Discordance between a deep learning model and clinical-grade variant pathogenicity classification in a rare disease cohort.

Genetic testing has become an essential component in the diagnosis and management of a wide range of clinical conditions, from cancer to developmental disorders, especially in rare Mendelian diseases. Efforts to identify rare phenotype-associated variants have predominantly focused on protein-truncating variants, while the interpretation of missense variants presents a considerable challenge. Deep learning algorithms excel in various applications across biomedical tasks1,2, yet accurately distinguishing between pathogenic and benign genetic variants remains an elusive goal3-5. Specifically, even the most sophisticated models encounter difficulties in accurately assessing the pathogenicity of missense variants of uncertain significance (VUS). Our investigation of AlphaMissense (AM)5, the latest iteration of deep learning methods for predicting the potential functional impact of missense variants and assessing gene essentiality, reveals important limitations in its ability to identify pathogenic missense variants within a rare disease cohort. Indeed, AM struggles to accurately assess the pathogenicity of variants in intrinsically disordered regions (IDRs), leading to unreliable gene-level essentiality scores for certain genes containing IDRs. This limitation highlights the challenges in applying AM faces in the context of clinical genetics6.

Roadmap on nanoscale magnetic resonance imaging.

The field of nanoscale magnetic resonance imaging (NanoMRI) was started 30 years ago. It was motivated by the desire to image single molecules and molecular assemblies, such as proteins and virus particles, with near-atomic spatial resolution and on a length scale of 100 nm. Over the years, the NanoMRI field has also expanded to include the goal of useful high-resolution nuclear magnetic resonance (NMR) spectroscopy of molecules under ambient conditions, including samples up to the micron-scale. The realization of these goals requires the development of spin detection techniques that are many orders of magnitude more sensitive than conventional NMR and MRI, capable of detecting and controlling nanoscale ensembles of spins. Over the years, a number of different technical approaches to NanoMRI have emerged, each possessing a distinct set of capabilities for basic and applied areas of science. The goal of this roadmap article is to report the current state of the art in NanoMRI technologies, outline the areas where they are poised to have impact, identify the challenges that lie ahead, and propose methods to meet these challenges. This roadmap also shows how developments in NanoMRI techniques can lead to breakthroughs in emerging quantum science and technology applications.

GSDMB/ORMDL3 Rare/Common Variants Are Associated with Inhaled Corticosteroid Response among Children with Asthma.

Inhaled corticosteroids (ICS) are efficacious in the treatment of asthma, which affects more than 300 million people in the world. While genome-wide association studies have identified genes involved in differential treatment responses to ICS in asthma, few studies have evaluated the effects of combined rare and common variants on ICS response among children with asthma. Among children with asthma treated with ICS with whole exome sequencing (WES) data in the PrecisionLink Biobank (91 White and 20 Black children), we examined the effect and contribution of rare and common variants with hospitalizations or emergency department visits. For 12 regions previously associated with asthma and ICS response (DPP10, FBXL7, NDFIP1, TBXT, GLCCI1, HDAC9, TBXAS1, STAT6, GSDMB/ORMDL3, CRHR1, GNGT2, FCER2), we used the combined sum test for the sequence kernel association test (SKAT) adjusting for age, sex, and BMI and stratified by race. Validation was conducted in the Biorepository and Integrative Genomics (BIG) Initiative (83 White and 134 Black children). Using a Bonferroni threshold for the 12 regions tested (i.e., 0.05/12 = 0.004), GSDMB/ORMDL3 was significantly associated with ICS response for the combined effect of rare and common variants (p-value = 0.003) among White children in the PrecisionLink Biobank and replicated in the BIG Initiative (p-value = 0.02). Using WES data, the combined effect of rare and common variants for GSDMB/ORMDL3 was associated with ICS response among asthmatic children in the PrecisionLink Biobank and replicated in the BIG Initiative. This proof-of-concept study demonstrates the power of biobanks of pediatric real-life populations in asthma genomic investigations.

Centrosome clustering control in osteoclasts through CCR5-mediated signaling.

Osteoclasts uniquely resorb calcified bone matrices. To exert their function, mature osteoclasts maintain the cellular polarity and directional vesicle trafficking to and from the resorbing bone surface. However, the regulatory mechanisms and pathophysiological relevance of these processes remain largely unexplored. Bone histomorphometric analyses in Ccr5-deficient mice showed abnormalities in the morphology and functional phenotype of their osteoclasts, compared to wild type mice. We observed disorganized clustering of nuclei, as well as centrosomes that organize the microtubule network, which was concomitant with impaired cathepsin K secretion in cultured Ccr5-deficient osteoclasts. Intriguingly, forced expression of constitutively active Rho or Rac restored these cytoskeletal phenotypes with recovery of cathepsin K secretion. Furthermore, a gene-disease enrichment analysis identified that PLEKHM1, a responsible gene for osteopetrosis, which regulates lysosomal trafficking in osteoclasts, was regulated by CCR5. These experimental results highlighted that CCR5-mediated signaling served as an intracellular organizer for centrosome clustering in osteoclasts, which was involved in the pathophysiology of bone metabolism.

Association between Neuroligin-1 polymorphism and plasma glutamine levels in individuals with autism spectrum disorder.

BACKGROUND: Unravelling the relationships between candidate genes and autism spectrum disorder (ASD) phenotypes remains an outstanding challenge. Endophenotypes, defined as inheritable, measurable quantitative traits, might provide intermediary links between genetic risk factors and multifaceted ASD phenotypes. In this study, we sought to determine whether plasma metabolite levels could serve as endophenotypes in individuals with ASD and their family members. METHODS: We employed an untargeted, high-resolution metabolomics platform to analyse 14,342 features across 1099 plasma samples. These samples were collected from probands and their family members participating in the Autism Genetic Resource Exchange (AGRE) (N = 658), compared with neurotypical individuals enrolled in the PrecisionLink Health Discovery (PLHD) program at Boston Children's Hospital (N = 441). We conducted a metabolite quantitative trait loci (mQTL) analysis using whole-genome genotyping data from each cohort in AGRE and PLHD, aiming to prioritize significant mQTL and metabolite pairs that were exclusively observed in AGRE. FINDINGS: Within the AGRE group, we identified 54 significant associations between genotypes and metabolite levels (P < 5.27 × 10-11), 44 of which were not observed in the PLHD group. Plasma glutamine levels were found to be associated with variants in the NLGN1 gene, a gene that encodes post-synaptic cell-adhesion molecules in excitatory neurons. This association was not detected in the PLHD group. Notably, a significant negative correlation between plasma glutamine and glutamate levels was observed in the AGRE group, but not in the PLHD group. Furthermore, plasma glutamine levels showed a negative correlation with the severity of restrictive and repetitive behaviours (RRB) in ASD, although no direct association was observed between RRB severity and the NLGN1 genotype. INTERPRETATION: Our findings suggest that plasma glutamine levels could potentially serve as an endophenotype, thus establishing a link between the genetic risk associated with NLGN1 and the severity of RRB in ASD. This identified association could facilitate the development of novel therapeutic targets, assist in selecting specific cohorts for clinical trials, and provide insights into target symptoms for future ASD treatment strategies. FUNDING: This work was supported by the National Institute of Health (grant numbers: R01MH107205, U01TR002623, R24OD024622, OT2OD032720, and R01NS129188) and the PrecisionLink Biobank for Health Discovery at Boston Children's Hospital.

ADGR: Admixture-Informed Differential Gene Regulation.

The regulatory elements in proximal and distal regions of genes are involved in the regulation of gene expression. Risk alleles in intronic and intergenic regions may alter gene expression by modifying the binding affinity and stability of diverse DNA-binding proteins implicated in gene expression regulation. By focusing on the local ancestral structure of coding and regulatory regions using the paired whole-genome sequence and tissue-wide transcriptome datasets from the Genotype-Tissue Expression project, we investigated the impact of genetic variants, in aggregate, on tissue-specific gene expression regulation. Local ancestral origins of the coding region, immediate and distant upstream regions, and distal regulatory region were determined using RFMix with the reference panel from the 1000 Genomes Project. For each tissue, inter-individual variation of gene expression levels explained by concordant or discordant local ancestry between coding and regulatory regions was estimated. Compared to European, African descent showed more frequent change in local ancestral structure, with shorter haplotype blocks. The expression level of the Adenosine Deaminase Like (ADAL) gene was significantly associated with admixed ancestral structure in the regulatory region across multiple tissue types. Further validations are required to understand the impact of the local ancestral structure of regulatory regions on gene expression regulation in humans and other species.

Investigating the Influence of PbS Quantum Dot-Decorated TiO2 Photoanode Thickness on Photoelectrochemical Hydrogen Production Performance.

To maximize the photoelectrochemical (PEC) hydrogen production performance of quantum dot (QD)-decorated photoelectrodes, it is crucial to prioritize the optimization of electrode's structure, including thickness and porosity. In this study, we prepare PbS QD-decorated mesoporous TiO2 photoanodes for PEC hydrogen production, and systematically investigate the influence of the photoanode thickness on optical properties and PEC performances. As the thickness of photoanodes increases from 6.4 µm to 16.3 µm, the light absorption capability is enhanced across the entire visible and near-infrared (IR) spectrum due to the improved loading of PbS QDs. However, the photocurrent density is optimized for the 11.9 µm thick photoanode (15.19 mA/cm2), compared to the 6.4 µm thick (10.80 mA/cm2) and 16.3 µm thick photoanodes (11.93 mA/cm2). This optimization is attributed to the trade-off between the light absorption capability and the efficient mass transfer of the electrolyte as the photoanode thickness increases, which is confirmed by the lowest charge transfer resistance (Rct) evaluated from the electrochemical impedance data.

Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort.

BACKGROUND: The human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels, while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype-metabotype associations. However, these associations have not been characterized in children. RESULTS: We conducted the largest genome by metabolome-wide association study to date of children (N = 441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h2 (> 0.8) for 15.9% of features and low h2 (< 0.2) for most of features (62.0%). The features with high h2 were enriched for amino acid and nucleic acid metabolism, while carbohydrate and lipid concentrations showed low h2. For each feature, a metabolite quantitative trait loci (mQTL) analysis was performed to identify genetic variants that were potentially associated with plasma levels. Fifty-four associations among 29 features and 43 genetic variants were identified at a genome-wide significance threshold p < 3.5 × 10-12 (= 5 × 10-8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; and ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride (m/z 781.7483, retention time (RT) 89.3 s); CALN1 and Tridecanol (m/z 283.2741, RT 27.6). A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for dADP biosynthesis, sterol synthesis, and long-chain fatty acid transport in the gene-feature network. CONCLUSION: Comprehensive profiling of plasma metabolome across age groups combined with genome-wide genotyping revealed a wide range of genetic influence on diverse chemical species and metabolic pathways. The developmental trajectory of a biological system is shaped by gene-environment interaction especially in early life. Therefore, continuous efforts on generating metabolomics data in diverse human tissue types across age groups are required to understand gene-environment interaction toward healthy aging trajectories.

Quantitative trait locus analysis for endophenotypes reveals genetic substrates of core symptom domains and neurocognitive function in autism spectrum disorder.

Autism spectrum disorder (ASD) represents a heterogeneous group of neurodevelopmental disorders and is largely attributable to genetic risk factors. Phenotypic and genetic heterogeneity of ASD have been well-recognized; however, genetic substrates for endophenotypes that constitute phenotypic heterogeneity are not yet known. In the present study, we compiled data from the Autism Genetic Resource Exchange, which contains the demographic and detailed phenotype information of 11,961 individuals. Notably, the whole-genome sequencing data available from MSSNG and iHART for 3833 individuals in this dataset was used to perform an endophenotype-wide association study. Using a linear mixed model, genome-wide association analyses were performed for 29 endophenotype scores and 0.58 million common variants with variant allele frequency ≥ 5%. We discovered significant associations between 9 genetic variants and 6 endophenotype scores comprising neurocognitive development and severity scores for core symptoms of ASD at a significance threshold of p < 5 × 10-7. Of note, the Stereotyped Behaviors and Restricted Interests total score in Autism Diagnostic Observation Schedule Module 3 was significantly associated with multiple variants in the VPS13B gene, a causal gene for Cohen syndrome and a candidate gene for syndromic ASD. Our findings yielded loci with small effect sizes due to the moderate sample size and, thus, require validation in another cohort. Nonetheless, our endophenotype-wide association analysis extends previous candidate gene discovery in the context of genotype and endophenotype association. As a result, these candidate genes may be responsible for specific traits that constitute core symptoms and neurocognitive function of ASD rather than the disorder itself.

Investigation of Anti-Liver Cancer Activity of the Herbal Drug FDY003 Using Network Pharmacology.

Globally, liver cancer (LC) is the sixth-most frequently occurring and the second-most fatal malignancy, responsible for 0.83 million deaths annually. Although the application of herbal drugs in cancer therapies has increased, their anti-LC activity and relevant mechanisms have not been fully studied from a systems perspective. To address these issues, we conducted a system-perspective network pharmacological investigation into the activity and mechanisms underlying the action of the herbal drug. FDY003 reduced the viability of human LC treatment. FDY003 reduced the viability of human LC cells and elevated their chemosensitivity. There were a total of 16 potential bioactive chemical components in FDY003 and they had 91 corresponding targets responsible for the pathological processes in LC. These FDY003 targets were functionally involved in regulating the survival, proliferation, apoptosis, and cell cycle of LC cells. Additionally, we found that FDY003 may target key signaling cascades connected to diverse LC pathological mechanisms, namely, PI3K-Akt, focal adhesion, IL-17, FoxO, MAPK, and TNF pathways. Overall, this study contributed to integrative mechanistic insights into the anti-LC potential of FDY003.

Evolution of multiple omics approaches to define pathophysiology of pediatric acute respiratory distress syndrome.

Pediatric acute respiratory distress syndrome (PARDS), though both common and deadly in critically ill children, lacks targeted therapies. The development of effective pharmacotherapies has been limited, in part, by lack of clarity about the pathobiology of pediatric ARDS. Epithelial lung injury, vascular endothelial activation, and systemic immune activation are putative drivers of this complex disease process. Prior studies have used either hypothesis-driven (e.g., candidate genes and proteins, in vitro investigations) or unbiased (e.g., genome-wide association, transcriptomic, metabolomic) approaches to predict clinical outcomes and to define subphenotypes. Advances in multiple omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have permitted more comprehensive investigation of PARDS pathobiology. However, omics studies have been limited in children compared to adults, and analyses across multiple tissue types are lacking. Here, we synthesized existing literature on the molecular mechanism of PARDS, summarized our interrogation of publicly available genomic databases to determine the association of candidate genes with PARDS phenotypes across multiple tissues and cell types, and integrated recent studies that used single-cell RNA sequencing (scRNA-seq). We conclude that novel profiling methods such as scRNA-seq, which permits more comprehensive, unbiased evaluation of pathophysiological mechanisms across tissue and cell types, should be employed to investigate the molecular mechanisms of PRDS toward the goal of identifying targeted therapies.

Exploration of the System-Level Mechanisms of the Herbal Drug FDY003 for Pancreatic Cancer Treatment: A Network Pharmacological Investigation.

Pancreatic cancer (PC) is the most lethal cancer with the lowest survival rate globally. Although the prescription of herbal drugs against PC is gaining increasing attention, their polypharmacological therapeutic mechanisms are yet to be fully understood. Based on network pharmacology, we explored the anti-PC properties and system-level mechanisms of the herbal drug FDY003. FDY003 decreased the viability of human PC cells and strengthened their chemosensitivity. Network pharmacological analysis of FDY003 indicated the presence of 16 active phytochemical components and 123 PC-related pharmacological targets. Functional enrichment analysis revealed that the PC-related targets of FDY003 participate in the regulation of cell growth and proliferation, cell cycle process, cell survival, and cell death. In addition, FDY003 was shown to target diverse key pathways associated with PC pathophysiology, namely, the PIK3-Akt, MAPK, FoxO, focal adhesion, TNF, p53, HIF-1, and Ras pathways. Our network pharmacological findings advance the mechanistic understanding of the anti-PC properties of FDY003 from a system perspective.

The usefulness of patient-specific 3D nasal silicone implant using 3D design and order form.

PURPOSE: The need for customized implants has continuously increased, but patient-specific silicone implants are not yet commonly used in the plastic surgery market. We sought to validate the effectiveness of a 3D customized nasal implant design in terms of design and lead time compared with a manually customized implant by a surgeon. MATERIALS AND METHODS: Based on the computed tomography (CT) findings of 15 patients who planned rhinoplasty, a surgeon wrote order forms reflecting the surgical plan and subsequently designed implants manually using epoxy on a 3D printed skull. Separately, engineers analyzed the CT findings and designed 3D implants based on the order forms. RESULTS: Epoxy designs were 3D-scanned, converted into a stereolithography format and compared with 3D implant designs to assess which method had a smaller margin of error as per the preoperative order form. Moreover, the lead time in all steps are compared. Nasion thickness, tip thickness, glabella starting point, glabella width, radix width, and total volume were comparatively analyzed. In all parameters, the error rate of the 3D design is relatively lower than that of the epoxy design. The former also had a lower total volume and a faster manufacturing time. CONCLUSION: With novel 3D customized nasal implants, the limitations of ready-made silicone implants are addressed, and it is now possible to preoperatively design implants more accurately, quickly, and conveniently.

Ice front retreat reconfigures meltwater-driven gyres modulating ocean heat delivery to an Antarctic ice shelf.

Pine Island Ice Shelf (PIIS) buttresses the Pine Island Glacier, the key contributor to sea-level rise. PIIS has thinned owing to ocean-driven melting, and its calving front has retreated, leading to buttressing loss. PIIS melting depends primarily on the thermocline variability in its front. Furthermore, local ocean circulation shifts adjust heat transport within Pine Island Bay (PIB), yet oceanic processes underlying the ice front retreat remain unclear. Here, we report a PIB double-gyre that moves with the PIIS calving front and hypothesise that it controls ocean heat input towards PIIS. Glacial melt generates cyclonic and anticyclonic gyres near and off PIIS, and meltwater outflows converge into the anticyclonic gyre with a deep-convex-downward thermocline. The double-gyre migrated eastward as the calving front retreated, placing the anticyclonic gyre over a shallow seafloor ridge, reducing the ocean heat input towards PIIS. Reconfigurations of meltwater-driven gyres associated with moving ice boundaries might be crucial in modulating ocean heat delivery to glacial ice.

Effects of Long-Term In Vitro Expansion on Genetic Stability and Tumor Formation Capacity of Stem Cells.

Stem cell therapeutics are emerging as novel alternative treatments for various neurodegenerative diseases based on their regenerative potentials. However, stem cell transplantation might have side effects such as tumor formation that limit their clinical applications. Especially, in vitro expansion of stem cells might provoke genetic instability and tumorigenic potential. To address this issue, we analyzed genomic alterations of adult human multipotent neural cells (ahMNCs), a type of human adult neural stem cells, after a long-term in vitro culture process (passage 15) using sensitive analysis techniques including karyotyping, array comparative genomic hybridization (aCGH), and whole exome sequencing (WES). Although karyotyping did not find any major abnormalities in chromosomal number or structure, diverse copy number variations (CNVs) and genetic mutations were detected by aCGH and WES in all five independent ahMNCs. However, the number of CNVs and genetic mutations did not increase and many of them did not persist as in vitro culture progressed. Although most observed CNVs and genetic mutations were not shared by all five ahMNCs, nonsynonymous missense mutations at MUC4 were found in three out of five long-term cultured ahMNC lines. The genetic instability did not confer in vivo tumorigenic potential to ahMNCs. Collectively, these results indicate that, although genetic instability can be induced by long-term in vitro expansion of stem cells, it is not sufficient to fully exert tumor formation capacity of stem cells. Other functional effects of such genetic instability need to be further elucidated.

Spin-Orbit Torque Nano-oscillators by Dipole-Field-Localized Spin Wave Modes.

We demonstrate a high-quality spin-orbit torque nano-oscillator comprised of spin wave modes confined by the magnetic field by the strongly inhomogeneous dipole field of a nearby micromagnet. This approach enables variable spatial confinement and systematic tuning of magnon spectrum and spectral separations for studying the impact of multimode interactions on auto-oscillations. We find these dipole-field-localized spin wave modes exhibit good characteristic properties as auto-oscillators─narrow line width and large amplitude─while persisting up to room temperature. We find that the line width of the lowest-lying localized mode is approximately proportional to temperature in good agreement with theoretical analysis of the impact of thermal fluctuations. This demonstration of a clean oscillator with tunable properties provides a powerful tool for understanding the fundamental limitations and line width contributions to improve future spin-Hall oscillators.

Millimeter-sized smart sensors reveal that a solar refuge protects tree snail Partula hyalina from extirpation.

Pacific Island land snails are highly endangered due in part to misguided biological control programs employing the alien predator Euglandina rosea. Its victims include the fabled Society Island partulid tree snail fauna, but a few members have avoided extirpation in the wild, including the distinctly white-shelled Partula hyalina. High albedo shell coloration can facilitate land snail survival in open, sunlit environments and we hypothesized that P. hyalina has a solar refuge from the predator. We developed a 2.2 × 4.8 × 2.4 mm smart solar sensor to test this hypothesis and found that extant P. hyalina populations on Tahiti are restricted to forest edge habitats, where they are routinely exposed to significantly higher solar radiation levels than those endured by the predator. Long-term survival of this species on Tahiti may require proactive conservation of its forest edge solar refugia and our study demonstrates the utility of miniaturized smart sensors in invertebrate ecology and conservation.

WEScover: selection between clinical whole exome sequencing and gene panel testing.

BACKGROUND: Whole exome sequencing (WES) is widely adopted in clinical and research settings; however, one of the practical concerns is the potential false negatives due to incomplete breadth and depth of coverage for several exons in clinically implicated genes. In some cases, a targeted gene panel testing may be a dependable option to ascertain true negatives for genomic variants in known disease-associated genes. We developed a web-based tool to quickly gauge whether all genes of interest would be reliably covered by WES or whether targeted gene panel testing should be considered instead to minimize false negatives in candidate genes. RESULTS: WEScover is a novel web application that provides an intuitive user interface for discovering breadth and depth of coverage across population-scale WES datasets, searching either by phenotype, by targeted gene panel(s) or by gene(s). Moreover, the application shows metrics from the Genome Aggregation Database to provide gene-centric view on breadth of coverage. CONCLUSIONS: WEScover allows users to efficiently query genes and phenotypes for the coverage of associated exons by WES and recommends use of panel tests for the genes with potential incomplete coverage by WES.

Genetic variation analyses indicate conserved SARS-CoV-2-host interaction and varied genetic adaptation in immune response factors in modern human evolution.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a pandemic as of early 2020. Upon infection, SARS-CoV-2 attaches to its receptor, that is, angiotensin-converting enzyme 2 (ACE2), on the surface of host cells and is then internalized into host cells via enzymatic machineries. This subsequently stimulates immune response factors. Since the host immune response and severity of COVID-19 vary among individuals, genetic risk factors for severe COVID-19 cases have been investigated. Our research group recently conducted a survey of genetic variants among SARS-CoV-2-interacting molecules across populations, noting near absence of difference in allele frequency spectrum between populations in these genes. Recent genome-wide association studies have identified genetic risk factors for severe COVID-19 cases in a segment of chromosome 3 that involves six genes encoding three immune-regulatory chemokine receptors and another three molecules. The risk haplotype seemed to be inherited from Neanderthals, suggesting genetic adaptation against pathogens in modern human evolution. Therefore, SARS-CoV-2 uses highly conserved molecules as its virion interaction, whereas its immune response appears to be genetically biased in individuals to some extent. We herein review the molecular process of SARS-CoV-2 infection as well as our further survey of genetic variants of its related immune effectors. We also discuss aspects of modern human evolution.