjogrens syndrome in men (vs. 6-fold and 15-fold among women respectively) and affected schizophrenia risk about twice as strongly in men as in women. At a protein level, both C4 and its effector (C3) were present at greater levels in men than women in cerebrospinal fluid (p < 10-5 for both C4 and C3) and plasma among adults ages 20-5015-17, corresponding to the ages of differential disease vulnerability. Sex differences in complement protein levels may help explain the larger effects of C4 alleles in men, womens greater risk of SLE and Sjogrens, and mens greater vulnerability in schizophrenia. These results nominate the complement system as a source of sexual dimorphism in vulnerability to diverse illnesses.

genetics↗