Low-frequency variation in TP53 has large effects on head circumference and intracranial volume

The Causal Relationships Between Gut Microbiota, Brain Volume, and Intelligence: A Two-Step Mendelian Randomization Analysis

BACKGROUND

Growing evidence indicates that dynamic changes in gut microbiome can affect intelligence; however, whether these relationships are causal remains elusive. We aimed to disentangle the poorly understood causal relationship between gut microbiota and intelligence.

METHODS

We performed a 2-sample Mendelian randomization (MR) analysis using genetic variants from the largest available genome-wide association studies of gut microbiota (N = 18,340) and intelligence (N = 269,867). The inverse-variance weighted method was used to conduct the MR analyses complemented by a range of sensitivity analyses to validate the robustness of the results. Considering the close relationship between brain volume and intelligence, we applied 2-step MR to evaluate whether the identified effect was mediated by regulating brain volume (N = 47,316).

RESULTS

We found a risk effect of the genus Oxalobacter on intelligence (odds ratio = 0.968 change in intelligence per standard deviation increase in taxa; 95% CI, 0.952-0.985; p = 1.88 × 10-4) and a protective effect of the genus Fusicatenibacter on intelligence (odds ratio = 1.053; 95% CI, 1.024-1.082; p = 3.03 × 10-4). The 2-step MR analysis further showed that the effect of genus Fusicatenibacter on intelligence was partially mediated by regulating brain volume, with a mediated proportion of 33.6% (95% CI, 6.8%-60.4%; p = .014).

CONCLUSIONS

Our results provide causal evidence indicating the role of the microbiome in intelligence. Our findings may help reshape our understanding of the microbiota-gut-brain axis and development of novel intervention approaches for preventing cognitive impairment.

Integrative Approach of Treating Early Undernutrition with an Enriched Black Corn Chip, Study on a Murine Model

Undernutrition (UN) increases child vulnerability to illness and mortality. Caused by a low amount and/or poor quality of food intake, it impacts physical, cognitive, and social development. Modern types of food consumption have given highly processed food a higher cultural value compared to minimally processed food.

OBJECTIVE

The objective of this study was to evaluate the effect on growth, metabolism, physical activity (PA), memory, inflammation, and toxicity of an enriched black corn chip (BC) made with endemic ingredients on post-weaned UN mice.

METHODS

A chip was made with a mixture of black corn, fava beans, amaranth, and nopal cactus. To probe the effects of UN, UN was induced in 3wo post-weaned male C57Bl/6j mice through a low-protein diet (LPD-50% of the regular requirement of protein) for 3w. Then, the BC was introduced to the animals' diet (17%) for 5w; murinometric parameters were measured, as were postprandial glucose response, PA, and short-term memory. Histological analysis was conducted on the liver and kidneys to measure toxicity. Gene expression related to energy balance, thermogenesis, and inflammation was measured in adipose and hypothalamic tissues.

RESULTS

Treatment with the BC significantly improved mouse growth, even with a low protein intake, as evidenced by a significant increase in body weight, tail length, cerebral growth, memory improvement, physical activation, normalized energy expenditure (thermogenesis), and orexigenic peptides (AGRP and NPY). It decreased anorexigenic peptides (POMC), and there was no tissue toxicity.

CONCLUSIONS

BC treatment, even with persistent low protein intake, is a promising strategy against UN, as it showed efficacy in correcting growth deficiency, cognitive impairment, and metabolic problems linked to treatment by adjusting energy expenditure, which led to the promotion of energy intake and regulation of thermogenesis, all by using low-cost, accessible, and endemic ingredients.

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Genome-Wide Analyses of Vocabulary Size in Infancy and Toddlerhood: Associations With Attention-Deficit/Hyperactivity Disorder, Literacy, and Cognition-Related Traits

BACKGROUND

The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors. Here, we performed a meta-genome-wide association study of vocabulary acquisition and investigated polygenic overlap with literacy, cognition, developmental phenotypes, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD).

METHODS

We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months), and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated single nucleotide polymorphism-based heritability (SNP-h2) and genetic correlations (rg) and modeled underlying factor structures with multivariate models.

RESULTS

Early-life vocabulary size was modestly heritable (SNP-h2 = 0.08-0.24). Genetic overlap between infant expressive and toddler receptive vocabulary was negligible (rg = 0.07), although each measure was moderately related to toddler expressive vocabulary (rg = 0.69 and rg = 0.67, respectively), suggesting a multifactorial genetic architecture. Both infant and toddler expressive vocabulary were genetically linked to literacy (e.g., spelling: rg = 0.58 and rg = 0.79, respectively), underlining genetic similarity. However, a genetic association of early-life vocabulary with educational attainment and intelligence emerged only during toddlerhood (e.g., receptive vocabulary and intelligence: rg = 0.36). Increased ADHD risk was genetically associated with larger infant expressive vocabulary (rg = 0.23). Multivariate genetic models in the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort confirmed this finding for ADHD symptoms (e.g., at age 13; rg = 0.54) but showed that the association effect reversed for toddler receptive vocabulary (rg = -0.74), highlighting developmental heterogeneity.

CONCLUSIONS

The genetic architecture of early-life vocabulary changes during development, shaping polygenic association patterns with later-life ADHD, literacy, and cognition-related traits.

The molecular genetic landscape of human brain size variation

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.

Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape

The cranial vault in humans is highly variable, clinically relevant, and heritable, yet its genetic architecture remains poorly understood. Here, we conduct a joint multi-ancestry and admixed multivariate genome-wide association study on 3D cranial vault shape extracted from magnetic resonance images of 6772 children from the ABCD study cohort yielding 30 genome-wide significant loci. Follow-up analyses indicate that these loci overlap with genomic risk loci for sagittal craniosynostosis, show elevated activity cranial neural crest cells, are enriched for processes related to skeletal development, and are shared with the face and brain. We present supporting evidence of regional localization for several of the identified genes based on expression patterns in the cranial vault bones of E15.5 mice. Overall, our study provides a comprehensive overview of the genetics underlying normal-range cranial vault shape and its relevance for understanding modern human craniofacial diversity and the etiology of congenital malformations.

Genomic insights into the genetic basis of eagle-beak jaw, large head, and long tail in the big-headed turtle

The big-headed turtle (Platysternon megacephalum) is an endemic chelonian species in Asia. Unlike most other turtles in the world, P. megacephalum is characterized with eagle-beak jaw, large head, and long tail. Although these unique characteristics are well recognized, the underlying genetic basis remains largely elusive. Here, we performed comparative genomic analysis between P. megacephalum and other representative species, aiming to reveal the genetic basis of the unique morphological features. Our results revealed that the eagle-beak jaw is most likely enabled by combined effects of expansion of SFRP5, extraction of FGF11, and mutation of both ZFYVE16 and PAX6. Large head is supported by mutations of SETD2 and FGRF2 and copy number variations of six head circumference modulation-related genes (TGFBR2, Twist2, Rdh10, Gas1, Chst11, and SNAP25). The long tail is probably involved in a genetic network comprising Gdf11, Lin 28, and HoxC12, two of which showed a consistent expression pattern with a model organism (mice). These findings suggest that expansion, extraction, and mutation of those genes may have profound effects on unique phenotypes of P. megacephalum.

PAM-independent ultra-specific activation of CRISPR-Cas12a via sticky-end dsDNA

Although CRISPR-Cas12a [clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 12a] combining pre-amplification technology has the advantage of high sensitivity in biosensing, its generality and specificity are insufficient, which greatly restrains its application range. Here, we discovered a new targeting substrate for LbaCas12a (Lachnospiraceae bacterium Cas12a), namely double-stranded DNA (dsDNA) with a sticky-end region (PAM-SE+ dsDNA). We discovered that CRISPR-Cas12a had special enzymatic properties for this substrate DNA, including the ability to recognize and cleave it without needing a protospacer adjacent motif (PAM) sequence and a high sensitivity to single-base mismatches in that substrate. Further mechanism studies revealed that guide RNA (gRNA) formed a triple-stranded flap structure with the substrate dsDNA. We also discovered the property of low-temperature activation of CRISPR-Cas12a and, by coupling with the unique DNA hybridization kinetics at low temperature, we constructed a complete workflow for low-abundance point mutation detection in real samples, which was fast, convenient and free of single-stranded DNA (ssDNA) transformation. The detection limits were 0.005-0.01% for synthesized strands and 0.01-0.05% for plasmid genomic DNA, and the mutation abundances provided by our system for 28 clinical samples were in accordance with next-generation sequencing results. We believe that our work not only reveals novel information about the target recognition mechanism of the CRISPR-Cas12a system, but also greatly broadens its application scenarios.

Genetics of early-life head circumference and genetic correlations with neurological, psychiatric and cognitive outcomes

BACKGROUND

Head circumference is associated with intelligence and tracks from childhood into adulthood.

METHODS

We performed a genome-wide association study meta-analysis and follow-up of head circumference in a total of 29,192 participants between 6 and 30 months of age.

RESULTS

Seven loci reached genome-wide significance in the combined discovery and replication analysis of which three loci near ARFGEF2, MYCL1, and TOP1, were novel. We observed positive genetic correlations for early-life head circumference with adult intracranial volume, years of schooling, childhood and adult intelligence, but not with adult psychiatric, neurological, or personality-related phenotypes.

CONCLUSIONS

The results of this study indicate that the biological processes underlying early-life head circumference overlap largely with those of adult head circumference. The associations of early-life head circumference with cognitive outcomes across the life course are partly explained by genetics.

Inherited variants in CHD3 show variable expressivity in Snijders Blok-Campeau syndrome

PURPOSE

Common diagnostic next-generation sequencing strategies are not optimized to identify inherited variants in genes associated with dominant neurodevelopmental disorders as causal when the transmitting parent is clinically unaffected, leaving a significant number of cases with neurodevelopmental disorders undiagnosed.

METHODS

We characterized 21 families with inherited heterozygous missense or protein-truncating variants in CHD3, a gene in which de novo variants cause Snijders Blok-Campeau syndrome.

RESULTS

Computational facial and Human Phenotype Ontology-based comparisons showed that the phenotype of probands with inherited CHD3 variants overlaps with the phenotype previously associated with de novo CHD3 variants, whereas heterozygote parents are mildly or not affected, suggesting variable expressivity. In addition, similarly reduced expression levels of CHD3 protein in cells of an affected proband and of healthy family members with a CHD3 protein-truncating variant suggested that compensation of expression from the wild-type allele is unlikely to be an underlying mechanism. Notably, most inherited CHD3 variants were maternally transmitted.

CONCLUSION

Our results point to a significant role of inherited variation in Snijders Blok-Campeau syndrome, a finding that is critical for correct variant interpretation and genetic counseling and warrants further investigation toward understanding the broader contributions of such variation to the landscape of human disease.

Thirty novel sequence variants impacting human intracranial volume

Intracranial volume, measured through magnetic resonance imaging and/or estimated from head circumference, is heritable and correlates with cognitive traits and several neurological disorders. We performed a genome-wide association study meta-analysis of intracranial volume (n = 79 174) and found 64 associating sequence variants explaining 5.0% of its variance. We used coding variation, transcript and protein levels, to uncover 12 genes likely mediating the effect of these variants, including GLI3 and CDK6 that affect cranial synostosis and microcephaly, respectively. Intracranial volume correlates genetically with volumes of cortical and sub-cortical regions, cognition, learning, neonatal and neurological traits. Parkinson's disease cases have greater and attention deficit hyperactivity disorder cases smaller intracranial volume than controls. Our Mendelian randomization studies indicate that intracranial volume associated variants either increase the risk of Parkinson's disease and decrease the risk of attention deficit hyperactivity disorder and neuroticism or correlate closely with a confounder.

Heritable genetic variants in key cancer genes link cancer risk with anthropometric traits

BACKGROUND

Height and other anthropometric measures are consistently found to associate with differential cancer risk. However, both genetic and mechanistic insights into these epidemiological associations are notably lacking. Conversely, inherited genetic variants in tumour suppressors and oncogenes increase cancer risk, but little is known about their influence on anthropometric traits.

METHODS

By integrating inherited and somatic cancer genetic data from the Genome-Wide Association Study Catalog, expression Quantitative Trait Loci databases and the Cancer Gene Census, we identify SNPs that associate with different cancer types and differential gene expression in at least one tissue type, and explore the potential pleiotropic associations of these SNPs with anthropometric traits through SNP-wise association in a cohort of 500,000 individuals.

RESULTS

We identify three regulatory SNPs for three important cancer genes, FANCA, MAP3K1 and TP53 that associate with both anthropometric traits and cancer risk. Of particular interest, we identify a previously unrecognised strong association between the rs78378222[C] SNP in the 3' untranslated region (3'-UTR) of TP53 and both increased risk for developing non-melanomatous skin cancer (OR=1.36 (95% 1.31 to 1.41), adjusted p=7.62E-63), brain malignancy (OR=3.12 (2.22 to 4.37), adjusted p=1.43E-12) and increased standing height (adjusted p=2.18E-24, beta=0.073±0.007), lean body mass (adjusted p=8.34E-37, beta=0.073±0.005) and basal metabolic rate (adjusted p=1.13E-31, beta=0.076±0.006), thus offering a novel genetic link between these anthropometric traits and cancer risk.

CONCLUSION

Our results clearly demonstrate that heritable variants in key cancer genes can associate with both differential cancer risk and anthropometric traits in the general population, thereby lending support for a genetic basis for linking these human phenotypes.

The EU Child Cohort Network's core data: establishing a set of findable, accessible, interoperable and re-usable (FAIR) variables

The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network's core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network's data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community.

Combining Structural-Equation Modeling with Genomic-Relatedness-Matrix Restricted Maximum Likelihood in OpenMx

There is a long history of fitting biometrical structural-equation models (SEMs) in the pregenomic behavioral-genetics literature of twin, family, and adoption studies. Recently, a method has emerged for estimating biometrical variance-covariance components based not upon the expected degree of genetic resemblance among relatives, but upon the observed degree of genetic resemblance among unrelated individuals for whom genome-wide genotypes are available-genomic-relatedness-matrix restricted maximum-likelihood (GREML). However, most existing GREML software is concerned with quickly and efficiently estimating heritability coefficients, genetic correlations, and so on, rather than with allowing the user to fit SEMs to multitrait samples of genotyped participants. We therefore introduce a feature in the OpenMx package, "mxGREML", designed to fit the biometrical SEMs from the pregenomic era in present-day genomic study designs. We explain the additional functionality this new feature has brought to OpenMx, and how the new functionality works. We provide an illustrative example of its use. We discuss the feature's current limitations, and our plans for its further development.

Genome-wide meta-analysis of brain volume identifies genomic loci and genes shared with intelligence

The phenotypic correlation between human intelligence and brain volume (BV) is considerable (r ≈ 0.40), and has been shown to be due to shared genetic factors. To further examine specific genetic factors driving this correlation, we present genomic analyses of the genetic overlap between intelligence and BV using genome-wide association study (GWAS) results. First, we conduct a large BV GWAS meta-analysis (N = 47,316 individuals), followed by functional annotation and gene-mapping. We identify 18 genomic loci (14 not previously associated), implicating 343 genes (270 not previously associated) and 18 biological pathways for BV. Second, we use an existing GWAS for intelligence (N = 269,867 individuals), and estimate the genetic correlation (rg) between BV and intelligence to be 0.24. We show that the rg is partly attributable to physical overlap of GWAS hits in 5 genomic loci. We identify 92 shared genes between BV and intelligence, which are mainly involved in signaling pathways regulating cell growth. Out of these 92, we prioritize 32 that are most likely to have functional impact. These results provide information on the genetics of BV and provide biological insight into BV's shared genetic etiology with intelligence.

Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits

The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.

Genetic variation in APOE, GRN, and TP53 are phenotype modifiers in frontotemporal dementia

Frontotemporal dementia (FTD) is a clinical, genetic, and pathologic heterogeneous group of neurodegenerative diseases. In this study, we investigated the role of APOƐ4, rs5848 in GRN, and rs1042522 in TP53 gene as disease risk factors and/or phenotype modifiers in 440 FTD patients, including 175 C9orf72 expansion carriers. We found that the C9orf72 expansion carriers showing an earlier age at onset (p < 0.001). Among the clinical groups, the FTD-MND (motoneuron disease) showed the lowest survival (hazard ratio [HR] = 4.12), and the progressive nonfluent aphasia group showed the highest onset age (p = 0.03). In our cohort, the rs1042522 in TP53 was associated with disease onset (p = 0.02) and survival (HR = 1.73) and rs5848 GRN with a significantly shorter survival in CC homozygous patients (HR = 1.98). The frequency of APOƐ4 carriers was significantly increased in the C9orf72 noncarriers (p = 0.022). Although validation of our findings is necessary, our results suggest that TP53, GRN, and APOE genes may act as phenotype modifiers in FTD and should be considered in future clinical trials.

The LifeCycle Project-EU Child Cohort Network: a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.

Morphometric traits predict educational attainment independently of socioeconomic background

Background

Aim of this study is to describe the relationship between anthropometric traits and educational attainment among Estonian schoolchildren born between 1937 and 1962. We asked whether height, cranial volume and face width (a testosterone-dependent trait), measured in childhood predict later educational attainment independently of each other, family socioeconomic position (SEP) and sex. Associations between morphometric traits and education and their interactions with biosocial variables are of scholarly importance because higher education is nearly universally associated with low fertility in women, and often with high fertility in men. Hence, morphometric traits associated with educational attainment are targeted by natural selection and describing the exact nature of these associations is relevant for understanding the current patterns of evolution of human body size.

Methods

Data on morphometric measurements and family background of 11,032 Estonian schoolchildren measured between seven and 19 years of age were obtained from the study performed by Juhan Aul between 1956 and 1969. Ordinal logistic regression was used for testing the effects of morphometric traits, biosocial variables and their interaction on the cumulative probability of obtaining education beyond primary level.

Results

Of biosocial variables, family SEP was the most important determinant of educational attainment, followed by the sex, rural vs urban origin and the number of siblings. No significant interactions with morphometric traits were detected, i.e., within each category of SEP, rural vs urban origin and sex, taller children and those with larger heads and relatively narrower faces were more likely to proceed to secondary and/or tertiary education. The effect of height on education was independent of cranial volume, indicating that taller children did not obtain more educations because their brains were larger than those of shorter children; height per se was important.

Conclusions

Our main finding – that adjusting for other morphometric traits and biosocial variables, morphometric traits still robustly predicted educational attainment, is relevant for understanding the current patterns of evolution of human body size. Our findings suggest that fecundity selection acting on educational attainment could be partly responsible for the concurrent selection for smaller stature and cranial volume in women and opposite trends in men.

Thermodynamics and kinetics guided probe design for uniformly sensitive and specific DNA hybridization without optimization

Sensitive and specific DNA hybridization is essential for nucleic acid chemistry. Competitive composition of probe and blocker has been the most adopted probe design for its relatively high sensitivity and specificity. However, the sensitivity and specificity were inversely correlated over the length and concentration of the blocker strand, making the optimization process cumbersome. Herein, we construct a theoretical model for competitive DNA hybridization, which disclose that both the thermodynamics and kinetics contribute to the inverse correlation. Guided by this, we invent the 4-way Strand Exchange LEd Competitive DNA Testing (SELECT) system, which breaks up the inverse correlation. Using SELECT, we identified 16 hot-pot mutations in human genome under uniform conditions, without optimization at all. The specificities were all above 140. As a demonstration of the clinical practicability, we develop probe systems that detect mutations in human genomic DNA extracted from ovarian cancer patients with a detection limit of 0.1%.

Optimisation of nucleic acid probes and blocker strands can be laborious. Here the authors construct a theoretical model of competitive DNA hybridisation to design DNA probes for optimisation-free mutation detection.

Three Novel Loci for Infant Head Circumference Identified by a Joint Association Analysis

As an important trait at birth, infant head circumference (HC) is associated with a variety of intelligence- and mental-related conditions. Despite being dominated by genetics, the mechanism underlying the variation of HC is poorly understood. Aiming to uncover the genetic basis of HC, we performed a genome-wide joint association analysis by integrating the genome-wide association summary statistics of HC with that of its two related traits, birth length and birth weight, using a recently developed integrative method, multitrait analysis of genome-wide association (MTAG), and performed in silico replication in an independent sample of intracranial volume (N = 26,577). We then conducted a series of bioinformatic investigations on the identified loci. Combining the evidence from both the MTAG analysis and the in silico replication, we identified three novel loci at the genome-wide significance level (α = 5.0 × 10^-8): 3q23 [lead single nucleotide polymorphism (SNP) rs9846396, p _MTAG = 3.35 × 10^-8, p _replication = 0.01], 7p15.3 (rs12534093, p _MTAG = 2.00 × 10^-8, p _replication = 0.004), and 9q33.3 (rs7048271 p _MTAG = 9.23 × 10^-10, p _replication = 1.14 × 10^-4). Each of the three lead SNPs was associated with at least one of eight brain-related traits including intelligence and educational attainment. Credible risk variants, defined as those SNPs located within 500 kb of the lead SNP and with p values within two orders of magnitude of the lead SNP, were enriched in DNase I hypersensitive site region in brain. Nine candidate genes were prioritized at the three novel loci using multiple sources of information. Gene set enrichment analysis identified one associated pathway GO:0048009, which participates in the development of nervous system. Our findings provide useful insights into the genetic basis of HC and the relationship between brain growth and mental health.