The coexistence of copy number variations (CNVs) and single nucleotide polymorphisms (SNPs) at a locus can result in distorted calculations of the significance in associating SNPs to disease

Genome-wide association testing beyond SNPs

Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale.

The genetics of hyper IgE syndromes

Hyper IgE syndromes (HIES) form a rare group of primary immunodeficiency disorders (PIDs) distinguished by persistent skin abscesses, dermatitis, allergies, and infections, in addition to their characteristic high serum IgE levels. Autosomal dominant (AD) and autosomal recessive (AR) genetic defects have been reported in HIES. From a clinical perspective, AD-HIES cases generally exhibit several non-immunologic features, including connective tissue, dental and skeletal abnormalities, whilst AR-HIES conditions have a higher incidence of neurologic complications and cutaneous viral infections. Genetic defects associated with HIES lead to impaired immune signaling, affecting pathways crucial for immune cell development, function, and immune response to pathogens/allergens. As a result, HIES patients are predisposed to recurrent bacterial and/or fungal infections, as well as atopic allergic responses. In many cases, the exact biological mechanisms responsible for the variations observed in the clinical phenotypes between the two inherited forms of HIES are still unclear. In this review, we describe the genetic basis of HIES with a distinction between the AR-HIES and AD-HIES forms, to better comprehend the different underlying molecular mechanisms, a distinction which is imperative for the accurate diagnosis, management, and development of targeted therapies for HIES patients.

Redefining copy number variation and single-nucleotide polymorphism counting via novel concepts based on recent PCR enhancements

Human genes have numerous copy number variations (CNVs) and single-nucleotide polymorphisms (SNPs) that control most of the body's core functions. On average, 12-16 % of human genes have CNVs, and a single gene can have a few hundred to several thousand SNPs. Numerous genome-wide association studies (GWAS) have shown that CNVs and SNPs can coexist in certain genomic regions, amplifying their effects on gene expression and regulation and disease susceptibility. Researchers initially categorized CNVs and SNPs into two types: homozygous and heterozygous. However, copy numbers were soon found to have a much wider range, underscoring their significance in certain diseases and microbial interactions. Because of the significant impact of CNVs and SNPs, research groups worldwide have eagerly sought effective methods for detecting both simultaneously. Despite yielding some minor results, these simultaneous counting methods have failed to meet expectations, leaving researchers to measure CNVs and SNPs separately. To overcome these limitations, we developed a novel approach by combining primers designed using the STexS method with matching probes used in the STexS II method. This method successfully detected both CNVs and SNPs in CYP2A6 and CYP2A7 using a single quantitative polymerase chain reaction. Once properly adjusted based on the three core principles, this new method markedly improved the time, cost-effectiveness, and overall accuracy of determining an individual's genetic status. Further testing of 100 human genomic DNA samples enabled calculations of the overall frequency of the [T] and [G] alleles of the CYP2A6 -48T > G SNP within an East Asian population yielded results that were highly congruent with those in a National Institutes of Health (NIH) database. This novel method will redefine genetic profiling and provide a means to successfully predict genetic characteristics and enhance personalized medicine by pinpointing appropriate individualized treatments.

Exploring the Intersection of Schizophrenia, Machine Learning, and Genomics: Scoping Review

BACKGROUND

An increasing body of literature highlights the integration of machine learning with genomic data in psychiatry, particularly for complex mental health disorders such as schizophrenia. These advanced techniques offer promising potential for uncovering various facets of these disorders. A comprehensive review of the current applications of machine learning in conjunction with genomic data within this context can significantly enhance our understanding of the current state of research and its future directions.

OBJECTIVE

This study aims to conduct a systematic scoping review of the use of machine learning algorithms with genomic data in the field of schizophrenia.

METHODS

To conduct a systematic scoping review, a search was performed in the electronic databases MEDLINE, Web of Science, PsycNet (PsycINFO), and Google Scholar from 2013 to 2024. Studies at the intersection of schizophrenia, genomic data, and machine learning were evaluated.

RESULTS

The literature search identified 2437 eligible articles after removing duplicates. Following abstract screening, 143 full-text articles were assessed, and 121 were subsequently excluded. Therefore, 21 studies were thoroughly assessed. Various machine learning algorithms were used in the identified studies, with support vector machines being the most common. The studies notably used genomic data to predict schizophrenia, identify schizophrenia features, discover drugs, classify schizophrenia amongst other mental health disorders, and predict the quality of life of patients.

CONCLUSIONS

Several high-quality studies were identified. Yet, the application of machine learning with genomic data in the context of schizophrenia remains limited. Future research is essential to further evaluate the portability of these models and to explore their potential clinical applications.

A proteomics approach to study mouse long bones: examining baseline differences and mechanical loading-induced bone formation in young-adult and old mice

With aging, bone mass declines and the anabolic effects of skeletal loading diminish. While much research has focused on gene transcription, how bone ages and loses its mechanoresponsiveness at the protein level remains unclear. We developed a novel proteomics approach and performed a paired mass spectrometry and RNA-seq analysis on tibias from young-adult (5-month) and old (22-month) mice. We report the first correlation estimate between the bone proteome and transcriptome (Spearman ρ = 0.40), which is in line with other tissues but indicates that a relatively low amount of variation in protein levels is explained by the variation in transcript levels. Of 71 shared targets that differed with age, eight were associated with bone mineral density in previous GWAS, including understudied targets Asrgl1 and Timp2. We used complementary RNA in situ hybridization to confirm that Asrgl1 and Timp2 had reduced expression in osteoblasts/osteocytes in old bones. We also found evidence for reduced TGF-beta signaling with aging, in particular Tgfb2. Next, we defined proteomic changes following mechanical loading. At the protein level, bone differed more with age than with loading, and aged bone had fewer loading-induced changes. Overall, our findings underscore the need for complementary protein-level assays in skeletal biology research.

Joint models reveal genetic architecture of pubertal stage transitions and their association with BMI in admixed Chilean population

Early or late pubertal onset can lead to disease in adulthood, including cancer, obesity, type 2 diabetes, metabolic disorders, bone fractures, and psychopathologies. Thus, knowing the age at which puberty is attained is crucial as it can serve as a risk factor for future diseases. Pubertal development is divided into five stages of sexual maturation in boys and girls according to the standardized Tanner scale. We performed genome-wide association studies (GWAS) on the "Growth and Obesity Chilean Cohort Study" cohort composed of admixed children with mainly European and Native American ancestry. Using joint models that integrate time-to-event data with longitudinal trajectories of body mass index (BMI), we identified genetic variants associated with phenotypic transitions between pairs of Tanner stages. We identified $42$ novel significant associations, most of them in boys. The GWAS on Tanner $3\rightarrow 4$ transition in boys captured an association peak around the growth-related genes LARS2 and LIMD1 genes, the former of which causes ovarian dysfunction when mutated. The associated variants are expression and splicing Quantitative Trait Loci regulating gene expression and alternative splicing in multiple tissues. Further, higher individual Native American genetic ancestry proportions predicted a significantly earlier puberty onset in boys but not in girls. Finally, the joint models identified a longitudinal BMI parameter significantly associated with several Tanner stages' transitions, confirming the association of BMI with pubertal timing.

Genome-wide association study of osteoporosis identifies genetic risk and interactions with Dietary Approaches to Stop Hypertension diet and sugar-sweetened beverages in a Hispanic cohort of older adults

Osteoporosis (OP) and low bone mass can be debilitating and costly conditions if not acted on quickly. This disease is also difficult to diagnose as the symptoms develop unnoticed until fracture occurs. Therefore, gaining understanding of the genetic risk associated with these conditions could be beneficial for health-care professionals in early detection and prevention. The Boston Puerto Rican Osteoporosis (BPROS) study, an ancillary study to the Boston Puerto Rican Health Study (BPRHS), collected information regarding bone and bone health. All bone measurements were taken during regular BPROS visits using dual-energy X-ray absorptiometry. The OP was defined as T-score ≤ -2.5 (≥2.5 SDs below peak bone mass). Dietary variables were collected at the second wave of the BPRHS via a food frequency questionnaire. We conducted genome-wide associations with bone outcomes, including BMD and OP for 978 participants. We also examined the interactions with dietary quality on the relationships between genotype and bone outcomes. We further tested if candidate genetic variants described in previous GWAS on OP and BMD contribute to OP risk in this population. Four variants were associated with OP: rs114829316 (IQ motif containing J gene), rs76603051, rs12214684 (melanin-concentrating hormone receptor 2 gene), and rs77303493 (Ras and Rab interactor 2 gene), and 2 variants were associated with BMD of lumbar spine (rs11855618, cingulin-like 1 gene) and hip (rs73480593, NTRK2), reaching the genome-wide significance threshold of P ≤ 5E-08. In a gene-diet interaction analysis, we found that 1 SNP showed a significant interaction with the overall Dietary Approaches to Stop Hypertension (DASH) score, and 7 SNPs with sugar-sweetened beverages (SSBs), a major contributor to the DASH score. This study identifies new genetic markers related to OP and BMD in older Hispanic adults. Additionally, we uncovered unique genetic markers that interact with dietary quality, specifically SSBs, in relation to bone health. These findings may be useful to guide early detection and preventative care.

Genome-wide analysis to uncover how Pocillopora acuta survives the challenging intertidal environment

Characterisation of genomic variation among corals can help uncover variants underlying trait differences and contribute towards genotype prioritisation in coastal restoration projects. For example, there is growing interest in identifying resilient genotypes for transplantation, and to better understand the genetic processes that allow some individuals to survive in specific conditions better than others. The coral species Pocillopora acuta is known to survive in a wide range of habitats, from reefs artificial coastal defences, suggesting its potential use as a starter species for ecological engineering efforts involving coral transplantation onto intertidal seawalls. However, the intertidal section of coastal armour is a challenging environment for corals, with conditions during periods of emersion being particularly stressful. Here, we scanned the entire genome of P. acuta corals to identify the regions harbouring single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) that separate intertidal colonies (n = 18) from those found in subtidal areas (n = 21). Findings revealed 74,391 high quality SNPs distributed across 386 regions of the P. acuta genome. While the majority of the detected SNPs were in non-coding regions, 12% were identified in exons (i.e. coding regions). Functional SNPs that were significantly associated with intertidal colonies were found in overrepresented genomic regions linked to cellular homeostasis, metabolism, and signalling processes, which may represent local environmental adaptation in the intertidal. Interestingly, regions that exhibited CNVs were also associated with metabolic and signalling processes, suggesting P. acuta corals living in the intertidal have a high capacity to perform biological functions critical for survival in extreme environments.

Integrated DNA methylation analysis reveals a potential role for PTPRN2 in Marfan syndrome scoliosis

Background

Marfan syndrome (MFS) is a rare genetic disorder caused by mutations in the Fibrillin-1 gene (FBN1) with significant clinical features in the skeletal, cardiopulmonary, and ocular systems. To gain deeper insights into the contribution of epigenetics in the variability of phenotypes observed in MFS, we undertook the first analysis of integrating DNA methylation and gene expression profiles in whole blood from MFS and healthy controls (HCs).

Methods

The Illumina 850K (EPIC) DNA methylation array was used to detect DNA methylation changes on peripheral blood samples of seven patients with MFS and five HCs. Associations between methylation levels and clinical features of MFS were analyzed. Subsequently, we conducted an integrated analysis of the outcomes of the transcriptome data to analyze the correlation between differentially methylated positions (DMPs) and differentially expressed genes (DEGs) and explore the potential role of methylation-regulated DEGs (MeDEGs) in MFS scoliosis. The weighted gene co-expression network analysis was used to find gene modules with the highest correlation coefficient with target MeDEGs to annotate their functions in MFS.

Results

Our study identified 1253 DMPs annotated to 236 genes that were primarily associated with scoliosis, cardiomyopathy, and vital capacity. These conditions are typically associated with reduced lifespan in untreated MFS. We calculated correlations between DMPs and clinical features, such as cobb angle to evaluate scoliosis and FEV1% to assess pulmonary function. Notably, cg20223687 (PTPRN2) exhibited a positive correlation with cobb angle of scoliosis, potentially playing a role in ERKs inactivation.

Conclusions

Taken together, our systems-level approach sheds light on the contribution of epigenetics to MFS and offers a plausible explanation for the complex phenotypes that are linked to reduced lifespan in untreated MFS patients.

A mammalian-specific Alex3/Gαq protein complex regulates mitochondrial trafficking, dendritic complexity, and neuronal survival

Mitochondrial dynamics and trafficking are essential to provide the energy required for neurotransmission and neural activity. We investigated how G protein-coupled receptors (GPCRs) and G proteins control mitochondrial dynamics and trafficking. The activation of Gαq inhibited mitochondrial trafficking in neurons through a mechanism that was independent of the canonical downstream PLCβ pathway. Mitoproteome analysis revealed that Gαq interacted with the Eutherian-specific mitochondrial protein armadillo repeat-containing X-linked protein 3 (Alex3) and the Miro1/Trak2 complex, which acts as an adaptor for motor proteins involved in mitochondrial trafficking along dendrites and axons. By generating a CNS-specific Alex3 knockout mouse line, we demonstrated that Alex3 was required for the effects of Gαq on mitochondrial trafficking and dendritic growth in neurons. Alex3-deficient mice had altered amounts of ER stress response proteins, increased neuronal death, motor neuron loss, and severe motor deficits. These data revealed a mammalian-specific Alex3/Gαq mitochondrial complex, which enables control of mitochondrial trafficking and neuronal death by GPCRs.

Copy number variations and their effect on the plasma proteome

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases

Cardiovascular disease (CVD) is caused by a multitude of complex and largely heritable conditions. Identifying key genes and understanding their susceptibility to CVD in the human genome can assist in early diagnosis and personalized treatment of the relevant patients. Heart failure (HF) is among those CVD phenotypes that has a high rate of mortality. In this study, we investigated genes primarily associated with HF and other CVDs. Achieving the goals of this study, we built a cohort of thirty-five consented patients, and sequenced their serum-based samples. We have generated and processed whole genome sequence (WGS) data, and performed functional mutation, splice, variant distribution, and divergence analysis to understand the relationships between each mutation type and its impact. Our variant and prevalence analysis found FLNA, CST3, LGALS3, and HBA1 linked to many enrichment pathways. Functional mutation analysis uncovered ACE, MME, LGALS3, NR3C2, PIK3C2A, CALD1, TEK, and TRPV1 to be notable and potentially significant genes. We discovered intron, 5' Flank, 3' UTR, and 3' Flank mutations to be the most common among HF and other CVD genes. Missense mutations were less common among HF and other CVD genes but had more of a functional impact. We reported HBA1, FADD, NPPC, ADRB2, ADBR1, MYH6, and PLN to be consequential based on our divergence analysis.

ERBIN and phosphoglucomutase 3 deficiency

ERBIN and phosphoglucomutase 3 (PGM3) mutations both lead to rare primary atopic disorders characterized by allergic disease and connective tissue abnormalities, though each disorder has its own rather unique pattern of multisystem presentations. Pathway studies show how ERBIN mutations allow for enhanced TGFb signaling, and prevent STAT3 from negative-regulating TGFb signaling. This likely explains many elements of clinical overlap between disorders of STAT3 and TGFb signaling. The excessive TGFb signaling leading to increased IL-4 receptor expression also provides the rationale for precision-based therapy blocking the IL-4 receptor to treat the atopic disease. The mechanism by which PGM3 deficiency leads to atopic phenotypes is not well understood, nor is the broad variability in disease penetrance and expressivity, though preliminary studies suggest an overlap with IL-6 receptor signaling defects.

Maternal pre-pregnancy BMI, offspring epigenome-wide DNA methylation, and childhood obesity: findings from the Boston Birth Cohort

BACKGROUND

Maternal pre-pregnancy obesity is an established risk factor for childhood obesity. Investigating epigenetic alterations induced by maternal obesity during fetal development could gain mechanistic insight into the developmental origins of childhood obesity. While obesity disproportionately affects underrepresented racial and ethnic mothers and children in the USA, few studies investigated the role of prenatal epigenetic programming in intergenerational obesity of these high-risk populations.

METHODS

This study included 903 mother-child pairs from the Boston Birth Cohort, a predominantly urban, low-income minority birth cohort. Mother-infant dyads were enrolled at birth and the children were followed prospectively to age 18 years. Infinium Methylation EPIC BeadChip was used to measure epigenome-wide methylation level of cord blood. We performed an epigenome-wide association study of maternal pre-pregnancy body mass index (BMI) and cord blood DNA methylation (DNAm). To quantify the degree to which cord blood DNAm mediates the maternal BMI-childhood obesity, we further investigated whether maternal BMI-associated DNAm sites impact birthweight or childhood overweight or obesity (OWO) from age 1 to age 18 and performed corresponding mediation analyses.

RESULTS

The study sample contained 52.8% maternal pre-pregnancy OWO and 63.2% offspring OWO at age 1-18 years. Maternal BMI was associated with cord blood DNAm at 8 CpG sites (genome-wide false discovery rate [FDR] < 0.05). After accounting for the possible interplay of maternal BMI and smoking, 481 CpG sites were discovered for association with maternal BMI. Among them 123 CpGs were associated with childhood OWO, ranging from 42% decrease to 87% increase in OWO risk for each SD increase in DNAm. A total of 14 identified CpG sites showed a significant mediation effect on the maternal BMI-child OWO association (FDR < 0.05), with mediating proportion ranging from 3.99% to 25.21%. Several of these 14 CpGs were mapped to genes in association with energy balance and metabolism (AKAP7) and adulthood metabolic syndrome (CAMK2B).

CONCLUSIONS

This prospective birth cohort study in a high-risk yet understudied US population found that maternal pre-pregnancy OWO significantly altered DNAm in newborn cord blood and provided suggestive evidence of epigenetic involvement in the intergenerational risk of obesity.

Combined genome-wide association study of 136 quantitative ear morphology traits in multiple populations reveal 8 novel loci

Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology.

Functional characterization of human genomic variation linked to polygenic diseases

The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.

Pharmaco-Omics in Psoriasis: Paving the Way towards Personalized Medicine

The emergence of high-throughput approaches has had a profound impact on personalized medicine, evolving the identification of inheritable variation to trajectory analyses of transient states and paving the way for the unveiling of response biomarkers. The utilization of the multi-layered pharmaco-omics data, including genomics, transcriptomics, proteomics, and relevant biological information, has facilitated the identification of key molecular biomarkers that can predict the response to therapy, thereby optimizing treatment regiments and providing the framework for a tailored treatment plan. Despite the availability of multiple therapeutic options for chronic diseases, the highly heterogeneous clinical response hinders the alleviation of disease signals and exacerbates the annual burden and cost of hospitalization and drug regimens. This review aimed to examine the current state of the pharmaco-omic approaches performed in psoriasis, a common inflammatory disease of the skin. We sought to identify central studies that investigate the inter-individual variability and explore the underlying molecular mechanisms of drug response progression via biological profiling in psoriatic patients administered with the extended therapeutic armamentarium of psoriasis, incorporating conventional therapies, small molecules, as well as biological drugs that inhibit central pathogenic cytokines involved in the disease pathogenesis.

Osteoarthritis year in review: genetics, genomics and epigenetics

This "year in review" provides a summary of the research findings on the topic of genetics, genomics and epigenetics for osteoarthritis (OA) between Mar 2021-Apr 2022. A search routine of the literature in PubMed for the keyword, osteoarthritis, together with topics on genetics, genomics, epigenetics, polymorphism, DNA methylation, noncoding RNA, lncRNA, proteomics, and single cell RNA sequencing, returned key research articles and relevant reviews. Following filtering of duplicates across search routines, 695 unique research articles and 112 reviews were identified. We manually curated these articles and selected 90 as references for this review. However, we were unable to refer to all these articles, and only used selected articles to highlight key outcomes and trends. The trend in genetics is on the meta-analysis of existing cohorts with comparable genetic and phenotype characterisation of OA; in particular, clear definition of endophenotypes to enhance the genetic power. Further, many researchers are realizing the power of big data and multi-omics approaches to gain molecular insights for OA, and this has opened innovative approaches to include transcriptomics and epigenetics data as quantitative trait loci (QTLs). Given that most of the genetic loci for OA are not located within coding regions of genes, implying the impact is likely to be on gene regulation, epigenetics is a hot topic, and there is a surge in studies relating to the role of miRNA and long non-coding RNA on cartilage biology and pathology. The findings are exciting and new insights are provided in this review to summarize a year of research and the road map to capture all new innovations to achieve the desired goal in OA prevention and treatment.

Deep Learning-Based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer's Disease

The prognosis and treatment of patients suffering from Alzheimer's disease (AD) have been among the most important and challenging problems over the last few decades. To better understand the mechanism of AD, it is of great interest to identify genetic variants associated with brain atrophy. Commonly, in these analyses, neuroimaging features are extracted based on one of many possible brain atlases with FreeSurf and other popular software; this, however, may cause the loss of important information due to our incomplete knowledge about brain function embedded in these suboptimal atlases. To address the issue, we propose convolutional neural network (CNN) models applied to three-dimensional MRI data for the whole brain or multiple, divided brain regions to perform completely data-driven and automatic feature extraction. These image-derived features are then used as endophenotypes in genome-wide association studies (GWASs) to identify associated genetic variants. When we applied this method to ADNI data, we identified several associated SNPs that have been previously shown to be related to several neurodegenerative/mental disorders, such as AD, depression, and schizophrenia.

Haplotypic variants of COVID-19 related genes are associated with blood pressure and metabolites levels

The genetic association of coronavirus disease 2019 (COVID-19) with its complications has not been fully understood. This study aimed to identify variants and haplotypes of candidate genes implicated in COVID-19 related traits by combining the literature review and pathway analysis. To explore such genes, the protein-protein interactions and relevant pathways of COVID-19-associated genes were assessed. A number of variants on candidate genes were identified from Genome-wide association studies (GWASs) which were associated with COVID-19 related traits (p ˂ 10^-6 ). Haplotypic blocks were assessed using haplotypic structures among the 1000 Genomes Project (r²  ≥ 0.8, D' ≥ 0.8). Further functional analyses were performed on the selected variants. The results demonstrated that a group of variants in ACE and AGT genes were significantly correlated with COVID-19 related traits. Three haplotypes were identified to be involved in the blood metabolites levels and the development of blood pressure. Functional analyses revealed that most GWAS index variants were expression quantitative trait loci and had transcription factor binding sites, exonic splicing enhancers or silencer activities. Furthermore, the proxy haplotype variants, rs4316, rs4353, rs4359, and three variants, namely rs2493133, rs2478543, and rs5051, were associated with blood metabolite and systolic blood pressure, respectively. These variants exerted more regulatory effects compared with other GWAS variants. The present study indicates that the genetic variants and candidate haplotypes of COVID-19 related genes are associated with blood pressure and blood metabolites. However, further observational studies are warranted to confirm these results.

Genetic insights into smoking behaviours in 10,558 men of African ancestry from continental Africa and the UK

Smoking is a leading risk factor for many of the top ten causes of death worldwide. Of the 1.3 billion smokers globally, 80% live in low- and middle-income countries, where the number of deaths due to tobacco use is expected to double in the next decade according to the World Health Organization. Genetic studies have helped to identify biological pathways for smoking behaviours, but have mostly focussed on individuals of European ancestry or living in either North America or Europe. We performed a genome-wide association study of two smoking behaviour traits in 10,558 men of African ancestry living in five African countries and the UK. Eight independent variants were associated with either smoking initiation or cessation at P-value < 5 × 10-6, four being monomorphic or rare in European populations. Gene prioritisation strategy highlighted five genes, including SEMA6D, previously described as associated with several smoking behaviour traits. These results confirm the importance of analysing underrepresented populations in genetic epidemiology, and the urgent need for larger genomic studies to boost discovery power to better understand smoking behaviours, as well as many other traits.

Genetic Determinants of 25-Hydroxyvitamin D Concentrations and Their Relevance to Public Health

Twin studies suggest a considerable genetic contribution to the variability in 25-hydroxyvitamin D (25(OH)D) concentrations, reporting heritability estimates up to 80% in some studies. While genome-wide association studies (GWAS) suggest notably lower rates (13−16%), they have identified many independent variants that associate with serum 25(OH)D concentrations. These discoveries have provided some novel insight into the metabolic pathway, and in this review we outline findings from GWAS studies to date with a particular focus on 35 variants which have provided replicating evidence for an association with 25(OH)D across independent large-scale analyses. Some of the 25(OH)D associating variants are linked directly to the vitamin D metabolic pathway, while others may reflect differences in storage capacity, lipid metabolism, and pathways reflecting skin properties. By constructing a genetic score including these 25(OH)D associated variants we show that genetic differences in 25(OH)D concentrations persist across the seasons, and the odds of having low concentrations (<50 nmol/L) are about halved for individuals in the highest 20% of vitamin D genetic score compared to the lowest quintile, an impact which may have notable influences on retaining adequate levels. We also discuss recent studies on personalized approaches to vitamin D supplementation and show how Mendelian randomization studies can help inform public health strategies to reduce adverse health impacts of vitamin D deficiency.

Landscape of Secondary Findings in Chinese Population: A Practice of ACMG SF v3.0 List

Clinical exome sequencing (CES) has shown great utility in the diagnosis of Mendelian disorders. CES can unravel secondary findings (SFs) unrelated to the primary diagnosis but with potential health implications. The American College of Medical Genetics and Genomics (ACMG) has published a guideline for reporting secondary findings and recently updated an ACMG SF v3.0 list comprising 73 genes. Several studies have been performed to explore the prevalence of SFs. However, the data were limited in the Chinese population. In this study, we evaluated the genetic data of 2987 individuals from the Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) study group in accordance with the ACMG SF v3.0 list. The detected variants were evaluated using the ACMG classification guidelines, HGMD, and ClinVar database. Totally, 157 (157/2987, 5.3%) individuals had reportable variants within genes associated with cancer, cardiovascular, metabolic, and miscellaneous phenotypes. We identified 63 known pathogenic (KP) variants in 72 individuals (72/2987, 2.4%) and 96 expected pathogenic (EP) variants in 105 individuals (3.5%). Forty-five individuals carried SFs in v3.0 newly added genes, which accounted for 1.5% of our cohort. Our findings could contribute to existing knowledge of secondary findings in different ethnicities and indicate the necessity for clinicians to update the SFs gene list.

DNA Methylation Episignatures in Neurodevelopmental Disorders Associated with Large Structural Copy Number Variants: Clinical Implications

Large structural chromosomal deletions and duplications, referred to as copy number variants (CNVs), play a role in the pathogenesis of neurodevelopmental disorders (NDDs) through effects on gene dosage. This review focuses on our current understanding of genomic disorders that arise from large structural chromosome rearrangements in patients with NDDs, as well as difficulties in overlap of clinical presentation and molecular diagnosis. We discuss the implications of epigenetics, specifically DNA methylation (DNAm), in NDDs and genomic disorders, and consider the implications and clinical impact of copy number and genomic DNAm testing in patients with suspected genetic NDDs. We summarize evidence of global methylation episignatures in CNV-associated disorders that can be used in the diagnostic pathway and may provide insights into the molecular pathogenesis of genomic disorders. Finally, we discuss the potential for combining CNV and DNAm assessment into a single diagnostic assay.

Exploration of Potential Ewing Sarcoma Drugs from FDA-Approved Pharmaceuticals through Computational Drug Repositioning, Pharmacogenomics, Molecular Docking, and MD Simulation Studies

Novel drug development is a time-consuming process with relatively high debilitating costs. To overcome this problem, computational drug repositioning approaches are being used to predict the possible therapeutic scaffolds against different diseases. In the current study, computational drug repositioning approaches were employed to fetch the promising drugs from the pool of FDA-approved drugs against Ewing sarcoma. The binding interaction patterns and conformational behaviors of screened drugs within the active region of Ewing sarcoma protein (EWS) were confirmed through molecular docking profiles. Furthermore, pharmacogenomics analysis was employed to check the possible associations of selected drugs with Ewing sarcoma genes. Moreover, the stability behavior of selected docked complexes (drugs-EWS) was checked by molecular dynamics simulations. Taken together, astemizole, sulfinpyrazone, and pranlukast exhibited a result comparable to pazopanib and can be used as a possible therapeutic agent in the treatment of Ewing sarcoma.

Biology in balance: human diploid genome integrity, gene dosage, and genomic medicine

The path to completion of the functional annotation of the haploid human genome reference build, exploration of the clan genomics hypothesis, understanding human gene and genome functional biology, and gene genome and organismal evolution, is in reach.

Rare coding variants in DNA damage repair genes associated with timing of natural menopause

The age of menopause is associated with fertility and disease risk, and its genetic control is of great interest. We use whole-exome sequences from 132,370 women in the UK Biobank to test for associations between rare damaging variants and age at natural menopause. Rare damaging variants in five genes are significantly associated with menopause: CHEK2 (p = 3.3 × 10⁻⁵¹), DCLRE1A (p = 8.4 × 10⁻¹³), and HELB (p = 5.7 × 10⁻⁷) with later menopause and TOP3A (p = 7.6 × 10⁻⁸) and CLPB (p = 8.1 × 10⁻⁷) with earlier menopause. Two additional genes are suggestive: RAD54L (p = 2.4 × 10⁻⁶) with later menopause and HROB (p = 2.9 × 10⁻⁶) with earlier menopause. In a follow-up analysis of repeated questionnaires in women who were initially premenopausal, CHEK2, TOP3A, and RAD54L genotypes are associated with subsequent menopause. Consistent with previous genome-wide association studies (GWASs), six of the seven genes are involved in the DNA damage repair pathway. Phenome-wide scans across 398,569 men and women revealed that in addition to known associations with cancers and blood cell counts, rare variants in CHEK2 are also associated with increased risk for uterine fibroids, polycystic ovary syndrome, and prostate hypertrophy; these associations are not shared with higher-penetrance breast cancer genes. Causal mediation analysis suggests that approximately 8% of the breast cancer risk conferred by CHEK2 pathogenic variants after menopause is mediated through delayed menopause.

Rare catastrophes and evolutionary legacies: human germline gene variants in MLKL and the necroptosis signalling pathway

Programmed cell death has long been characterised as a key player in the development of human disease. Necroptosis is a lytic form of programmed cell death that is universally mediated by the effector protein mixed lineage kinase domain-like (MLKL), a pseudokinase. MLKL's activating kinase, receptor interacting protein kinase 3 (RIPK3), is itself activated within context specific scaffolds of receptor interacting protein kinase 1 (RIPK1), Z-DNA Binding Protein-1 (ZBP1) or TIR domain-containing adaptor inducing interferon-β (TRIF). These core necroptosis modulating proteins have been comprehensively revealed as potent drivers and suppressors of disease in inbred mouse strains. However, their roles in human disease within the 'real world' of diverse genetic backgrounds, natural infection and environmental challenges remains less well understood. Over 20 unique disease-associated human germline gene variants in this core necroptotic machinery have been reported in the literature and human clinico-genetics databases like ClinVar to date. In this review, we provide an overview of these human gene variants, with an emphasis on those encoding MLKL. These experiments of nature have the potential to not only enrich our understanding of the basic biology of necroptosis, but offer important population level insights into which clinical indications stand to benefit most from necroptosis-targeted drugs.

COVID-19 Pharmacotherapy: Drug Development, Repurposing of Drugs, and the Role of Pharmacogenomics

The SARS-CoV-2 virus has been the subject of intense pharmacological research. Various pharmacotherapeutic approaches including antiviral and immunotherapy are being explored. A pandemic, however, cannot depend on the development of new drugs; the time required for conventional drug discovery and development is far too lengthy. As such, repurposing drugs is being used as a viable approach for identifying pharmacological agents for COVID-19 infections. Evaluation of repurposed drug candidates with pharmacogenomic analysis is being used to identify near-term pharmacological remedies for COVID-19.

A genome-wide association study of a rage-related misophonia symptom and the genetic link with audiological traits, psychiatric disorders, and personality

Introduction

People with misophonia experience strong negative emotional responses to sounds and associated stimuli-mostly human produced-to an extent that it may cause impairment in social functioning. The exact nature of the disorder remains a matter of ongoing research and debate. Here, we investigated the genetic etiology of misophonia to understand contributing genetic factors and shed light on individual differences in characteristics that are related to the disorder.

Methods

For misophonia, we used an unpublished genome-wide association study (GWAS) from genetic service provider 23andMe, Inc., on a self-report item probing a single common misophonic symptom: the occurrence of rage when others produce eating sounds. First, we used gene-based and functional annotation analyses to explore neurobiological determinants of the rage-related misophonia symptom. Next, we calculated genetic correlations (r _G) of this rage-related misophonia symptom GWAS with a wide range of traits and disorders from audiology (tinnitus, hearing performance, and hearing trauma), psychiatry, neurology, and personality traits.

Results

The rage-related misophonia symptom was significantly correlated with tinnitus, major depression disorder (MDD), post-traumatic stress disorder (PTSD), and generalized anxiety disorder (GAD; 0.12 < r _G < 0.22). Stronger genetic correlations (0.21 < r _G < 0.42) were observed for two clusters of personality traits: a guilt/neuroticism and an irritability/sensitivity cluster. Our results showed no genetic correlation with attention deficit and hyperactivity disorder, obsessive-compulsive disorder, and psychotic disorders. A negative correlation with autism spectrum disorder (ASD) was found, which may be surprising given the previously reported comorbidities and the sensory sensitivity reported in ASD. Clustering algorithms showed that rage-related misophonia consistently clustered with MDD, generalized anxiety, PTSD, and related personality traits.

Discussion

We conclude that-based on the genetics of a common misophonia symptom-misophonia most strongly clusters with psychiatric disorders and a personality profile consistent with anxiety and PTSD.

An Integrative Co-localization (INCO) Analysis for SNV and CNV Genomic Features With an Application to Taiwan Biobank Data

Genomic studies have been a major approach to elucidating disease etiology and to exploring potential targets for treatments of many complex diseases. Statistical analyses in these studies often face the challenges of multiplicity, weak signals, and the nature of dependence among genetic markers. This situation becomes even more complicated when multi-omics data are available. To integrate the data from different platforms, various integrative analyses have been adopted, ranging from the direct union or intersection operation on sets derived from different single-platform analysis to complex hierarchical multi-level models. The former ignores the biological relationship between molecules while the latter can be hard to interpret. We propose in this study an integrative approach that combines both single nucleotide variants (SNVs) and copy number variations (CNVs) in the same genomic unit to co-localize the concurrent effect and to deal with the sparsity due to rare variants. This approach is illustrated with simulation studies to evaluate its performance and is applied to low-density lipoprotein cholesterol and triglyceride measurements from Taiwan Biobank. The results show that the proposed method can more effectively detect the collective effect from both SNVs and CNVs compared to traditional methods. For the biobank analysis, the identified genetic regions including the gene VNN2 could be novel and deserve further investigation.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Quantitative neurogenetics: applications in understanding disease

Neurodevelopmental and neurodegenerative disorders (NNDs) are a group of conditions with a broad range of core and co-morbidities, associated with dysfunction of the central nervous system. Improvements in high throughput sequencing have led to the detection of putative risk genetic loci for NNDs, however, quantitative neurogenetic approaches need to be further developed in order to establish causality and underlying molecular genetic mechanisms of pathogenesis. Here, we discuss an approach for prioritizing the contribution of genetic risk loci to complex-NND pathogenesis by estimating the possible impacts of these loci on gene regulation. Furthermore, we highlight the use of a tissue-specificity gene expression index and the application of artificial intelligence (AI) to improve the interpretation of the role of genetic risk elements in NND pathogenesis. Given that NND symptoms are associated with brain dysfunction, risk loci with direct, causative actions would comprise genes with essential functions in neural cells that are highly expressed in the brain. Indeed, NND risk genes implicated in brain dysfunction are disproportionately enriched in the brain compared with other tissues, which we refer to as brain-specific expressed genes. In addition, the tissue-specificity gene expression index can be used as a handle to identify non-brain contexts that are involved in NND pathogenesis. Lastly, we discuss how using an AI approach provides the opportunity to integrate the biological impacts of risk loci to identify those putative combinations of causative relationships through which genetic factors contribute to NND pathogenesis.

Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy

Lung cancer is one of the most prevalent human cancers, and single-cell RNA sequencing (scRNA-seq) has been widely used to study human lung cancer at the cellular, genetic, and molecular level. Even though there are published reviews, which summarized the applications of scRNA-seq in human cancers like breast cancer, there is lack of a comprehensive review, which could effectively highlight the broad use of scRNA-seq in studying lung cancer. This review, therefore, was aimed to summarize the various applications of scRNA-seq in human lung cancer research based on the findings from different published in vitro, in vivo, and clinical studies. The review would first briefly outline the concept and principle of scRNA-seq, followed by the discussion on the applications of scRNA-seq in studying human lung cancer. Finally, the challenges faced when using scRNA-seq to study human lung cancer would be discussed, and the potential applications and challenges of scRNA-seq to facilitate the development of personalized cancer therapy in the future would be explored.

A QTL for conformation of back and croup influences lateral gait quality in Icelandic horses

BACKGROUND

The back plays a vital role in horse locomotion, where the spine functions as a spring during the stride cycle. A complex interaction between the spine and the muscles of the back contribute to locomotion soundness, gait ability, and performance of riding and racehorses. Conformation is commonly used to select horses for breeding and performance in multiple horse breeds, where the back and croup conformation plays a significant role. The conformation of back and croup plays an important role on riding ability in Icelandic horses. However, the genes behind this trait are still unknown. Therefore, the aim of this study was to identify genomic regions associated with conformation of back and croup in Icelandic horses and to investigate their effects on riding ability. One hundred seventy-seven assessed Icelandic horses were included in the study. A genome-wide association analysis was performed using the 670 K+ Axiom Equine Genotyping Array, and the effects of different haplotypes in the top associated region were estimated for riding ability and additional conformation traits assessed during breeding field tests.

RESULTS

A suggestive quantitative trait loci (QTL) for the score of back and croup was detected on Equus caballus (ECA) 22 (p-value = 2.67 × 10- 7). Haplotype analysis revealed two opposite haplotypes, which resulted in higher and lower scores of the back and croup, respectively (p-value < 0.001). Horses with the favorable haplotype were more inclined to have a well-balanced backline with an uphill conformation and had, on average, higher scores for the lateral gaits tölt (p-value = 0.02) and pace (p-value = 0.004). This genomic region harbors three genes: C20orf85, ANKRD60 and LOC100056167. ANKRD60 is associated with body height in humans. C20orf85 and ANKRD60 are potentially linked to adolescent idiopathic scoliosis in humans.

CONCLUSIONS

Our results show that the detected QTL for conformation of back and croup is of importance for quality of lateral gaits in Icelandic horses. These findings could result in a genetic test to aid in the selection of breeding horses, thus they are of major interest for horse breeders. The results may also offer a gateway to comparative functional genomics by potentially linking both motor laterality and back inclination in horses with scoliosis in humans.

Research progress on the etiology and pathogenesis of adolescent idiopathic scoliosis

Etiology of adolescent idiopathic scoliosis (AIS), a complicated three-dimensional spinal deformity with early-onset, receives continuous attention but remains unclear. To gain an insight into AIS pathogenesis, this review searched PubMed database up to June 2019, using key words or medical subject headings terms including "adolescent idiopathic scoliosis," "scoliosis," "pathogenesis," "etiology," "genetics," "mesenchymal stem cells," and their combinations, summarized existing literatures and categorized the theories or hypothesis into nine aspects. These aspects include bone marrow mesenchymal stem cell studies, genetic studies, tissue analysis, spine biomechanics measurements, neurologic analysis, hormone studies, biochemical analysis, environmental factor analysis, and lifestyle explorations. These categories could be a guidance for further etiology or treatment researches to gain inspiration.

From genetics to epigenetics to unravel the etiology of adolescent idiopathic scoliosis

Scoliosis is defined as the three-dimensional (3D) structural deformity of the spine with a radiological lateral Cobb angle (a measure of spinal curvature) of ≥10° that can be caused by congenital, developmental or degenerative problems. However, those cases whose etiology is still unknown, and affect healthy children and adolescents during growth, are the commonest form of spinal deformity, known as adolescent idiopathic scoliosis (AIS). In AIS management, early diagnosis and the accurate prediction of curve progression are most important because they can decrease negative long-term effects of AIS treatment, such as unnecessary bracing, frequent exposure to radiation, as well as saving the high costs of AIS treatment. Despite efforts made to identify a method or technique capable of predicting AIS progression, this challenge still remains unresolved. Genetics and epigenetics, and the application of machine learning and artificial intelligence technologies, open up new avenues to not only clarify AIS etiology, but to also identify potential biomarkers that can substantially improve the clinical management of these patients. This review presents the most relevant biomarkers to help explain the etiopathogenesis of AIS and provide new potential biomarkers to be validated in large clinical trials so they can be finally implemented into clinical settings.

Phenotypic and genetic spectrum of isolated macrodactyly: somatic mosaicism of PIK3CA and AKT1 oncogenic variants

BACKGROUND

Isolated macrodactyly is a severe congenital hand anomaly with functional and physiological impact. Known causative genes include PIK3CA, AKT1 and PTEN. The aim of this study is to gain insights into the genetics basis of isolated macrodactyly.

RESULTS

We enrolled 24 patients with isolated macrodactyly. Four of them were diagnosed with Proteus syndrome based on skin presentations characteristic to this disease. Targeted next-generation sequencing was performed using patients' blood and affected tissues. Overall, 20 patients carry mosaic PIK3CA pathogenic variants, i.e. p.His1047Arg (N = 7), p.Glu542Lys (N = 6), p.Glu545Lys (N = 2), p.His1047Leu (N = 2), p.Glu453Lys (N = 1), p.Gln546Lys (N = 1) and p.His1047Tyr (N = 1). Four patients who met the diagnostic criteria of Proteus syndrome carry mosaic AKT1 p.Glu17Lys variant. Variant allele frequencies of these mosaic variants obtained through next-generation sequencing range from 10 to 33%. In genotype-phenotype correlation analysis of patients with PIK3CA variant, we found that patients with the macrodactyly of the lower limbs tend to carry PIK3CA variants located in the helical domain (P = 0.005).

CONCLUSIONS

Mosaic PIK3CA and AKT1 variants can be found in all of our samples with isolated macrodactyly. Insights into phenotypic and genetic spectrum of isolated macrodactyly may be helpful in perusing a more precise and effective management of isolated macrodactyly.

A trans-eQTL network regulates osteoclast multinucleation and bone mass

Functional characterisation of cell-type-specific regulatory networks is key to establish a causal link between genetic variation and phenotype. The osteoclast offers a unique model for interrogating the contribution of co-regulated genes to in vivo phenotype as its multinucleation and resorption activities determine quantifiable skeletal traits. Here we took advantage of a trans-regulated gene network (MMnet, macrophage multinucleation network) which we found to be significantly enriched for GWAS variants associated with bone-related phenotypes. We found that the network hub gene Bcat1 and seven other co-regulated MMnet genes out of 13, regulate bone function. Specifically, global (Pik3cb^-/-, Atp8b2^+/-, Igsf8^-/-, Eml1^-/-, Appl2^-/-, Deptor^-/-) and myeloid-specific Slc40a1 knockout mice displayed abnormal bone phenotypes. We report opposing effects of MMnet genes on bone mass in mice and osteoclast multinucleation/resorption in humans with strong correlation between the two. These results identify MMnet as a functionally conserved network that regulates osteoclast multinucleation and bone mass.

Identification of 5 Gene Signatures in Survival Prediction for Patients with Lung Squamous Cell Carcinoma Based on Integrated Multiomics Data Analysis

Background

Lung squamous cell carcinoma (LSCC) is a frequently diagnosed cancer worldwide, and it has a poor prognosis. The current study is aimed at developing the prediction of LSCC prognosis by integrating multiomics data including transcriptome, copy number variation data, and mutation data analysis, so as to predict patients' survival and discover new therapeutic targets.

Methods

RNASeq, SNP, CNV data, and LSCC patients' clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA), and the samples were randomly divided into two groups, namely, the training set and the validation set. In the training set, the genes related to prognosis and those with different copy numbers or with different SNPs were integrated to extract features using random forests, and finally, robust biomarkers were screened. In addition, a gene-related prognostic model was established and further verified in the test set and GEO validation set.

Results

We obtained a total of 804 prognostic-related genes and 535 copy amplification genes, 621 copy deletions genes, and 388 significantly mutated genes in genomic variants; noticeably, these genomic variant genes were found closely related to tumor development. A total of 51 candidate genes were obtained by integrating genomic variants and prognostic genes, and 5 characteristic genes (HIST1H2BH, SERPIND1, COL22A1, LCE3C, and ADAMTS17) were screened through random forest feature selection; we found that many of those genes had been reported to be related to LSCC progression. Cox regression analysis was performed to establish 5-gene signature that could serve as an independent prognostic factor for LSCC patients and can stratify risk samples in training set, test set, and external validation set (p < 0.01), and the 5-year survival areas under the curve (AUC) of both training set and validation set were > 0.67.

Conclusion

In the current study, 5 gene signatures were constructed as novel prognostic markers to predict the survival of LSCC patients. The present findings provide new diagnostic and prognostic biomarkers and therapeutic targets for LSCC treatment.

Human and mouse studies establish TBX6 in Mendelian CAKUT and as a potential driver of kidney defects associated with the 16p11.2 microdeletion syndrome

Congenital anomalies of the kidney and urinary tract (CAKUTs) are the most common cause of chronic kidney disease in children. Human 16p11.2 deletions have been associated with CAKUT, but the responsible molecular mechanism remains to be illuminated. To explore this, we investigated 102 carriers of 16p11.2 deletion from multi-center cohorts, among which we retrospectively ascertained kidney morphologic and functional data from 37 individuals (12 Chinese and 25 Caucasian/Hispanic). Significantly higher CAKUT rates were observed in 16p11.2 deletion carriers (about 25% in Chinese and 16% in Caucasian/Hispanic) than those found in the non-clinically ascertained general populations (about 1/1000 found at autopsy). Furthermore, we identified seven additional individuals with heterozygous loss-of-function variants in TBX6, a gene that maps to the 16p11.2 region. Four of these seven cases showed obvious CAKUT. To further investigate the role of TBX6 in kidney development, we engineered mice with mutated Tbx6 alleles. The Tbx6 heterozygous null (i.e., loss-of-function) mutant (Tbx6^+/‒) resulted in 13% solitary kidneys. Remarkably, this incidence increased to 29% in a compound heterozygous model (Tbx6^mh/‒) that reduced Tbx6 gene dosage to below haploinsufficiency, by combining the null allele with a novel mild hypomorphic allele (mh). Renal hypoplasia was also frequently observed in these Tbx6-mutated mouse models. Thus, our findings in patients and mice establish TBX6 as a novel gene involved in CAKUT and its gene dosage insufficiency as a potential driver for kidney defects observed in the 16p11.2 microdeletion syndrome.

Monocarboxylate Transporters (SLC16): Function, Regulation, and Role in Health and Disease

The solute carrier family 16 (SLC16) is comprised of 14 members of the monocarboxylate transporter (MCT) family that play an essential role in the transport of important cell nutrients and for cellular metabolism and pH regulation. MCTs 1-4 have been extensively studied and are involved in the proton-dependent transport of L-lactate, pyruvate, short-chain fatty acids, and monocarboxylate drugs in a wide variety of tissues. MCTs 1 and 4 are overexpressed in a number of cancers, and current investigations have focused on transporter inhibition as a novel therapeutic strategy in cancers. MCT1 has also been used in strategies aimed at enhancing drug absorption due to its high expression in the intestine. Other MCT isoforms are less well characterized, but ongoing studies indicate that MCT6 transports xenobiotics such as bumetanide, nateglinide, and probenecid, whereas MCT7 has been characterized as a transporter of ketone bodies. MCT8 and MCT10 transport thyroid hormones, and recently, MCT9 has been characterized as a carnitine efflux transporter and MCT12 as a creatine transporter. Expressed at the blood brain barrier, MCT8 mutations have been associated with an X-linked intellectual disability, known as Allan-Herndon-Dudley syndrome. Many MCT isoforms are associated with hormone, lipid, and glucose homeostasis, and recent research has focused on their potential roles in disease, with MCTs representing promising novel therapeutic targets. This review will provide a summary of the current literature focusing on the characterization, function, and regulation of the MCT family isoforms and on their roles in drug disposition and in health and disease. SIGNIFICANCE STATEMENT: The 14-member solute carrier family 16 of monocarboxylate transporters (MCTs) plays a fundamental role in maintaining intracellular concentrations of a broad range of important endogenous molecules in health and disease. MCTs 1, 2, and 4 (L-lactate transporters) are overexpressed in cancers and represent a novel therapeutic target in cancer. Recent studies have highlighted the importance of MCTs in glucose, lipid, and hormone homeostasis, including MCT8 in thyroid hormone brain uptake, MCT12 in carnitine transport, and MCT11 in type 2 diabetes.

Biological and practical implications of genome-wide association study of schizophrenia using Bayesian variable selection

Genome-wide association studies (GWAS) have identified over 100 loci associated with schizophrenia. Most of these studies test genetic variants for association one at a time. In this study, we performed GWAS of the molecular genetics of schizophrenia (MGS) dataset with 5334 subjects using multivariate Bayesian variable selection (BVS) method Posterior Inference via Model Averaging and Subset Selection (piMASS) and compared our results with the previous univariate analysis of the MGS dataset. We showed that piMASS can improve the power of detecting schizophrenia-associated SNPs, potentially leading to new discoveries from existing data without increasing the sample size. We tested SNPs in groups to allow for local additive effects and used permutation test to determine statistical significance in order to compare our results with univariate method. The previous univariate analysis of the MGS dataset revealed no genome-wide significant loci. Using the same dataset, we identified a single region that exceeded the genome-wide significance. The result was replicated using an independent Swedish Schizophrenia Case-Control Study (SSCCS) dataset. Based on the SZGR 2.0 database we found 63 SNPs from the best performing regions that are mapped to 27 genes known to be associated with schizophrenia. Overall, we demonstrated that piMASS could discover association signals that otherwise would need a much larger sample size. Our study has important implication that reanalyzing published datasets with BVS methods like piMASS might have more power to discover new risk variants for many diseases without new sample collection, ascertainment, and genotyping.

A Genocentric Approach to Discovery of Mendelian Disorders

The advent of inexpensive, clinical exome sequencing (ES) has led to the accumulation of genetic data from thousands of samples from individuals affected with a wide range of diseases, but for whom the underlying genetic and molecular etiology of their clinical phenotype remains unknown. In many cases, detailed phenotypes are unavailable or poorly recorded and there is little family history to guide study. To accelerate discovery, we integrated ES data from 18,696 individuals referred for suspected Mendelian disease, together with relatives, in an Apache Hadoop data lake (Hadoop Architecture Lake of Exomes [HARLEE]) and implemented a genocentric analysis that rapidly identified 154 genes harboring variants suspected to cause Mendelian disorders. The approach did not rely on case-specific phenotypic classifications but was driven by optimization of gene- and variant-level filter parameters utilizing historical Mendelian disease-gene association discovery data. Variants in 19 of the 154 candidate genes were subsequently reported as causative of a Mendelian trait and additional data support the association of all other candidate genes with disease endpoints.

Mitochondrial chaperone, TRAP1 as a potential pharmacological target to combat cancer metabolism

The stress response forms the most ancient defense system in living cells. Heat shock proteins (Hsps) are highly conserved across species and play major roles in mounting the stress response. The emerging information now suggests that Hsp90 family of chaperones display additional cellular roles contributing to diseases like cancer. For this reason, pharmacological targeting of Hsp90 has emerged as a novel antitumor strategy. However, its mitochondrial homologue TRAP1 has not been implicated in cancer with conclusive mechanistic insights. Since understanding the mutational spectrum of cancer cells indicates the outcome of the disease as well as treatment response, we examined mutational spectrum of TRAP1. Our in silico analyses of TRAP1 SNPs and CNVs correlated with the aggressive cancer phenotypes, and are found to be predominant over Hsp90 itself. The increased CNVs have been correlated with increased expression of TRAP1 in metastatic cancer cells, increased ATP production, and decreased oxygen consumption rate of mitochondria. Examining TRAP1 knockdown as well as over expression in metastatic cancer cells furthered our understanding that TRAP1 likely to facilitate the altered energy metabolism in the functional compromise of mitochondrial OXPHOS. Interestingly, the increased ATP levels in the TRAP1 background are found to be independent of glucose oxidation. Our results suggest TRAP1 role in triggering the alternate energy metabolism in cancer cells. Since targeting tumor metabolism is considered as an alternate strategy to combat cancer, we propose pharmacological targeting of TRAP1 to target alternate energy metabolism.

TBX6 missense variants expand the mutational spectrum in a non-Mendelian inheritance disease

Congenital scoliosis (CS) is a birth defect with variable clinical and anatomical manifestations due to spinal malformation. The genetic etiology underlying about 10% of CS cases in the Chinese population is compound inheritance by which the gene dosage is reduced below that of haploinsufficiency. In this genetic model, the trait manifests as a result of the combined effect of a rare variant and common pathogenic variant allele at a locus. From exome sequencing (ES) data of 523 patients in Asia and two patients in Texas, we identified six TBX6 gene-disruptive variants from 11 unrelated CS patients via ES and in vitro functional testing. The in trans mild hypomorphic allele was identified in 10 of the 11 subjects; as anticipated these 10 shared a similar spinal deformity of hemivertebrae. The remaining case has a homozygous variant in TBX6 (c.418C>T) and presents a more severe spinal deformity phenotype. We found decreased transcriptional activity and abnormal cellular localization as the molecular mechanisms for TBX6 missense loss-of-function alleles. Expanding the mutational spectrum of TBX6 pathogenic alleles enabled an increased molecular diagnostic detection rate, provided further evidence for the gene dosage-dependent genetic model underlying CS, and refined clinical classification.

TBX6 compound inheritance leads to congenital vertebral malformations in humans and mice

Congenital vertebral malformations (CVMs) are associated with human TBX6 compound inheritance that combines a rare null allele and a common hypomorphic allele at the TBX6 locus. Our previous in vitro evidence suggested that this compound inheritance resulted in a TBX6 gene dosage of less than haploinsufficiency (i.e. <50%) as a potential mechanism of TBX6-associated CVMs. To further investigate this pathogenetic model, we ascertained and collected 108 Chinese CVM cases and found that 10 (9.3%) of them carried TBX6 null mutations in combination with common hypomorphic variants at the second TBX6 allele. For in vivo functional verification and genetic analysis of TBX6 compound inheritance, we generated both null and hypomorphic mutations in mouse Tbx6 using the CRISPR-Cas9 method. These Tbx6 mutants are not identical to the patient variants at the DNA sequence level, but instead functionally mimic disease-associated TBX6 variants. Intriguingly, as anticipated by the compound inheritance model, a high penetrance of CVM phenotype was only observed in the mice with combined null and hypomorphic alleles of Tbx6. These findings are consistent with our experimental observations in humans and supported the dosage effect of TBX6 in CVM etiology. In conclusion, our findings in the newly collected human CVM subjects and Tbx6 mouse models consistently support the contention that TBX6 compound inheritance causes CVMs, potentially via a gene dosage-dependent mechanism. Furthermore, mouse Tbx6 mutants mimicking human CVM-associated variants will be useful models for further mechanistic investigations of CVM pathogenesis in the cases associated with TBX6.

The coexistence of a novel WNK1 variant and a copy number variation causes hereditary sensory and autonomic neuropathy type IIA

Background

Hereditary sensory and autonomic neuropathy (HSAN) type II is a group of extremely rare autosomal recessive neurological disorders with heterogeneous clinical and genetic characteristics.

Methods

We performed high-depth next-generation targeted sequencing using a custom-ordered “HSAN” panel, covering WNK1, NTRK1, NGF, SPTLC1 and IKBKAP genes, to identify pathogenic variants of the proband as well as the family members. We also performed whole exome sequencing to further investigate the potential occurrence of additional pathogenic variants in genes that were not covered by the “HSAN” panel. Quantitative real-time PCR was used to identify pathogenic copy number variations (CNVs) and to analyze the mRNA level of WNK1 gene of the family. Western blot analysis was performed to evaluate the WNK1 protein expression level.

Results

After sequencing, a novel nonsense variant (c.2747 T > G, p.Leu916Ter) in exon 9 of WNK1 gene was identified in two patients (hemizygous) and their mother (heterozygous). This variant is absent in all public databases as well as in 600 Han Chinese healthy controls. The region of this variant is evolutionary highly conserved. Furthermore, by quantitative real-time PCR using DNA of the pedigree, we revealed a large deletion containing the whole WNK1 gene in two patients. The WNK1 expression levels of the patients were significantly reduced.

Conclusions

Our study firstly revealed that the coexistence of a novel WNK1 nonsense variant and a CNV resulted in HSAN type IIA in a Han Chinese family.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0828-5) contains supplementary material, which is available to authorized users.

Centromeric Satellite DNAs: Hidden Sequence Variation in the Human Population

The central goal of medical genomics is to understand the inherited basis of sequence variation that underlies human physiology, evolution, and disease. Functional association studies currently ignore millions of bases that span each centromeric region and acrocentric short arm. These regions are enriched in long arrays of tandem repeats, or satellite DNAs, that are known to vary extensively in copy number and repeat structure in the human population. Satellite sequence variation in the human genome is often so large that it is detected cytogenetically, yet due to the lack of a reference assembly and informatics tools to measure this variability, contemporary high-resolution disease association studies are unable to detect causal variants in these regions. Nevertheless, recently uncovered associations between satellite DNA variation and human disease support that these regions present a substantial and biologically important fraction of human sequence variation. Therefore, there is a pressing and unmet need to detect and incorporate this uncharacterized sequence variation into broad studies of human evolution and medical genomics. Here I discuss the current knowledge of satellite DNA variation in the human genome, focusing on centromeric satellites and their potential implications for disease.