American journal of human genetics最新文献

How might members of a large, multi-institutional research and resource consortium foster justice, equity, diversity, and inclusion as central to its mission, goals, governance, and culture? These four principles, often referred to as JEDI, can be aspirational-but to be operationalized, they must be supported by concrete actions, investments, and a persistent long-term commitment to the principles themselves, which often requires self-reflection and course correction. We present here the iterative design process implemented across the Clinical Genome Resource (ClinGen) that led to the development of an action plan to operationalize JEDI principles across three major domains, with specific deliverables and commitments dedicated to each. Active involvement of consortium leadership, buy-in from its members at all levels, and support from NIH program staff at pivotal stages were essential to the success of this effort. The ClinGen JEDI action plan that resulted from our process is a living document and roadmap whose target goals and deliverables will continue to evolve. Here, we offer a transparent account of how a large, multi-site biomedical research consortium achieved this, as well as the challenges and opportunities we encountered on this first step in our journey toward enacting JEDI principles in our sphere of influence. We hope that others seeking to engage in this work will gain valuable insights from our process, experience, and lessons learned.

Alzheimer disease (AD) is a complex and progressive neurodegenerative disorder that accounts for the majority of individuals with dementia. Here, we aim to identify causal plasma proteins for AD, shedding light on the etiology of AD. We utilized the latest large-scale plasma proteomic data from the UK Biobank Pharma Proteomics Project (UKB-PPP) and AD genome-wide association study (GWAS) summary data from the International Genomics of Alzheimer's Project (IGAP). Via a robust univariate instrumental variable (IV) regression method, we identified causal proteins through cis-protein quantitative trait loci (pQTLs) and (both cis- and trans-)pQTLs. To further reduce potential false positives due to high linkage disequilibrium (LD) of some pQTLs and high correlations among some proteins, we developed a robust multivariate IV regression method, called two-stage constrained maximum likelihood (MV-2ScML), to distinguish direct and confounding/mediating effects of proteins; some key features of the method include its robustness to invalid IVs and applicability to GWAS summary data. Our work highlights some differences between using cis-pQTLs and trans-pQTLs and critical values of multivariate analysis for fine-mapping causal proteins, providing insights into plasma protein pathways to AD.

Four genes-DAND5, PKD1L1, MMP21, and CIROP-form a genetic module that has specifically evolved in vertebrate species that harbor motile cilia in their left-right organizer (LRO). We find here that CIROZ (previously known as C1orf127) is also specifically expressed in the LRO of mice, frogs, and fish, where it encodes a protein with a signal peptide followed by 3 zona pellucida N domains, consistent with extracellular localization. We report 16 individuals from 10 families with bi-allelic CIROZ inactivation variants, which cause heterotaxy with congenital heart defects. While the knockout of Ciroz in mice also leads to situs anomalies, we unexpectedly find that its targeted inactivation in zebrafish and Xenopus does not lead to observable LR anomalies. Moreover, CIROZ is absent or obsolete in select animals with motile cilia at their LRO, including Carnivora, Atherinomorpha fish, or jawless vertebrates. In summary, this evo-devo study identifies CIROZ as an essential gene for breaking bilateral embryonic symmetry in humans and mice, whereas we witness its contemporary pseudogenization in discrete vertebrate species.

Clinical short-read exome and genome sequencing approaches have positively impacted diagnostic testing for rare diseases. Yet, technical limitations associated with short reads challenge their use for the detection of disease-associated variation in complex regions of the genome. Long-read sequencing (LRS) technologies may overcome these challenges, potentially qualifying as a first-tier test for all rare diseases. To test this hypothesis, we performed LRS (30× high-fidelity [HiFi] genomes) for 100 samples with 145 known clinically relevant germline variants that are challenging to detect using short-read sequencing and necessitate a broad range of complementary test modalities in diagnostic laboratories. We show that relevant variant callers readily re-identified the majority of variants (120/145, 83%), including ∼90% of structural variants, SNVs/insertions or deletions (indels) in homologous sequences, and expansions of short tandem repeats. Another 10% (n = 14) was visually apparent in the data but not automatically detected. Our analyses also identified systematic challenges for the remaining 7% (n = 11) of variants, such as the detection of AG-rich repeat expansions. Titration analysis showed that 90% of all automatically called variants could also be identified using 15-fold coverage. Long-read genomes thus identified 93% of challenging pathogenic variants from our dataset. Even with reduced coverage, the vast majority of variants remained detectable, possibly enhancing cost-effective diagnostic implementation. Most importantly, we show the potential to use a single technology to accurately identify all types of clinically relevant variants.

Neurodevelopmental diseases (NDDs) are notoriously difficult to treat because clinical symptoms stem from developmental processes that begin before birth. Prenatal gene editing could fill the treatment gap for NDDs by targeting and permanently correcting the genetic variants that underlie these pathogenic developmental processes. At the same time, there is a risk of unintended edits to the fetus or the pregnant person that could result in serious adverse consequences that are difficult, if not impossible, to undo. This raises ethical concerns that make the development of prenatal gene editing especially challenging. To date, there are no frameworks for considering the steps necessary for an ethical path forward for prenatal gene editing specifically. The 60-year history of in utero therapy has included the development of frameworks for other therapies that can provide starting points for addressing the unique issues of prenatal gene editing. We identified 12 themes from 17 ethical frameworks, literature, consensus statements, and government reports on prenatal interventions that could set precedents for prenatal gene editing interventions. In considering these alongside current criteria for postnatal gene therapies for NDDs, we discuss a path forward for prenatal gene editing interventions of NDDs.

The Fulani people, one of the most important pastoralist groups in sub-Saharan Africa, are still largely underrepresented in population genomic research. They speak a Niger-Congo language called Fulfulde or Pulaar and live in scattered locations across the Sahel/Savannah belt, from the Atlantic Ocean to Lake Chad. According to historical records, their ancestors spread from Futa Toro in the Middle Senegal Valley to Futa-Jallon in Guinea and then eastward into the Sahel belt over the past 1,500 years. However, the earlier history of this traditionally pastoral population has not been well studied. To uncover the genetic structure and ancestry of this widespread population, we gathered genome-wide genotype data from 460 individuals across 18 local Fulani populations, along with comparative data from both modern and ancient worldwide populations. This represents a comprehensive geographically wide-scaled genome-wide study of the Fulani. We revealed a genetic component closely associated with all local Fulani populations, suggesting a shared ancestral component possibly linked to the beginning of African pastoralism in the Green Sahara. Comparison to ancient DNA results also identified the presence of an ancient Iberomaurusian-associated component across all Fulani groups, providing additional insights into their deep genetic history. Additionally, our genetic data indicate a later Fulani expansion from the western to the eastern Sahel, characterized by a clinal pattern and admixture with several other African populations north of the equator.

Genetic summary data are broadly accessible and highly useful, including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into summary data, such as allele frequencies, masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted-for substructure limits summary data usability, especially for understudied or admixed populations. There is a need for methods to enable the harmonization of summary data where the underlying substructure is matched between datasets. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to enable the harmonization of genetic summary data by estimating and adjusting for substructure. In extensive simulations and application to public data, we show that Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and scans for potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse, publicly available summary data, resulting in improved and more equitable research.

cis-regulatory elements (CREs) control gene transcription dynamics across cell types and in response to the environment. In asthma, multiple immune cell types play an important role in the inflammatory process. Genetic variants in CREs can also affect gene expression response dynamics and contribute to asthma risk. However, the regulatory mechanisms underlying control of transcriptional dynamics across different environmental contexts and cell types at single-cell resolution remain to be elucidated. To resolve this question, we performed single-cell ATAC-seq (scATAC-seq) in peripheral blood mononuclear cells (PBMCs) from 16 children with asthma. PBMCs were activated with phytohemagglutinin (PHA) or lipopolysaccharide (LPS) and treated with dexamethasone (DEX), an anti-inflammatory glucocorticoid. We analyzed changes in chromatin accessibility, measured transcription factor motif activity, and identified treatment- and cell-type-specific transcription factors that drive changes in both gene expression mean and variability. We observed a strong positive linear dependence between motif response and their target gene expression changes but a negative relationship with changes in target gene expression variability. This result suggests that an increase of transcription factor binding tightens the variability of gene expression around the mean. We then annotated genetic variants in chromatin accessibility peaks and response motifs, followed by computational fine-mapping of expression quantitative trait loci (eQTL) from a pediatric asthma cohort. We found that eQTLs were 5-fold enriched in peaks with response motifs and refined the credible set for 410 asthma risk genes, with 191 having the causal variant in response motifs. In conclusion, scATAC-seq enhances the understanding of molecular mechanisms for asthma risk variants mediated by gene expression.

Sex differences in human transcriptomes have been argued to drive sex-differential selection (SDS). Here, we show that previous evidence supporting this hypothesis has been largely unfounded. We develop a method to test for a genome-wide relationship between sex differences in expression and selection on expression-influencing alleles (expression quantitative trait loci [eQTLs]). We apply it across 34 human tissues and find no evidence for a general relationship. We offer possible explanations for the lack of evidence, including that it is due in part to eQTL ascertainment bias toward sites under weak selection. We conclude that the drivers of ongoing SDS in humans remain to be identified.

Loss-of-function mutations in the X chromosome gene PIGA lead to phosphatidylinositol glycan class A congenital disorder of glycosylation (PIGA-CDG), an ultra-rare CDG typically presenting with seizures, hypotonia, and neurodevelopmental delay. We identified two brothers (probands) with PIGA-CDG, presenting with epilepsy and mild developmental delay. Both probands carry PIGA c.395C>G (p.Ser132Cys), an ultra-rare variant predicted to be damaging. Strikingly, the maternal grandfather and a great uncle also carry the same PIGA variant, but neither presents with symptoms associated with PIGA-CDG. We hypothesized that genetic modifiers might contribute to this reduced penetrance. Using whole-genome sequencing and pedigree analysis, we identified possible susceptibility variants found in the probands and not in the carriers and possible protective variants found in the carriers and not in the probands. Candidate genetic modifier variants included heterozygous, damaging variants in three genes involved directly in glycosylphosphatidylinositol (GPI)-anchor biosynthesis and additional variants in other glycosylation pathways or encoding GPI-anchored proteins. Using a Drosophila eye-based model, we tested modifiers identified through genome sequencing. Loss of CNTN2, a predicted protective modifier that encodes a GPI-anchored protein responsible for neuron/glial interactions, rescues loss of PIGA in the eye-based model, as we predict in the family. Further testing found that the loss of CNTN2 also rescues PIGA-CDG-specific phenotypes, including seizures and climbing defects in Drosophila neurological models of PIGA-CDG. Using pedigree information, genome sequencing, and in vivo testing, we identified CNTN2 as a strong candidate modifier that could explain the incomplete penetrance in this family. Identifying and studying rare disease modifier genes in families may lead to therapeutic targets.