Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA.

Cupping of the optic nerve head, a highly heritable trait, is a hallmark of glaucomatous optic neuropathy. Two key parameters are vertical cup-to-disc ratio (VCDR) and vertical disc diameter (VDD). However, manual assessment often suffers from poor accuracy and is time intensive. Here, we show convolutional neural network models can accurately estimate VCDR and VDD for 282,100 images from both UK Biobank and an independent study (Canadian Longitudinal Study on Aging), enabling cross-ancestry epidemiological studies and new genetic discovery for these optic nerve head parameters. Using the AI approach, we perform a systematic comparison of the distribution of VCDR and VDD and compare these with intraocular pressure and glaucoma diagnoses across various genetically determined ancestries, which provides an explanation for the high rates of normal tension glaucoma in East Asia. We then used the large number of AI gradings to conduct a more powerful genome-wide association study (GWAS) of optic nerve head parameters. Using the AI-based gradings increased estimates of heritability by ∼50% for VCDR and VDD. Our GWAS identified more than 200 loci associated with both VCDR and VDD (double the number of loci from previous studies) and uncovered dozens of biological pathways; many of the loci we discovered also confer risk for glaucoma.

Portable Surface Plasmon Resonance Detector for COVID-19 Infection.

Methods based on nucleic acid detection are currently the most commonly used technique in COVID-19 diagnostics. Although generally considered adequate, these methods are characterised by quite a long time-to-result and the necessity to prepare the material taken from the examined person-RNA isolation. For this reason, new detection methods are being sought, especially those characterised by the high speed of the analysis process from the moment of sampling to the result. Currently, serological methods of detecting antibodies against the virus in the patient's blood plasma have attracted much attention. Although they are less precise in determining the current infection, such methods shorten the analysis time to several minutes, making it possible to consider them a promising method for screening tests in people with suspected infection. The described study investigated the feasibility of a surface plasmon resonance (SPR)-based detection system for on-site COVID-19 diagnostics. A simple-to-use portable device was proposed for the fast detection of anti-SARS-CoV-2 antibodies in human plasma. SARS-CoV-2-positive and -negative patient blood plasma samples were investigated and compared with the ELISA test. The receptor-binding domain (RBD) of spike protein from SARS-CoV-2 was selected as a binding molecule for the study. Then, the process of antibody detection using this peptide was examined under laboratory conditions on a commercially available SPR device. The portable device was prepared and tested on plasma samples from humans. The results were compared with those obtained in the same patients using the reference diagnostic method. The detection system is effective in the detection of anti-SARS-CoV-2 with the detection limit of 40 ng/mL. It was shown that it is a portable device that can correctly examine human plasma samples within a 10 min timeframe.

Study on Saccharide-Glucose Receptor Interactions with the Use of Surface Plasmon Resonance.

The aim of this study was to investigate the process of attachment of saccharide particles differing in degree of complexity to cell receptors responsible for transport of glucose across the cell membrane (GLUT proteins). This phenomenon is currently considered when designing modern medicines, e.g., peptide drugs to which glucose residues are attached, enabling drugs to cross the barrier of cell membranes and act inside cells. This study aims to help us understand the process of assimilation of polysaccharide nanoparticles by tumour cells. In this study, the interactions between simple saccharides (glucose and sucrose) and dextran nanoparticles with two species of GLUT proteins (GLUT1 and GLUT4) were measured using the surface plasmon resonance technique. We managed to observe the interactions of glucose and sucrose with both applied proteins. The lowest concentration that resulted in the detection of interaction was 4 mM of glucose on GLUT1. Nanoparticles were measured using the same proteins with a detection limit of 40 mM. These results indicate that polysaccharide nanoparticles interact with GLUT proteins. The measured strengths of interactions differ between proteins; thus, this study can suggest which protein is preferable when considering it as a mean of nanoparticle carrier transport.

Exploring Extracellular Vesicles of Probiotic Yeast as Carriers of Biologically Active Molecules Transferred to Human Intestinal Cells.

Extracellular vesicles (EVs) are nanoparticles containing various bioactive cargos-e.g., proteins, RNAs, and lipids-that are released into the environment by all cell types. They are involved in, amongst other functions, intercellular communication. This article presents studies on EVs produced by the probiotic yeast Saccharomyces boulardii CNCM I-745. The size distribution and concentration of EVs in the liquid culture of yeast were estimated. Moreover, the vesicles of S. boulardii were tested for their cytotoxicity against three model human intestinal cell lines. This study did not show any significant negative effect of yeast EVs on these cells under tested conditions. In addition, EVs of S. boulardii were verified for their ability to internalize in vitro with human cells and transfer their cargo. The yeast vesicles were loaded with doxorubicin, an anticancer agent, and added to the cellular cultures. Subsequently, microscopic observations revealed that these EVs transferred the compound to human intestinal cell lines. A cytotoxicity test confirmed the activity of the transferred doxorubicin. Detailed information about the proteins present in EVs might be important in terms of exploring yeast EVs as carriers of active molecules. Thus, proteomic analysis of the EV content was also conducted within the present study, and it allowed the identification of 541 proteins after matching them to the Saccharomyces Genome Database (SGD). Altogether, this study provides strong evidence that the EVs of the probiotic CNCM I-745 strain could be considered a drug delivery system.

Protein-Mediated Transformations of Superparamagnetic Nanoparticles Evidenced by Single-Particle Inductively Coupled Plasma Tandem Mass Spectrometry: A Disaggregation Phenomenon.

Progress toward translating superparamagnetic iron oxide nanoparticles (SPIONs) with specific diagnostic and therapeutic properties for clinical applications depends on developing and implementing appropriate methodologies that would allow in-depth characterizations of their behavior in a real biological environment. Herein, we report a versatile approach for studying interactions between SPIONs and proteins using single-particle inductively coupled plasma tandem mass spectrometry. By monitoring the changes in the size distribution upon exposure to human serum, the formation of stable protein corona is revealed, accompanied by particle disaggregation.

Comparative Evaluation of Different Surface Coatings of Fe3O4-Based Magnetic Nano Sorbent for Applications in the Nucleic Acids Extraction.

Nucleic acid extraction and purification are crucial steps in sample preparation for multiple diagnostic procedures. Routine methodologies of DNA isolation require benchtop equipment (e.g., centrifuges) and labor-intensive steps. Magnetic nanoparticles (MNPs) as solid-phase sorbents could simplify this procedure. A wide range of surface coatings employs various molecular interactions between dsDNA and magnetic nano-sorbents. However, a reliable, comparative evaluation of their performance is complex. In this work, selected Fe3O4 modifications, i.e., polyethyleneimine, gold, silica, and graphene derivatives, were comprehensively evaluated for applications in dsDNA extraction. A family of single batch nanoparticles was compared in terms of morphology (STEM), composition (ICP-MS/MS and elemental analysis), surface coating (UV-Vis, TGA, FTIR), and MNP charge (ζ-potential). ICP-MS/MS was also used to unify MNPs concentration allowing a reliable assessment of individual coatings on DNA extraction. Moreover, studies on adsorption medium (monovalent vs. divalent ions) and extraction buffer composition were carried out. As a result, essential relationships between nanoparticle coatings and DNA adsorption efficiencies have been noticed. Fe3O4@PEI MNPs turned out to be the most efficient nano sorbents. The optimized composition of the extraction buffer (medium containing 0.1 mM EDTA) helped avoid problems with Fe3+ stripping, which improved the validity of the spectroscopic determination of DNA recovery.

MicroRNA Delivery by Graphene-Based Complexes into Glioblastoma Cells.

Glioblastoma (GBM) is the most common primary and aggressive tumour in brain cancer. Novel therapies, despite achievements in chemotherapy, radiation and surgical techniques, are needed to improve the treatment of GBM tumours and extend patients' survival. Gene delivery therapy mostly uses the viral vector, which causes serious adverse events in gene therapy. Graphene-based complexes can reduce the potential side effect of viral carries, with high efficiency of microRNA (miRNA) or antisense miRNA delivery to GBM cells. The objective of this study was to use graphene-based complexes to induce deregulation of miRNA level in GBM cancer cells and to regulate the selected gene expression involved in apoptosis. The complexes were characterised by Fourier transform infrared spectroscopy (FTIR), scanning transmission electron microscopy and zeta potential. The efficiency of miRNA delivery to the cancer cells was analysed by flow cytometry. The effect of the anticancer activity of graphene-based complexes functionalised by the miRNA sequence was analysed using 2,3-bis-(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxyanilide salt (XTT) assays at the gene expression level. The results partly explain the mechanisms of miRNA deregulation stress, which is affected by graphene-based complexes together with the forced transport of mimic miR-124, miR-137 and antisense miR-21, -221 and -222 as an anticancer supportive therapy.

Discontinuity in the genetic and environmental causes of the intellectual disability spectrum.

Intellectual disability (ID) occurs in almost 3% of newborns. Despite substantial research, a fundamental question about its origin and links to intelligence (IQ) still remains. ID has been shown to be inherited and has been accepted as the extreme low of the normal IQ distribution. However, ID displays a complex pattern of inheritance. Previously, noninherited rare mutations were shown to contribute to severe ID risk in individual families, but in the majority of cases causes remain unknown. Common variants associated with ID risk in the population have not been systematically established. Here we evaluate the hypothesis, originally proposed almost 1 century ago, that most ID is caused by the same genetic and environmental influences responsible for the normal distribution of IQ, but that severe ID is not. We studied more than 1,000,000 sibling pairs and 9,000 twin pairs assessed for IQ and for the presence of ID. We evaluated whether genetic and environmental influences at the extremes of the distribution are different from those operating in the normal range. Here we show that factors influencing mild ID (lowest 3% of IQ distribution) were similar to those influencing IQ in the normal range. In contrast, the factors influencing severe ID (lowest 0.5% of IQ distribution) differ from those influencing mild ID or IQ scores in the normal range. Taken together, our results suggest that most severe ID is a distinct condition, qualitatively different from the preponderance of ID, which, in turn, represents the low extreme of the normal distribution of intelligence.

Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder.

Major depressive disorder (MDD) is clinically heterogeneous with prevalence rates twice as high in women as in men. There are many possible sources of heterogeneity in MDD most of which are not measured in a sufficiently comparable way across study samples. Here, we assess genetic heterogeneity based on two fundamental measures, between-cohort and between-sex heterogeneity. First, we used genome-wide association study (GWAS) summary statistics to investigate between-cohort genetic heterogeneity using the 29 research cohorts of the Psychiatric Genomics Consortium (PGC; N cases = 16,823, N controls = 25,632) and found that some of the cohort heterogeneity can be attributed to ascertainment differences (such as recruitment of cases from hospital vs. community sources). Second, we evaluated between-sex genetic heterogeneity using GWAS summary statistics from the PGC, Kaiser Permanente GERA, UK Biobank, and the Danish iPSYCH studies but did not find convincing evidence for genetic differences between the sexes. We conclude that there is no evidence that the heterogeneity between MDD data sets and between sexes reflects genetic heterogeneity. Larger sample sizes with detailed phenotypic records and genomic data remain the key to overcome heterogeneity inherent in assessment of MDD.

Mosaic structural variation in children with developmental disorders.

Delineating the genetic causes of developmental disorders is an area of active investigation. Mosaic structural abnormalities, defined as copy number or loss of heterozygosity events that are large and present in only a subset of cells, have been detected in 0.2-1.0% of children ascertained for clinical genetic testing. However, the frequency among healthy children in the community is not well characterized, which, if known, could inform better interpretation of the pathogenic burden of this mutational category in children with developmental disorders. In a case-control analysis, we compared the rate of large-scale mosaicism between 1303 children with developmental disorders and 5094 children lacking developmental disorders, using an analytical pipeline we developed, and identified a substantial enrichment in cases (odds ratio = 39.4, P-value 1.073e - 6). A meta-analysis that included frequency estimates among an additional 7000 children with congenital diseases yielded an even stronger statistical enrichment (P-value 1.784e - 11). In addition, to maximize the detection of low-clonality events in probands, we applied a trio-based mosaic detection algorithm, which detected two additional events in probands, including an individual with genome-wide suspected chimerism. In total, we detected 12 structural mosaic abnormalities among 1303 children (0.9%). Given the burden of mosaicism detected in cases, we suspected that many of the events detected in probands were pathogenic. Scrutiny of the genotypic-phenotypic relationship of each detected variant assessed that the majority of events are very likely pathogenic. This work quantifies the burden of structural mosaicism as a cause of developmental disorders.

The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence.

Because educational achievement at the end of compulsory schooling represents a major tipping point in life, understanding its causes and correlates is important for individual children, their families, and society. Here we identify the general ingredients of educational achievement using a multivariate design that goes beyond intelligence to consider a wide range of predictors, such as self-efficacy, personality, and behavior problems, to assess their independent and joint contributions to educational achievement. We use a genetically sensitive design to address the question of why educational achievement is so highly heritable. We focus on the results of a United Kingdom-wide examination, the General Certificate of Secondary Education (GCSE), which is administered at the end of compulsory education at age 16. GCSE scores were obtained for 13,306 twins at age 16, whom we also assessed contemporaneously on 83 scales that were condensed to nine broad psychological domains, including intelligence, self-efficacy, personality, well-being, and behavior problems. The mean of GCSE core subjects (English, mathematics, science) is more heritable (62%) than the nine predictor domains (35-58%). Each of the domains correlates significantly with GCSE results, and these correlations are largely mediated genetically. The main finding is that, although intelligence accounts for more of the heritability of GCSE than any other single domain, the other domains collectively account for about as much GCSE heritability as intelligence. Together with intelligence, these domains account for 75% of the heritability of GCSE. We conclude that the high heritability of educational achievement reflects many genetically influenced traits, not just intelligence.

Common genetic variants associated with cognitive performance identified using the proxy-phenotype method.

We identify common genetic variants associated with cognitive performance using a two-stage approach, which we call the proxy-phenotype method. First, we conduct a genome-wide association study of educational attainment in a large sample (n = 106,736), which produces a set of 69 education-associated SNPs. Second, using independent samples (n = 24,189), we measure the association of these education-associated SNPs with cognitive performance. Three SNPs (rs1487441, rs7923609, and rs2721173) are significantly associated with cognitive performance after correction for multiple hypothesis testing. In an independent sample of older Americans (n = 8,652), we also show that a polygenic score derived from the education-associated SNPs is associated with memory and absence of dementia. Convergent evidence from a set of bioinformatics analyses implicates four specific genes (KNCMA1, NRXN1, POU2F3, and SCRT). All of these genes are associated with a particular neurotransmitter pathway involved in synaptic plasticity, the main cellular mechanism for learning and memory.

Thinking positively: The genetics of high intelligence.

High intelligence (general cognitive ability) is fundamental to the human capital that drives societies in the information age. Understanding the origins of this intellectual capital is important for government policy, for neuroscience, and for genetics. For genetics, a key question is whether the genetic causes of high intelligence are qualitatively or quantitatively different from the normal distribution of intelligence. We report results from a sibling and twin study of high intelligence and its links with the normal distribution. We identified 360,000 sibling pairs and 9000 twin pairs from 3 million 18-year-old males with cognitive assessments administered as part of conscription to military service in Sweden between 1968 and 2010. We found that high intelligence is familial, heritable, and caused by the same genetic and environmental factors responsible for the normal distribution of intelligence. High intelligence is a good candidate for "positive genetics" - going beyond the negative effects of DNA sequence variation on disease and disorders to consider the positive end of the distribution of genetic effects.

Genes influence young children's human figure drawings and their association with intelligence a decade later.

Drawing is ancient; it is the only childhood cognitive behavior for which there is any direct evidence from the Upper Paleolithic. Do genes influence individual differences in this species-typical behavior, and is drawing related to intelligence (g) in modern children? We report on the first genetically informative study of children's figure drawing. In a study of 7,752 pairs of twins, we found that genetic differences exert a greater influence on children's figure drawing at age 4 than do between-family environmental differences. Figure drawing was as heritable as g at age 4 (heritability of .29 for both). Drawing scores at age 4 correlated significantly with g at age 4 (r = .33, p < .001, n = 14,050) and with g at age 14 (r = .20, p < .001, n = 4,622). The genetic correlation between drawing at age 4 and g at age 14 was .52, 95% confidence interval = [.31, .75]. Individual differences in this widespread behavior have an important genetic component and a significant genetic link with g.

Word reading fluency: role of genome-wide single-nucleotide polymorphisms in developmental stability and correlations with print exposure.

The genetic effects on individual differences in reading development were examined using genome-wide complex trait analysis (GCTA) in a twin sample. In unrelated individuals (one twin per pair, n = 2,942), the GCTA-based heritability of reading fluency was ~20%-29% at ages 7 and 12. GCTA bivariate results showed that the phenotypic stability of reading fluency from 7 to 12 years (r = 0.69) is largely driven by genetic stability (genetic r = 0.69). Genetic effects on print exposure at age 12 were moderate (~26%) and correlated with those influencing reading fluency at 12 (genetic r = 0.89), indicative of a gene-environment correlation. These findings were largely consistent with quantitative genetic twin analyses that used both twins in each pair (n = 1,066-1,409).

Nature, Nurture, and Expertise.

Rather than investigating the extent to which training can improve performance under experimental conditions ('what could be'), we ask about the origins of expertise as it exists in the world ('what is'). We used the twin method to investigate the genetic and environmental origins of exceptional performance in reading, a skill that is a major focus of educational training in the early school years. Selecting reading experts as the top 5% from a sample of 10,000 12-year-olds twins assessed on a battery of reading tests, three findings stand out. First, we found that genetic factors account for more than half of the difference in performance between expert and normal readers. Second, our results suggest that reading expertise is the quantitative extreme of the same genetic and environmental factors that affect reading performance for normal readers. Third, growing up in the same family and attending the same schools account for less than a fifth of the difference between expert and normal readers. We discuss implications and interpretations ('what is inherited is DNA sequence variation'; 'the abnormal is normal'). Finally, although there is no necessary relationship between 'what is' and 'what could be', the most far-reaching issues about the acquisition of expertise lie at the interface between them ('the nature of nurture: from a passive model of imposed environments to an active model of shaped experience').

Genetic influence on family socioeconomic status and children's intelligence.

Environmental measures used widely in the behavioral sciences show nearly as much genetic influence as behavioral measures, a critical finding for interpreting associations between environmental factors and children's development. This research depends on the twin method that compares monozygotic and dizygotic twins, but key aspects of children's environment such as socioeconomic status (SES) cannot be investigated in twin studies because they are the same for children growing up together in a family. Here, using a new technique applied to DNA from 3000 unrelated children, we show significant genetic influence on family SES, and on its association with children's IQ at ages 7 and 12. In addition to demonstrating the ability to investigate genetic influence on between-family environmental measures, our results emphasize the need to consider genetics in research and policy on family SES and its association with children's IQ.

Advanced three-dimensional in vitro liver models to study the activity of anticancer drugs.

The liver is one of the most important organs in the human body. It performs many important functions, including being responsible for the metabolism of most drugs, which is often associated with its drug-induced damage. Currently, there are no ideal pharmacological models that would allow the evaluation of the effect of newly tested drugs on the liver in preclinical studies. Moreover, the influence of hepatic metabolism on the effectiveness of the tested drugs is rarely evaluated. Therefore, in this work we present an advanced model of the liver, which reflects most of the morphologically and metabolically important features of the liver in vivo, namely: three-dimensionality, cellular composition, presence of extracellular matrix, distribution of individual cell types in the structure of the liver model, high urea and albumin synthesis efficiency, high cytochrome p450 activity. In addition, the work, based on the example of commonly used anticancer drugs, shows how important it is to take into account hepatic metabolism in the effective assessment of their impact on the target organ, in this case cancer. In our research, we have shown that the most similar to liver in vivo are 3D cellular aggregates composed of three important liver cells, namely hepatocytes (HepG2), hepatic stellate cells (HSCs), and hepatic sinusoidal endothelial cells (HSECs). Moreover, we showed that the cells in 3D aggregate structure need time (cell-cell interactions) to improve proper liver characteristic. The triculture model additionally showed the greatest ability to metabolize selected anticancer drugs.

DNA evidence for strong genome-wide pleiotropy of cognitive and learning abilities.

Very different neurocognitive processes appear to be involved in cognitive abilities such as verbal and non-verbal ability as compared to learning abilities taught in schools such as reading and mathematics. However, twin studies that compare similarity for monozygotic and dizygotic twins suggest that the same genes are largely responsible for genetic influence on these diverse aspects of cognitive function. It is now possible to test this evidence for strong pleiotropy using DNA alone from samples of unrelated individuals. Here we used this new method with 1.7 million DNA markers for a sample of 2,500 unrelated children at age 12 to investigate for the first time the extent of pleiotropy between general cognitive ability (aka intelligence) and learning abilities (reading, mathematics and language skills). We also compared these DNA results to results from twin analyses using the same sample and measures. The DNA-based method revealed strong genome-wide pleiotropy: Genetic correlations were greater than 0.70 between general cognitive ability and language, reading, and mathematics, results that were highly similar to twin study estimates of genetic correlations. These results indicate that genes related to diverse neurocognitive processes have general rather than specific effects.

The role of gene-environment correlations and interactions in middle childhood depressive symptoms.

Depression is known to be associated with a wide array of environmental factors. Such associations are due at least in part to genetic influences on both. This issue has been little explored with preadolescent children. Measures of family chaos and parenting style at age 9 and child depressive symptoms at age 12 were completed by 3,258 twin pairs from the Twins Early Development Study and their parents. Quantitative genetic modeling was used to explore common and unique genetic and environmental influences on both family environment and later depressive symptoms. Depressive symptoms at age 12 were significantly heritable. Moderate genetic effects influenced parenting style and family chaos at the age of 9, indicating gene-environment correlation. There were significant genetic correlations between family environment and depressive symptoms. There was some evidence of a Gene × Environment interaction, with stronger genetic effects on depressive symptoms for children with more suboptimal family environment. There was an Environment × Environment interaction, with effects of nonshared environment on depressive symptoms stronger for twins with more adverse parenting experiences. There is some evidence for gene-environment correlation between aspects of family environment in middle childhood and subsequent depressive symptoms. This suggests that one of the mechanisms by which genes lead to depressive symptoms may be by themselves influencing depressogenic environments.