Biology subjects

Patterson, N.

Publications and source records attributed to Patterson, N..

At least 19 recordsLinked to original sources

bioRxiv2026

The Pan-European Impact of the Balkan Hunter-Gatherers

During the Last Glacial Maximum (LGM) 26-19 thousand years ago (kya), Europe had three principal refugia not covered by ice: the Iberian, Italian, and Balkan peninsulas1,2. While the Iberian and Italian refugia have been studied with ancient DNA3-7, the legacy of the Balkan refugium has remained a mystery due to a lack of genetic data 30-12 kya. We present genome-wide data from nine newly reported individuals: three Epipaleolithic from Romania, one Epipaleolithic from Bosnia and Herzegovina, three Mesolithic from Greece, one Epipaleolithic from Southern Italy, and one Mesolithic from Sardinia. We find that the Epipaleolithic individuals from Romania and the Mesolithic individual from mainland Greece were from a previously unsampled population that was the primary source for later European hunter-gatherers. Westward expansion of Balkan Epipaleolithic people into the Italian Peninsula and mixture with a minority contribution from pre-LGM Italians, produced a population that then spread further west to become the primary ancestry of west-ern European Mesolithic people. Northeastward expansion, bypassing Italy, contributed the European ancestry source of Scandinavian and Eastern European hunter-gatherers. Southeastward expansion to the Aegean led to Anatolian-European mixtures before the spread of farming.

genetics↗

bioRxiv2026

CMTM6-Silencing Microbial Immunotherapy Reprograms PDAC Tumors and Restores T-cell Function

Despite recent advances in immunotherapy for advanced malignancies, Pancreatic ductal adenocarcinoma (PDAC) remains largely refractory to current immunotherapy due to dense fibrosis, limited antigen presentation, and myeloid-driven immune suppression. Here we report the tumor-targeting, immune remodeling, and safety profiles of the attenuated Salmonella enterica serovar Typhimurium strain CRC2631, and of iSTORM, a next-generation derivative engineered for tumor-localized CMTM6 silencing. CRC2631 preferentially colonizes orthotopic and genetically engineered PDAC tumors, with enrichment in primary lesions and metastases. Tumor-localized CRC2631 induces chemokine and adhesion programs consistent with leukocyte recruitment, increases intratumoral activated T-cell fractions, and triggers transcriptional signatures aligned with innate sensing, interferon signaling, antigen-processing and presentation, and apoptosis programs. iSTORM extends this platform by delivering CMTM6-targeting shRNA to modulate a PD-L1-stabilizing, myeloid-associated immune-evasion programs within tumor-colonized tissue. Compared with CRC2631, iSTORM increases intratumoral CD8+ T cells, shifts T-cell state toward activation with reduced exhaustion-prone features, strengthens antigen-presentation programs, and achieves deeper tumor control. A lyophilized formulation preserves immune remodeling while improving deployability. Mechanistically, glycan arrays and functional studies support mannose-rich glycan-guided tumor engagement. iSTORM toxicity studies, including systemic cytokine, hematologic, blood chemistry, and lethality demonstrate a favorable safety profile. Collectively, these findings establish iSTORM as a safe, programmable, CMTM6-silencing microbial immunotherapy platform that selectively targets and penetrate PDAC tumors to unleash anti-tumor immune activities. What is already known on this topicPDAC is highly resistant to immune checkpoint blockade because dense stroma and myeloid-dominated suppression prevent effective T-cell infiltration; attenuated Salmonella strains can selectively colonize tumors but first-generation agents showed limited efficacy and safety concerns. What this study addsThis study defines CRC2631/iSTORM as a tumor-selective microbial immunotherapy that exploits surface-exposed, mannose-rich N-glycans to colonize PDAC, delivers CMTM6 silencing, and restores CD8+ T-cell activation and tumor control in models resistant to PD-1 blockade immunotherapy. How this study might affect research, practice or policyThese findings provide a mechanistic blueprint for glycan-guided, CMTM6-targeted bacterial "living drugs," support rational combination strategies for deepening therapeutic effect, and establish a lyophilized, biocontained platform that could be developed into scalable microbial immunotherapies for PDAC and other immunologically cold solid tumors.

cancer biology↗

bioRxiv2025

Therapy-induced PSMA2 Sensitizes Prostate Cancer Cells to Residual Androgen and Promotes Neuroendocrine Lineage Transformation

Aberrant activation of the androgen receptor (AR) pathway drives prostate cancer (PCa). Androgen deprivation therapy (ADT) and next-generation AR blockade (e.g., enzalutamide) are initially effective, but virtually all patients develop castration-resistant prostate cancer (CRPC), which frequently transitions to treatment-emergent neuroendocrine PCa (tNEPC) following AR suppression. The molecular logic that links AR blockade to lineage plasticity remains incompletely understood. Here, we identify PSMA2 (Proteasome Subunit Alpha 2) as a treatment-induced effector that mechanistically connects AR blockade to tNEPC evolution. Enzalutamide induces PSMA2 expression in AR-expressing PCa cells. Enforced PSMA2 expression accelerates HSP90 turnover, hypersensitizes AR to residual post-castration androgen, drives AR nuclear activity under androgen-poor conditions, and confers enzalutamide resistance. Conversely, PSMA2 silencing stabilizes HSP90, desensitizes CRPC to androgen, and re-sensitizes resistant cells to enzalutamide-induced cell death. Importantly, PSMA2 also promotes lineage plasticity: treatment-induced PSMA2 enhances transcriptional and phenotypic conversion toward tNEPC. Thus, we uncover a single stress-induced node (PSMA2) that both maintains AR-dependent survival under ADT and fuels the neuroendocrine transition. PSMA2 marks an AR-hypersensitized transitional state and is itself a therapeutically actionable driver of tNEPC evolution, revealing an opportunity for rational interception of the lethal ADT-CRPC-tNEPC trajectory.

cancer biology↗

bioRxiv2025

Long-term hunter-gatherer continuity in the Rhine-Meuse region was disrupted by local formation of expansive Bell Beaker groups

The first phase of the ancient DNA revolution painted a broad-brush picture of European Holocene prehistory, whereby 6500-4000 BCE, farmers descending from western Anatolians mixed with local hunter-gatherers resulting in 70-100% ancestry turnover, then 3000-2500 BCE people associated with the Corded Ware complex spread steppe ancestry into north-central Europe. We document an exception to this pattern in the wider Rhine-Meuse area in communities in the wetlands, riverine areas, and coastal areas of the western and central Netherlands, Belgium and western Germany, where we assembled genome-wide data for 109 people 8500-1700 BCE. Here, a distinctive population with high hunter-gatherer ancestry ([~]50%) persisted up to three thousand years later than in continental European regions, reflecting limited incorporation of females of Early European Farmer ancestry into local communities. In the western Netherlands, the arrival of the Corded Ware complex was also exceptional: lowland individuals from settlements adopting Corded Ware pottery had hardly any steppe ancestry, despite a characteristic early Corded Ware Y-chromosome. The limited influx may reflect the unique ecology of the regions river-dominated landscapes, which were not amenable to wholesale adoption of the early Neolithic type of farming introduced by Linearbandkeramik, making it possible for previously established groups to thrive, and creating a persistent but permeable boundary that allowed transfer of ideas and low-level gene flow. This changed with the formation-through-mixture of Bell Beaker using populations [~]2500 BCE by fusion of local Rhine-Meuse people (9-17%) and Corded Ware associated migrants of both sexes. Their expansion from the Rhine-Meuse region then had a disruptive impact across a much wider part of northwest Europe, including Britain where its arrival was the main source of a 90-100% replacement of local Neolithic peoples.

genomics↗

bioRxiv2024

Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation

We present a method for detecting evidence of natural selection in ancient DNA time-series data that leverages an opportunity not utilized in previous scans: testing for a consistent trend in allele frequency change over time. By applying this to 8433 West Eurasians who lived over the past 14000 years and 6510 contemporary people, we find an order of magnitude more genome-wide significant signals than previous studies: 347 independent loci with >99% probability of selection. Previous work showed that classic hard sweeps driving advantageous mutations to fixation have been rare over the broad span of human evolution, but in the last ten millennia, many hundreds of alleles have been affected by strong directional selection. Discoveries include an increase from [~]0% to [~]20% in 4000 years for the major risk factor for celiac disease at HLA-DQB1; a rise from [~]0% to [~]8% in 6000 years of blood type B; and fluctuating selection at the TYK2 tuberculosis risk allele rising from [~]2% to [~]9% from [~]5500 to [~]3000 years ago before dropping to [~]3%. We identify instances of coordinated selection on alleles affecting the same trait, with the polygenic score today predictive of body fat percentage decreasing by around a standard deviation over ten millennia, consistent with the "Thrifty Gene" hypothesis that a genetic predisposition to store energy during food scarcity became disadvantageous after farming. We also identify selection for combinations of alleles that are today associated with lighter skin color, lower risk for schizophrenia and bipolar disease, slower health decline, and increased measures related to cognitive performance (scores on intelligence tests, household income, and years of schooling). These traits are measured in modern industrialized societies, so what phenotypes were adaptive in the past is unclear. We estimate selection coefficients at 9.9 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits.

evolutionary biology↗

bioRxiv2024

The Genetic Origin of the Indo-Europeans

The Yamnaya archaeological complex appeared around 3300BCE across the steppes north of the Black and Caspian Seas, and by 3000BCE reached its maximal extent from Hungary in the west to Kazakhstan in the east. To localize the ancestral and geographical origins of the Yamnaya among the diverse Eneolithic people that preceded them, we studied ancient DNA data from 428 individuals of which 299 are reported for the first time, demonstrating three previously unknown Eneolithic genetic clines. First, a "Caucasus-Lower Volga" (CLV) Cline suffused with Caucasus hunter-gatherer (CHG) ancestry extended between a Caucasus Neolithic southern end in Neolithic Armenia, and a steppe northern end in Berezhnovka in the Lower Volga. Bidirectional gene flow across the CLV cline created admixed intermediate populations in both the north Caucasus, such as the Maikop people, and on the steppe, such as those at the site of Remontnoye north of the Manych depression. CLV people also helped form two major riverine clines by admixing with distinct groups of European hunter-gatherers. A "Volga Cline" was formed as Lower Volga people mixed with upriver populations that had more Eastern hunter-gatherer (EHG) ancestry, creating genetically hyper-variable populations as at Khvalynsk in the Middle Volga. A "Dnipro Cline" was formed as CLV people bearing both Caucasus Neolithic and Lower Volga ancestry moved west and acquired Ukraine Neolithic hunter-gatherer (UNHG) ancestry to establish the population of the Serednii Stih culture from which the direct ancestors of the Yamnaya themselves were formed around 4000BCE. This population grew rapidly after 3750-3350BCE, precipitating the expansion of people of the Yamnaya culture who totally displaced previous groups on the Volga and further east, while admixing with more sedentary groups in the west. CLV cline people with Lower Volga ancestry contributed four fifths of the ancestry of the Yamnaya, but also, entering Anatolia from the east, contributed at least a tenth of the ancestry of Bronze Age Central Anatolians, where the Hittite language, related to the Indo-European languages spread by the Yamnaya, was spoken. We thus propose that the final unity of the speakers of the "Proto-Indo-Anatolian" ancestral language of both Anatolian and Indo-European languages can be traced to CLV cline people sometime between 4400-4000 BCE. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/589597v1_ufig1.gif" ALT="Figure 1"> View larger version (91K): org.highwire.dtl.DTLVardef@127de98org.highwire.dtl.DTLVardef@87010aorg.highwire.dtl.DTLVardef@1554627org.highwire.dtl.DTLVardef@170dd63_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOSummary Figure:C_FLOATNO The origin of Indo-Anatolian and Indo-European languages. Genetic reconstruction of the ancestry of Pontic-Caspian steppe and West Asian populations points to the North Caucasus-Lower Volga area as the homeland of Indo-Anatolian languages and to the Serednii Stih archaeological culture of the Dnipro-Don area as the homeland of Indo-European languages. The Caucasus-Lower Volga people had diverse distal roots, estimated using the qpAdm software on the left barplot, as Caucasus hunter-gatherer (purple), Central Asian (red), Eastern hunter-gatherer (pink), and West Asian Neolithic (green). Caucasus-Lower Volga expansions, estimated using qpAdm on the right barplot as disseminated Caucasus Neolithic (blue)-Lower Volga Eneolithic (orange) proximal ancestries, mixing with the inhabitants of the North Pontic region (yellow), Volga region (yellow), and West Asia (green). C_FIG

genetics↗

bioRxiv2024

A genomic history of the North Pontic Region from the Neolithic to the Bronze Age

The north Black Sea (Pontic) Region was the nexus of the farmers of Old Europe and the foragers and pastoralists of the Eurasian steppe1,2, and the source of waves of migrants that expanded deep into Europe3-5. We report genome-wide data from 78 prehistoric North Pontic individuals to understand the genetic makeup of the people involved in these migrations and discover the reasons for their success. First, we show that native North Pontic foragers had ancestry not only from Balkan and Eastern hunter-gatherers6 but also from European farmers and, occasionally, Caucasus hunter-gatherers. More dramatic inflows ensued during the Eneolithic, when migrants from the Caucasus-Lower Volga area7 moved westward, bypassing the local foragers to mix with Trypillian farmers advancing eastward. People of the Usatove archaeological group in the Northwest Pontic were formed ca. 4500 BCE with an equal measure of ancestry from the two expanding groups. A different Caucasus-Lower Volga group, moving westward in a distinct but temporally overlapping wave, avoided the farmers altogether, and blended with the foragers instead to form the people of the Serednii Stih archaeological complex7. A third wave of expansion occurred when Yamna descendants of the Serednii Stih forming ca. 4000 BCE expanded during the Early Bronze Age (3300 BCE). The temporal gap between Serednii Stih and the Yamna expansion is bridged by a genetically Yamna individual from Mykhailivka in Ukraine (3635-3383 BCE), a site of uninterrupted archaeological continuity across the Eneolithic-Bronze Age transition, and the likely epicenter of Yamna formation. Each of these three waves propagated distinctive ancestries while also incorporating outsiders during its advance, a flexible strategy forged in the North Pontic region that may explain its peoples outsized success in spreading their genes and culture across Eurasia3-5,8-10.

genetics↗

bioRxiv2024

50,000 years of Evolutionary History of India: Insights from ~2,700 Whole Genome Sequences

India has been underrepresented in whole genome sequencing studies. We generated 2,762 high coverage genomes from India--including individuals from most geographic regions, speakers of all major languages, and tribal and caste groups--providing a comprehensive survey of genetic variation in India. With these data, we reconstruct the evolutionary history of India through space and time at fine scales. We show that most Indians derive ancestry from three ancestral groups related to ancient Iranian farmers, Eurasian Steppe pastoralists and South Asian hunter-gatherers. We uncover a common source of Iranian-related ancestry from early Neolithic cultures of Central Asia into the ancestors of Ancestral South Indians (ASI), Ancestral North Indians (ANI), Austro-asiatic-related and East Asian-related groups in India. Following these admixtures, India experienced a major demographic shift towards endogamy, resulting in extensive homozygosity and identity-by-descent sharing among individuals. At deep time scales, Indians derive around 1-2% of their ancestry through gene flow from archaic hominins, Neanderthals and Denisovans. By assembling the surviving fragments of archaic ancestry in modern Indians, we recover [~]1.5 Gb (or 50%) of the introgressing Neanderthal and [~]0.6 Gb (or 20%) of the introgressing Denisovan genomes, more than any other previous archaic ancestry study. Moreover, Indians have the largest variation in Neanderthal ancestry, as well as the highest amount of population-specific Neanderthal segments among worldwide groups. Finally, we demonstrate that most of the genetic variation in Indians stems from a single major migration out of Africa that occurred around 50,000 years ago, with minimal contribution from earlier migration waves. Together, these analyses provide a detailed view of the population history of India and underscore the value of expanding genomic surveys to diverse groups outside Europe.

evolutionary biology↗

bioRxiv2024

Accurate inference of population history in the presence of background selection

1All published methods for learning about demographic history make the simplifying assumption that the genome evolves neutrally, and do not seek to account for the effects of natural selection on patterns of variation. This is a major concern, as ample work has demonstrated the pervasive effects of natural selection and in particular background selection (BGS) on patterns of genetic variation in diverse species. Simulations and theoretical work have shown that methods to infer changes in effective population size over time (Ne(t)) become increasingly inaccurate as the strength of linked selection increases. Here, we introduce an extension to the Pairwise Sequentially Markovian Coalescent (PSMC) algorithm, PSMC+, which explicitly co-models demographic history and natural selection. We benchmark our method using forward-in-time simulations with BGS and find that our approach improves the accuracy of effective population size inference. Leveraging a high resolution map of BGS in humans, we infer considerable changes in the magnitude of inferred effective population size relative to previous reports. Finally, we separately infer Ne(t) on the X chromosome and on the autosomes in diverse great apes without making a correction for selection, and find that the inferred ratio fluctuates substantially through time in a way that differs across species, showing that uncorrected selection may be an important driver of signals of genetic difference on the X chromosome and autosomes.

genetics↗

bioRxiv2023

A Light sheet fluorescence microscopy and machine learning-based approach to investigate drug and biomarker distribution in whole organs and tumors.

Tissue clearing and Light sheet fluorescence microscopy (LSFM) provide spatial information at a subcellular resolution in intact organs and tumors which is a significant advance over tools that limit imaging to a few representative tissue sections. The spatial distribution of drugs, targets, and biomarkers can help inform relationships between exposure at the site of action, efficacy, and safety during drug discovery. We demonstrate the use of LSFM to investigate distribution of an oncolytic virus (OV) and vasculature in xenograft tumors, as well as brain A{beta} pathology in an Alzheimers disease (AD) mouse model. Machine learning-based image analysis tools developed to segment vasculature in tumors showed that random forest and deep learning methods provided superior segmentation accuracy vs intensity-based thresholding. Sub-cellular resolution enabled detection of punctate and diffuse intracellular OV distribution profiles. LSFM investigation in the brain in a TgCRND8 AD mouse model at 6.5 months of age enabled evaluation of A{beta} plaque density in different brain regions. The utility of LSFM data to support quantitative systems pharmacology (QSP) and physiology-based pharmacokinetics (PBPK) modeling to inform drug development are also discussed. In summary, we showcase how LSFM can expand our understanding of macromolecular drug and biomarker distribution to advance drug discovery and development.

cancer biology↗

bioRxiv2023

ancIBD - Screening for identity by descent segments in human ancient DNA

Long DNA sequences shared between two individuals, known as Identical by descent (IBD) segments, are a powerful signal for identifying close and distant biological relatives because they only arise when the pair shares a recent common ancestor. Existing methods to call IBD segments between present-day genomes cannot be straightforwardly applied to ancient DNA data (aDNA) due to typically low coverage and high genotyping error rates. We present ancIBD, a method to identify IBD segments for human aDNA data implemented as a Python package. Our approach is based on a Hidden Markov Model, using as input genotype probabilities imputed based on a modern reference panel of genomic variation. Through simulation and downsampling experiments, we demonstrate that ancIBD robustly identifies IBD segments longer than 8 centimorgan for aDNA data with at least either 0.25x average whole-genome sequencing (WGS) coverage depth or at least 1x average depth for in-solution enrichment experiments targeting a widely used aDNA SNP set ( 1240k). This application range allows us to screen a substantial fraction of the aDNA record for IBD segments and we showcase two downstream applications. First, leveraging the fact that biological relatives up to the sixth degree are expected to share multiple long IBD segments, we identify relatives between 10,156 ancient Eurasian individuals and document evidence of long-distance migration, for example by identifying a pair of two approximately fifth-degree relatives who were buried 1410km apart in Central Asia 5000 years ago. Second, by applying ancIBD, we reveal new details regarding the spread of ancestry related to Steppe pastoralists into Europe starting 5000 years ago. We find that the first individuals in Central and Northern Europe carrying high amounts of Steppe-ancestry, associated with the Corded Ware culture, share high rates of long IBD (12-25 cM) with Yamnaya herders of the Pontic-Caspian steppe, signaling a strong bottleneck and a recent biological connection on the order of only few hundred years, providing evidence that the Yamnaya themselves are a main source of Steppe ancestry in Corded Ware people. We also detect elevated sharing of long IBD segments between Corded Ware individuals and people associated with the Globular Amphora culture (GAC) from Poland and Ukraine, who were Copper Age farmers not yet carrying Steppe-like ancestry. These IBD links appear for all Corded Ware groups in our analysis, indicating that individuals related to GAC contexts must have had a major demographic impact early on in the genetic admixtures giving rise to various Corded Ware groups across Europe. These results show that detecting IBD segments in aDNA can generate new insights both on a small scale, relevant to understanding the life stories of people, and on the macroscale, relevant to large-scale cultural-historical events.

genetics↗

bioRxiv2022

The Entwined African and Asian Genetic Roots of the Medieval Peoples of the Swahili Coast

The peoples of the Swahili coast of eastern Africa established a literate urban culture by the second millennium CE. They traded across eastern Africa and the Indian Ocean and were among the first sub-Saharan practitioners of Islam. An open question has been the extent to which these early interactions between Africans and non-Africans were accompanied by genetic admixture. We report genome-wide ancient DNA from 80 individuals in five medieval and early modern (1300-1800 CE) coastal towns, as well as people from an inland town postdating 1650 CE. Over half of the ancestry of most coastal individuals came from African ancestors; these African ancestors were primarily female. A slightly smaller proportion of ancestry was from Asia. This Asian component was approximately eighty to ninety percent from Near Eastern males and ten to twenty percent from Indian females. Peoples of African and Asian origins began to mix by around 1000 CE, a time when archaeological evidence documents changes on the coast that are often interpreted as marking the large-scale adoption of Islam. Before roughly 1500 CE, the Near Eastern ancestry detected in the individuals was mainly Persian-related, consistent with the narrative of the Kilwa Chronicle, the oldest history told by the Swahili themselves. After this time, the sources of Near Eastern ancestry became increasingly Arabian, consistent with the archaeological and historical evidence of growing interactions between the Swahili coast and parts of southern Arabia. Subsequent interactions of Swahili coast peoples with other Asian and African groups further changed the ancestry of present-day peoples relative to the ancient individuals we sequenced, highlighting how Swahili genetic legacies can be more clearly understood with ancient DNA.

genetics↗

bioRxiv2022

Reconstructing the spatiotemporal patterns of admixture during the European Holocene using a novel genomic dating method

Recent studies have shown that gene flow or admixture has been pervasive throughout human history. While several methods exist for dating admixture in contemporary populations, they are not suitable for sparse, low coverage data available from ancient specimens. To overcome this limitation, we developed DATES that leverages ancestry covariance patterns across the genome of a single individual to infer the timing of admixture. By performing simulations, we show that DATES provides reliable results under a range of demographic scenarios and outperforms available methods for ancient DNA applications. We apply DATES to ~1,100 ancient genomes to reconstruct gene flow events during the European Holocene. Present-day Europeans derive ancestry from three distinct groups, local Mesolithic hunter-gatherers, Anatolian farmers, and Yamnaya Steppe pastoralists. These ancestral groups were themselves admixed. By studying the formation of Anatolian farmers, we infer that the gene flow related to Iranian Neolithic farmers occurred no later than 9,600 BCE, predating agriculture in Anatolia. We estimate the early Steppe pastoralist groups genetically formed more than a millennium before the start of steppe pastoralism, providing new insights about the history of proto-Yamnaya cultures and the origin of Indo-European languages. Using ancient genomes across sixteen regions in Europe, we provide a detailed chronology of the Neolithization across Europe that occurred from ~6,400-4,300 BCE. This movement was followed by a rapid spread of steppe ancestry from ~3,200-2,500 BCE. Our analyses highlight the power of genomic dating methods to elucidate the legacy of human migrations, providing insights complementary to archaeological and linguistic evidence. SignificanceThe European continent was subject to two major migrations during the Holocene: the movement of Near Eastern farmers during the Neolithic and the migration of Steppe pastoralists during the Bronze Age. To understand the timing and dynamics of these movements, we developed DATES that leverages ancestry covariance patterns across the genome of a single individual to infer the timing of admixture. Using ~1,100 ancient genomes spanning ~8,000-350 BCE, we reconstruct the chronology of the formation of the ancestral populations and the fine-scale details of the spread of Neolithic farming and Steppe pastoralist-related ancestry to Europe. Our analysis demonstrates the power of genomic dating methods to provide an independent and complementary timeline of population origins and movements using genetic data.

evolutionary biology↗

bioRxiv2021

Let-7b-5p, miR-184, and miR-22-3p: Multianalyte Plasma Biomarkers for NSCLC Diagnosis and for Predicting Resistance to Osimertinib

Low-dose computed tomography (LDCT) Non-Small Cell Lung (NSCLC) screening is associated with high false-positive rates, leading to unnecessary expensive and invasive follow ups. There is a need for minimally invasive approaches to improve the accuracy of NSCLC diagnosis. Plasma extracellular vesicle (EV) and circulating microRNA (miRNA) have been proposed as cancer screening biomarkers. However, the identification of highly sensitive and broadly predictive core miRNA signatures remains a challenge. Also, how these systemic and diverse miRNAs impact cancer drug response is not well understood. Using an integrative approach, we examined plasma EV and circulating miRNA isolated from NSCLC patients versus screening controls with a similar risk profile. We found that combining EV (Hsa-miR-184, Let-7b-5p) and circulating (Hsa-miR-22-3p) miRNAs abundance robustly discriminates between NSCLC patients and high-risk cancer-free controls. Diagnosed NSCLC patients harboring sensitizing mutations in epidermal growth factor receptor EGFR (T790M, L578R) are treated with Osimertinib, a potent tyrosine kinase inhibitor (TKI). Nearly all patients develop TKI resistance via complex mechanisms and progress. We found that Hsa-miR-22-3p, Hsa-miR-184, and Let-7b-5p functionally converge on WNT/{beta}catenin and mTOR/AKT signaling axes, known cancer therapy resistance signals. Targeting Hsa-miR-22-3p and Hsa-miR-184 desensitized EGFR-mutated (T790M, L578R) NSCLC cells to Osimertinib. These findings suggest that the expression levels of circulating hsa-miR-22-3p combined with EV hsa-miR-184 and Let-7b-5p levels potentially define a core biomarker signature for improving the accuracy of NSCLC diagnosis. Importantly, these biomarkers have the potential to enable prospective identification of patients who are at risk of responding poorly to Osimertinib alone but likely to benefit from Osimertinib/AKT blockade combination treatments.

cancer biology↗

bioRxiv2021

A unified genealogy of modern and ancient genomes

The sequencing of modern and ancient genomes from around the world has revolutionised our understanding of human history and evolution1,2. However, the general problem of how best to characterise the full complexity of ancestral relationships from the totality of human genomic variation remains unsolved. Patterns of variation in each data set are typically analysed independently, and often using parametric models or data reduction techniques that cannot capture the full complexity of human ancestry3,4. Moreover, variation in sequencing technology5,6, data quality7 and in silico processing8,9, coupled with complexities of data scale10, limit the ability to integrate data sources. Here, we introduce a non-parametric approach to inferring human genealogical history that overcomes many of these challenges and enables us to build the largest genealogy of both modern and ancient humans yet constructed. The genealogy provides a lossless and compact representation of multiple datasets, addresses the challenges of missing and erroneous data, and benefits from using ancient samples to constrain and date relationships. Using simulations and empirical analyses, we demonstrate the power of the method to recover relationships between individuals and populations, as well as to identify descendants of ancient samples. Finally, we show how applying a simple non-parametric estimator of ancestor geographical location to the inferred genealogy recapitulates key events in human history. Our results demonstrate that whole-genome genealogies are a powerful means of synthesising genetic data and provide rich insights into human evolution.

genomics↗

bioRxiv2021

Social stratification without genetic differentiation at the site of Kulubnarti in Christian Period Nubia

Nubia has been a corridor for the movement of goods, culture, and people between sub-Saharan Africa, Egypt, and West Eurasia since prehistory, but little is known about the genetic landscape of the region prior to the influence of the Islamic migrations that began in the late 1st millennium CE. We report genome-wide data for 66 individuals from the site of Kulubnarti ([~]650-1000 CE), increasing the number of ancient individuals with genome-level data from the Nile Valley from three to 69. Our results shed light on the genetic ancestry of a Christian Period group and help to address a long-standing question about the relationships among people buried in two neighboring cemeteries who show skeletal evidence of differences in morbidity and mortality that are broadly suggestive of differences in social status. We find that the Kulubnarti Nubians were admixed with [~]43% Nilotic-related ancestry on average (individual proportions varied between [~]36-54%) and the remaining ancestry reflecting a West Eurasian-related gene pool likely introduced into Nubia through Egypt, but ultimately deriving from an ancestry pool like that found in the Bronze and Iron Age Levant. The admixed ancestry at Kulubnarti reflects interactions between genetically-distinct people in northeast Africa spanning almost a millennium, with West Eurasian ancestry disproportionately associated with females, highlighting the impact of female mobility in this region. We find no significant differences in ancestry among individuals from the two plausibly socially-stratified cemeteries at Kulubnarti, supporting hypotheses that the groups may have been socially divided but were not genetically distinct. We identify seven pairs of inter-cemetery relatives as close as second-degree, suggesting that any social divisions at Kulubnarti did not prevent mixing between groups. Present-day Nubians are not directly descended from the Christian Period people from Kulubnarti without additional admixture, attesting to the dynamic history of interaction that continues to shape the cultural and genetic landscape of Nubia.

genomics↗

bioRxiv2020

Negative short-range genomic autocorrelation of causal effects on human complex traits

Most models of complex trait genetic architecture assume that signed causal effect sizes of each SNP (defined with respect to the minor allele) are uncorrelated with those of nearby SNPs, but it is currently unknown whether this is the case. We develop a new method, autocorrelation LD regression (ACLR), for estimating the genome-wide autocorrelation of causal minor allele effect sizes as a function of genomic distance. Our method estimates these autocorrelations by regressing the products of summary statistics on distance-dependent LD scores. We determined that ACLR robustly assesses the presence or absence of nonzero autocorrelation, producing unbiased estimates with well-calibrated standard errors in null simulations regardless of genetic architecture; if true autocorrelation is nonzero, ACLR correctly detects its sign, although estimates of the autocorrelation magnitude are susceptible to bias in cases of certain genetic architectures. We applied ACLR to 31 diseases and complex traits from the UK Biobank (average N=331K), meta-analyzing results across traits. We determined that autocorrelations were significantly negative at distances of 1-50bp (P = 8 x 10-6, point estimate -0.35 {+/-}0.08) and 50-100bp (P = 2 x 10-3, point estimate -0.33 {+/-} 0.11). We show that the autocorrelation is primarily driven by pairs of SNPs in positive LD, which is consistent with the expectation that linked SNPs with opposite effects are less impacted by natural selection. Our findings suggest that this mechanism broadly affects complex trait genetic architectures, and we discuss implications for association mapping, heritability estimation, and genetic risk prediction.

genetics↗

bioRxiv2020

Assessing the Performance of qpAdm: A Statistical Tool for Studying Population Admixture

qpAdm is a statistical tool for studying the ancestry of populations with histories that involve admixture between two or more source populations. Using qpAdm, it is possible to identify plausible models of admixture that fit the population history of a group of interest and to calculate the relative proportion of ancestry that can be ascribed to each source population in the model. Although qpAdm is widely used in studies of population history of human (and non-human) groups, relatively little has been done to assess its performance. We performed a simulation study to assess the behavior of qpAdm under various scenarios in order to identify areas of potential weakness and establish recommended best practices for use. We find that qpAdm is a robust tool that yields accurate results in many cases, including when data coverage is low, there are high rates of missing data or ancient DNA damage, or when diploid calls cannot be made. However, we caution against co-analyzing ancient and present-day data, the inclusion of an extremely large number of reference populations in a single model, and analyzing population histories involving extended periods of gene flow. We provide a user guide suggesting best practices for the use of qpAdm.

genomics↗