Biology subjects

Arner, A. M.

Publications and source records attributed to Arner, A. M..

3 recordsLinked to original sources

bioRxiv2024

Public RNA-seq data are not representative of global human diversity

The field of human genetics has reached a consensus that it is important to work with diverse and globally representative participant groups. This diverse sampling is required to build a robust understanding of the genomic basis of complex traits and diseases as well as human evolution, and to ensure that all people benefit from downstream scientific discoveries. While previous work has characterized compositional biases and disparities for public genome-wide association (GWAS), microbiome, and epigenomic studies, we currently lack a comprehensive understanding of the degree of bias for transcriptomic studies. To address this gap, we analyzed the metadata for RNA-seq studies from two public databases--the Sequence Read Archive (SRA), representing 795,071 samples from 21,209 studies, and the Database of Genotypes and Phenotypes (dbGaP), representing 167,389 samples from 649 studies. We also randomly selected 620 studies from SRA for detailed, manual evaluation. We found that 3% of samples in SRA and 21% of individuals described in the literature had population descriptors (race, ethnicity, or ancestry); 28% of samples in dbGaP had paired genotype data that was used to empirically infer ancestry. In SRA, dbGaP, and the literature, race, ethnicity, and ancestry terms were frequently conflated and difficult to disambiguate. After standardizing population descriptors, we observed many clear biases: for example, among samples in SRA that were coded using US Census terms, 69.0% came from white donors, corresponding to an 1.2x overrepresentation of this group relative to the US population. Among samples in SRA coded using continental ancestry labels, 55.6% came from European ancestry donors--an 4.1x overrepresentation of this group relative to the global population. These biases were generally similar across datasets (SRA, dbGaP, literature review), and were comparable to previous reports for other omics data types. However, we note that, relative to other omics data subsets like GWAS, there is considerably less information, of arguably worse quality, about who is participating in RNA-seq studies. Together, these results demonstrate a critical need to improve our thoughtfulness, consistency, and effort around reporting population descriptors in RNA-seq studies, and to more generally strive for greater diversity in this important data type.

genomics↗

bioRxiv2024

Sex differences in immune function and disease risk are not easily explained by an evolutionary mismatch

The "Pregnancy Compensation Hypothesis" (PCH) posits that sex differences in the mammalian immune system reflect the effects of selection on female immunity during pregnancy, during which increased immunomodulation is required to reduce immune responses to the fetus, while maintaining the ability to respond to pathogens. In humans, fewer pathogens and lower parity in urban, industrialized environments has been suggested to leave female immune systems under-stimulated, creating an "evolutionary mismatch" which exacerbates sex differences in immunity and increases female autoimmune disease risk. Yet, robust tests of this mismatch hypothesis have not been conducted. Here, we first confirmed a sex-bias in autoimmune disease prevalence in a large dataset of individuals from the United Kingdom (UK Biobank). Second, we asked whether sex differences in immune function are affected by shifts toward urban, lower-parity lifestyles in a single population--the Turkana people of northwest Kenya. We found that lifestyle alters sex differences in immune cell type proportions, but not in gene expression levels. Contrary to expectations from the PCH, parity did not predict immune physiology. We then tested for generalizable trends across natural fertility mammalian populations versus urban humans (data from Turkana, NHANES, GTEx, Batwa and Bakiga, yellow baboons, and macaques). We did not find consistent relationships between lifestyle and sex-biases in immune biomarkers or between parity and the same immune outcomes. Indeed, we found that parity predicts autoimmune disease risk in the opposite direction than expected from the PCH, with higher parity associated with higher autoimmune disease risk while adjusting for relevant socioeconomic variables in the UK Biobank. Taken together, our work suggests that while sex clearly influences immune physiology and disease risk in urban settings, these effects are not easily explained by an evolutionary mismatch. Future work addressing how sex interacts with lifestyle change to generate disease is needed.

evolutionary biology↗

bioRxiv2020

Evolutionary genomic patterns of recent natural selection on loci associated with sexually differentiated human body size and shape phenotypes

Levels of sex differences for human body size and shape phenotypes are hypothesized to have adaptively reduced following the agricultural transition as part of an evolutionary response to relatively more equal divisions of labor and new technology adoption. In this study, we tested this hypothesis by studying genetic variants associated with five sexually differentiated human phenotypes: height, body mass, hip circumference, body fat percentage, and waist circumference. We first analyzed genome-wide association (GWAS) results for UK Biobank individuals ([~]197,000 females and [~]167,000 males) to identify a total of 119,023 single nucleotide polymorphisms (SNPs) significantly associated with at least one of the studied phenotypes in females, males, or both sexes (P<5x10-8). From these loci we then identified 3,016 SNPs (2.5%) with significant differences in the strength of association between the female- and male-specific GWAS results at a low false-discovery rate (FDR<0.001). Genes with known roles in sexual differentiation are significantly enriched for co-localization with one or more of these SNPs versus SNPs associated with the phenotypes generally but not with sex differences (2.93-fold enrichment; permutation test; P=0.0041). We also confirmed that the identified variants are disproportionately associated with greater phenotype effect sizes in the sex with the stronger association value. We then used the singleton density score statistic, which quantifies recent (within the last [~]3,000 years; post-agriculture adoption in Britain) changes in the frequencies of alleles underlying polygenic traits, to identify a signature of recent positive selection on alleles associated with greater body fat percentage in females (permutation test; P=0.0038; FDR=0.0380), directionally opposite to that predicted by the sex differentiation reduction hypothesis. Otherwise, we found no evidence of positive selection for sex difference-associated alleles for any other trait. Overall, our results challenge the longstanding hypothesis that sex differences adaptively decreased following subsistence transitions from hunting and gathering to agriculture. Author SummaryThere is uncertainty regarding the evolutionary history of human sex differences for quantitative body size and shape phenotypes. In this study we identified thousands of genetic loci that differentially impact body size and shape trait variation between females and males using a large sample of UK Biobank individuals. After confirming the biological plausibility of these loci, we used a population genomics approach to study the recent (over the past 3,000 years) evolutionary histories of these loci in this population. We observed significant increases in the frequencies of alleles associated with greater body fat percentage in females. This result is contradictory to longstanding hypotheses that sex differences have adaptively decreased following subsistence transitions from hunting and gathering to agriculture.

evolutionary biology↗