Abstract: A primary goal of human genetics is to identify DNA sequence variants that influence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition.

Abstract: Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has now been confirmed worldwide. Yet, COVID-19 is strangely and tragically selective. Morbidity and mortality due to COVID19 rise dramatically with age and co-existing health conditions, including cancer and cardiovascular diseases. Human genetic factors may contribute to the extremely high transmissibility of SARS-CoV-2 and to the relentlessly progressive disease observed in a small but significant proportion of infected individuals, but these factors are largely unknown. In this study, we investigated genetic susceptibility to COVID-19 by examining DNA polymorphisms in ACE2 and TMPRSS2 (two key host factors of SARS-CoV-2) from ~ 81,000 human genomes. We found unique genetic susceptibility across different populations in ACE2 and TMPRSS2. Specifically, ACE2 polymorphisms were found to be associated with cardiovascular and pulmonary conditions by altering the angiotensinogen-ACE2 interactions, such as p.Arg514Gly in the African/African-American population. Unique but prevalent polymorphisms (including p.Val160Met (rs12329760), an expression quantitative trait locus (eQTL)) in TMPRSS2, offer potential explanations for differential genetic susceptibility to COVID-19 as well as for risk factors, including those with cancer and the high-risk group of male patients. We further discussed that polymorphisms in ACE2 or TMPRSS2 could guide effective treatments (i.e., hydroxychloroquine and camostat) for COVID-19. This study suggested that ACE2 or TMPRSS2 DNA polymorphisms were likely associated with genetic susceptibility of COVID-19, which calls for a human genetics initiative for fighting the COVID-19 pandemic.

Abstract: Mitochondria are essential cellular organelles that play critical roles in cancer. Here, as part of the International Cancer Genome Consortium/The Cancer Genome Atlas Pan-Cancer Analysis of Whole Genomes Consortium, which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumor types, we performed a multidimensional, integrated characterization of mitochondrial genomes and related RNA sequencing data. Our analysis presents the most definitive mutational landscape of mitochondrial genomes and identifies several hypermutated cases. Truncating mutations are markedly enriched in kidney, colorectal and thyroid cancers, suggesting oncogenic effects with the activation of signaling pathways. We find frequent somatic nuclear transfers of mitochondrial DNA, some of which disrupt therapeutic target genes. Mitochondrial copy number varies greatly within and across cancers and correlates with clinical variables. Co-expression analysis highlights the function of mitochondrial genes in oxidative phosphorylation, DNA repair and the cell cycle, and shows their connections with clinically actionable genes. Our study lays a foundation for translating mitochondrial biology into clinical applications.

Abstract: Metabolic diseases are the most common and rapidly growing health issues worldwide. The massive population-based human genetics is crucial for the precise prevention and intervention of metabolic disorders. The China Metabolic Analytics Project (ChinaMAP) is based on cohort studies across diverse regions and ethnic groups with metabolic phenotypic data in China. Here, we describe the centralized analysis of the deep whole genome sequencing data and the genetic bases of metabolic traits in 10,588 individuals from the ChinaMAP. The frequency spectrum of variants, population structure, pathogenic variants and novel genomic characteristics were analyzed. The individual genetic evaluations of Mendelian diseases, nutrition and drug metabolism, and traits of blood glucose and BMI were integrated. Our study establishes a large-scale and deep resource for the genetics of East Asians and provides opportunities for novel genetic discoveries of metabolic characteristics and disorders.

Abstract: The UK Biobank Exome Sequencing Consortium (UKB-ESC) is a unique private/public partnership between the UK Biobank and eight biopharma companies that will sequence the exomes of all ∼500,000 UK Biobank participants. Here we describe early results from the exome sequence data generated by this consortium for the first ∼200,000 UKB subjects and the key features of this project that enabled the UKB-ESC to come together and generate this data. Exome sequencing data from the first 200,643 UKB enrollees are now accessible to the research community. Approximately 10M variants were observed within the targeted regions, including: 8,086,176 SNPs, 370,958 indels and 1,596,984 multi-allelic variants. Of the ∼8M variants observed, 84.5% are coding variants and include 2,139,318 (25.3%) synonymous, 4,549,694 (53.8%) missense, 453,733 (5.4%) predicted loss-of-function (LOF) variants (initiation codon loss, premature stop codons, stop codon loss, splicing and frameshift variants) affecting at least one coding transcript. This open access data provides a rich resource of coding variants for rare variant genetic studies, and is particularly valuable for drug discovery efforts that utilize rare, functionally consequential variants. Over the past decade, the biopharma industry has increasingly leveraged human genetics as part of their drug discovery and development strategies. This shift was motivated by technical advances that enabled cost-effective human genetics research at scale, the emergence of electronic health records and biobanks, and a maturing understanding of how human genetics can increase the probability of successful drug development. Recognizing the need for large-scale human genetics data to drive drug discovery, and the unique value of the open data access policies and contribution terms of the UK Biobank, the UKB-ESC was formed. This precompetitive collaboration has further strengthened the ties between academia and industry and provided teams an unprecedented opportunity to interact with and learn from the wider research community.

Abstract: Ancestry connects genetics and society in fundamental ways. For many people it has cultural, religious or even political significance, and can play a key role in shaping personal and public identities. People’s desire to discover their own ancestry drives the multibillion-dollar genealogy industry, which has grown rapidly in the era of consumer genomics. Companies such as 23andMe and Ancestry now claim tens of millions of customers worldwide. In parallel, our scientific understanding of the human past is being transformed by studies of ancient and modern genetic data, which allow us to track changes in ancestry over space and time. Sophisticated methods have been developed to infer and visualise these relationships. Thus, it seems that both scientists and the wider public are learning more and more about ancestry, and there is an optimistic sense that genetic data provide an exhaustive repository of ancestral information. However, although frequently discussed, ancestry itself is rarely defined. We argue that this reflects widespread underlying confusion about what it means in different contexts and what genetic data can really tell us. This leads to miscommunication between researchers in different fields, and leaves customers open to spurious claims about consumer genomics products and overinterpretation of individual results. In wider usage, the terms ancestry and ancestors often indicate a general connection to people or things in the past. But in a genetic context they have a more specific meaning: your ancestors are the individuals from whom you are biologically descended and ancestry is information about them and their genetic relationship to you. Even here however, confusion arises from the way that ancestry is presented and discussed. Rather than emphasising its complex structure, results are often simplified in terms of discrete categories. While convenient and sometimes useful, ultimately this is misleading about the nature of ancestry. These labels can also impose contemporary political or cultural divisions which may be misrepresentative of ancestral relationships. Another source of confusion is that three distinct concepts–genealogical ancestry, genetic ancestry, and genetic similarity–are frequently conflated. We discuss them in turn, but note that only the first two are explicitly forms of ancestry, and that genetic data are surprisingly uninformative about either of them. Consequently, most statements about ancestry are really statements about genetic similarity, which has a complex relationship with ancestry, and can only be related to it by making assumptions about human demography whose validity is uncertain and difficult to test. Genealogical ancestry probably reflects the most common and intuitive understanding of the term ancestry. Consider your parents, grandparents, or even great-grandparents. You likely have a sense of these people as individuals, even if you have never met them. If one of them belonged to a particular group X, you might say that you have some “X” ancestry. You might even be able to claim ancestry in this way from more distant ancestors, based on PLOS GENETICS

Abstract: 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. Brain volume and intelligence have been previously found to have shared genetic etiology, but the specific common genetic signals have not been identified. Here, the authors perform a genome-wide association study on brain volume, finding common genetic loci driving brain volume and intelligence.

Abstract: Craniofacial development involves several complex tissue movements including several fusion processes to form the frontonasal and maxillary structures, including the upper lip and palate. Each of these movements are controlled by many different factors that are tightly regulated by several integral morphogenetic signaling pathways. Subject to both genetic and environmental influences, interruption at nearly any stage can disrupt lip, nasal, or palate fusion and result in a cleft. Here, we discuss many of the genetic risk factors that may contribute to the presentation of orofacial clefts in patients, and several of the key signaling pathways and underlying cellular mechanisms that control lip and palate formation, as identified primarily through investigating equivalent processes in animal models, are examined.

Abstract: This review focuses on the human genetics, epidemiology, and molecular pathophysiology of sex differences in central obesity, adipose distribution, and related cardiometabolic disorders. Distribution of fat is important for cardiometabolic health, with peripheral fat depots having a protective effect and central visceral fat depots conferring a detrimental effect on health. There are important sex differences in fat distribution that are masked when studying body mass index as a measure of obesity. From epidemiological, murine, and in vitro studies, several mechanisms have been proposed to explain the sex differences in adipose distribution, including sex hormonal effects, cell-intrinsic properties, and the microenvironment in fat depots. More recently, human genetics have revealed hundreds of loci for central obesity providing disruptive opportunities for mechanistic discoveries and clinical translation. A striking feature is that over one-third of these loci have reproducible but poorly understood sexual dimorphic associations with central obesity, most having stronger effects in women. Understanding the genetic and molecular mechanisms of adipose distribution and its sexual dimorphism in humans provides a unique opportunity to promote the use of precision medicine for early identification of at-risk individuals, and the development of novel therapeutic strategies for central obesity and related cardiometabolic disorders.

Abstract: Keloid, a common dermal fibroproliferative disorder, is benign skin tumors characterized by the aggressive fibroblasts proliferation and excessive accumulation of extracellular matrix. However, common therapeutic approaches of keloid have limited effectiveness, emphasizing the momentousness of developing innovative mechanisms and therapeutic strategies. Epigenetics, representing the potential link of complex interactions between genetics and external risk factors, is currently under intense scrutiny. Accumulating evidence has demonstrated that multiple diverse and reversible epigenetic modifications, represented by DNA methylation, histone modification, and non-coding RNAs (ncRNAs), play a critical role in gene regulation and downstream fibroblastic function in keloid. Importantly, abnormal epigenetic modification manipulates multiple behaviors of keloid-derived fibroblasts, which served as the main cellular components in keloid skin tissue, including proliferation, migration, apoptosis, and differentiation. Here, we have reviewed and summarized the present available clinical and experimental studies to deeply investigate the expression profiles and clarify the mechanisms of epigenetic modification in the progression of keloid, mainly including DNA methylation, histone modification, and ncRNAs (miRNA, lncRNA, and circRNA). Besides, we also provide the challenges and future perspectives associated with epigenetics modification in keloid. Deciphering the complicated epigenetic modification in keloid is hopeful to bring novel insights into the pathogenesis etiology and diagnostic/therapeutic targets in keloid, laying a foundation for optimal keloid ending.

Abstract: Clinical whole-genome sequencing (WGS) offers clear diagnostic benefits for patients with rare disease. However, there are barriers to its widespread adoption, including a lack of standards for clinical practice. The Medical Genome Initiative consortium was formed to provide practical guidance and support the development of standards for the use of clinical WGS.

Abstract: It is becoming increasingly apparent that certain phenotypes are inherited across generations independent of the information contained in the DNA sequence, by factors in germ cells that remain largely uncharacterized. As evidence for germline non-genetic inheritance of phenotypes and diseases continues to grow in model organisms, there are fewer reports of this phenomenon in humans, due to a variety of complications in evaluating this mechanism of inheritance in humans. This review summarizes the evidence for germline-based non-genetic inheritance in humans, as well as the significant challenges and important caveats that must be considered when evaluating this process in human populations. Most reports of this process evaluate the association of a lifetime exposure in ancestors with changes in DNA methylation or small RNA expression in germ cells, as well as the association between ancestral experiences and the inheritance of a phenotype in descendants, down to great-grandchildren in some cases. Collectively, these studies provide evidence that phenotypes can be inherited in a DNA-independent manner; the extent to which this process contributes to disease development, as well as the cellular and molecular regulation of this process, remain largely undefined.

Abstract: The intestinal microbiome has emerged as an important component involved in various diseases. Therefore, the interest in understanding the factors shaping its composition is growing. The gut microbiome, often defined as a complex trait, contains diverse components and its properties are determined by a combination of external and internal effects. Although much effort has been invested so far, it is still difficult to evaluate the extent to which human genetics shape the composition of the gut microbiota. However, in mouse studies, where the environmental factors are better controlled, the effect of the genetic background was significant. The purpose of this paper is to provide a current assessment of the role of human host genetics in shaping the gut microbiome composition. Despite the inconsistency of the reported results, it can be estimated that the genetic factor affects a portion of the microbiome. However, this effect is currently lower than the initial estimates, and it is difficult to separate the genetic influence from the environmental effect. Additionally, despite the differences between the microbial composition of humans and mice, results from mouse models can strengthen our knowledge of host genetics underlying the human gut microbial variation.

Abstract: The lysosomal degradation pathway of macroautophagy (herein referred to as autophagy) plays a crucial role in cellular physiology by regulating the removal of unwanted cargoes such as protein aggregates and damaged organelles. Over the last five decades, significant progress has been made in understanding the molecular mechanisms that regulate autophagy and its roles in human physiology and diseases. These advances, together with discoveries in human genetics linking autophagy-related gene mutations to specific diseases, provide a better understanding of the mechanisms by which autophagy-dependent pathways can be potentially targeted for treating human diseases. Here, we review mutations that have been identified in genes involved in autophagy and their associations with neurodegenerative diseases.

Abstract: Population structure is a commonplace feature of genetic variation data, and it has importance in numerous application areas, including evolutionary genetics, conservation genetics, and human genetics. Understanding the structure in a sample is necessary before more sophisticated analyses are undertaken. Here we provide a protocol for running principal component analysis (PCA) and admixture proportion inference-two of the most commonly used approaches in describing population structure. Along with hands-on examples with CEPH-Human Genome Diversity Panel and pragmatic caveats, readers will learn to analyze and visualize population structure on their own data.

Abstract: DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes that affect DNA methylation patterns in blood using large-scale population genomics data. By employing genetic instruments as causal anchors, we establish directed associations between gene expression and distant DNA methylation levels, while ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. The identified genes are enriched for transcription factors, of which many consistently increased or decreased DNA methylation levels at multiple CpG sites. In addition, we show that a substantial number of transcription factors affected DNA methylation at their experimentally determined binding sites. We also observe genes encoding proteins with heterogenous functions that have widespread effects on DNA methylation, e.g., NFKBIE, CDCA7(L), and NLRC5, and for several examples, we suggest plausible mechanisms underlying their effect on DNA methylation. We report hundreds of genes that affect DNA methylation and provide key insights in the principles underlying epigenetic regulation.

Abstract: ATP-binding cassette (ABC) transporters constitute a superfamily of 48 structurally similar membrane transporters that mediate the ATP-dependent cellular export of a plethora of endogenous and xenobiotic substances. Importantly, genetic variants in ABC genes that affect gene function have clinically important effects on drug disposition and can be predictors of the risk of adverse drug reactions and efficacy of chemotherapeutics, calcium channel blockers, and protease inhibitors. Furthermore, loss-of-function of ABC transporters is associated with a variety of congenital disorders. Despite their clinical importance, information about the frequencies and global distribution of functionally relevant ABC variants is limited and little is known about the overall genetic complexity of this important gene family. Here, we systematically mapped the genetic landscape of the entire human ABC superfamily using Next-Generation Sequencing data from 138,632 individuals across seven major populations. Overall, we identified 62,793 exonic variants, 98.5% of which were rare. By integrating five computational prediction algorithms with structural mapping approaches using experimentally determined crystal structures, we found that the functional ABC variability is extensive and highly population-specific. Every individual harbored between 9.3 and 13.9 deleterious ABC variants, 76% of which were found only in a single population. Carrier rates of pathogenic variants in ABC transporter genes associated with autosomal recessive congenital diseases, such as cystic fibrosis or pseudoxanthoma elasticum, closely mirrored the corresponding population-specific disease prevalence, thus providing a novel resource for rare disease epidemiology. Combined, we provide the most comprehensive, systematic, and consolidated overview of ethnogeographic ABC transporter variability with important implications for personalized medicine, clinical genetics, and precision public health.

Abstract: Immune response is one of the functions that have been more strongly targeted by natural selection during human evolution. The evolutionary genetic dissection of the immune system has greatly helped to distinguish genes and functions that are essential, redundant or advantageous for human survival. It is also becoming increasingly clear that admixture between early Eurasians with now-extinct hominins such as Neanderthals or Denisovans, or admixture between modern human populations, can be beneficial for human adaptation to pathogen pressures. In this review, we discuss how the integration of population genetics with functional genomics in diverse human populations can inform about the changes in immune functions related to major lifestyle transitions (e.g., from hunting and gathering to farming), the action of natural selection to the evolution of the immune system, and the history of past epidemics. We also highlight the need of expanding the characterization of the immune system to a larger array of human populations-particularly neglected human groups historically exposed to different pathogen pressures-to fully capture the relative contribution of genetic, epigenetic, and environmental factors to immune response variation in humans.

Abstract: * Correspondence: itai.yanai@ nyulangone.org; martin.lercher@ hhu.de Institute for Computational Medicine, NYU Langone Health, New York, NY 10016, USA Institute for Computer Science & Department of Biology, Heinrich Heine University, 40225 Düsseldorf, Germany “If we allow ourselves the license of talking about genes as if they had conscious aims, always reassuring ourselves that we could translate our sloppy language back into respectable terms if we wanted to, we can ask the question, what is a single selfish gene trying to do?”—Richard Dawkins, The Selfish Gene: p. 88 “I’ve made agents out of system 1 and system 2 because everybody finds it easier to think about agents – with propensities and traits – than about abstract categories. Agents make powerful subjects because they’re active and they do things.”—Daniel Kahneman, personal communication

Abstract: One of the rapidly developing areas in human genetics and genomics is detection of candidate Single Nucleotide Polymorphism (SNPs) for human complex traits. These findings can be used in the field ...

Abstract: Preterm delivery is both a traumatizing experience for the patient and a burden on the healthcare system. A condition distinguishable by its phenotype in prematurity is cervical insufficiency, where certain cases exhibit a strong genetic component. Despite genomic advancements, little is known about the genetics of human cervix remodeling during pregnancy. Using selected gene approaches, a few studies have demonstrated an association of common gene variants with cervical insufficiency. However, until now, no study has employed comprehensive methods to investigate this important subject matter. In this study, we asked: i) are there genes reliably linked to cervical insufficiency and, if so, what are their roles? and ii) what is the proportion of cases of non-syndromic cervical insufficiency attributable to these genetic variations? We performed next-generation sequencing on 21 patients with a clinical presentation of cervical insufficiency. To assist the sequencing data interpretation, we retrieved all known genes implicated in cervical functioning through a systematic literature analysis and additional gene searches. These genes were then classified according to their relation to the questions being posed by the study. Patients' sequence variants were filtered for pathogenicity and assigned a likelihood of being contributive to phenotype development. Gene extraction and analysis revealed 12 genes primarily linked to cervical insufficiency, the majority of which are known to cause collagenopathies. Ten patients carried disruptive variants potentially contributive to the development of non-syndromic cervical insufficiency. Pathway enrichment analysis of variant genes from our cohort revealed an increased variation burden in genes playing roles in tissue mechanical and biomechanical properties, i.e. collagen biosynthesis and cell-extracellular matrix communications. Consequently, the proposed idea of cervical insufficiency being a subtle form of collagenopathy, now strengthened by our genetic findings, might open up new opportunities for improved patient evaluation and management.

Abstract: A challenge in medical genomics is to identify variants and genes associated with severe genetic disorders. Based on the premise that severe, early-onset disorders often result in a reduction of evolutionary fitness, several statistical methods have been developed to predict pathogenic variants or constrained genes based on the signatures of negative selection in human populations. However, we currently lack a statistical framework to jointly predict deleterious variants and constrained genes from both variant-level features and gene-level selective constraints. Here we present such a unified approach, UNEECON, based on deep learning and population genetics. UNEECON treats the contributions of variant-level features and gene-level constraints as a variant-level fixed effect and a gene-level random effect, respectively. The sum of the fixed and random effects is then combined with an evolutionary model to infer the strength of negative selection at both variant and gene levels. Compared with previously published methods, UNEECON shows improved performance in predicting missense variants and protein-coding genes associated with autosomal dominant disorders, and feature importance analysis suggests that both gene-level selective constraints and variant-level predictors are important for accurate variant prioritization. Furthermore, based on UNEECON, we observe a low correlation between gene-level intolerance to missense mutations and that to loss-of-function mutations, which can be partially explained by the prevalence of disordered protein regions that are highly tolerant to missense mutations. Finally, we show that genes intolerant to both missense and loss-of-function mutations play key roles in the central nervous system and the autism spectrum disorders. Overall, UNEECON is a promising framework for both variant and gene prioritization.

Abstract: Congenital heart disease (CHD) occurs in almost 1% of newborn children and is considered a multifactorial disorder. CHD may segregate in families due to significant contribution of genetic factors in the disease etiology. The aim of the study was to identify pathophysiological mechanisms in families segregating CHD. We used whole exome sequencing to identify rare genetic variants in ninety consenting participants from 32 Danish families with recurrent CHD. We applied a systems biology approach to identify developmental mechanisms influenced by accumulation of rare variants. We used an independent cohort of 714 CHD cases and 4922 controls for replication and performed functional investigations using zebrafish as in vivo model. We identified 1785 genes, in which rare alleles were shared between affected individuals within a family. These genes were enriched for known cardiac developmental genes, and 218 of these genes were mutated in more than one family. Our analysis revealed a functional cluster, enriched for proteins with a known participation in calcium signaling. Replication in an independent cohort confirmed increased mutation burden of calcium-signaling genes in CHD patients. Functional investigation of zebrafish orthologues of ITPR1, PLCB2, and ADCY2 verified a role in cardiac development and suggests a combinatorial effect of inactivation of these genes. The study identifies abnormal calcium signaling as a novel pathophysiological mechanism in human CHD and confirms the complex genetic architecture underlying CHD.

Abstract: A person's genome typically contains millions of variants which represent the differences between this personal genome and the reference human genome. The interpretation of these variants, i.e., the assessment of their potential impact on a person's phenotype, is currently of great interest in human genetics and medicine. We have developed a prioritization tool called OpenCausal which takes as inputs 1) a personal genome and 2) a reference context-specific TF expression profile and returns a list of noncoding variants prioritized according to their impact on chromatin accessibility for any given genomic region of interest. We applied OpenCausal to 6,430 samples across 18 tissues derived from the GTEx project and found that the variants prioritized by OpenCausal are highly enriched for eQTLs and caQTLs. We further propose a strategy to integrate the predicted open scores with genome-wide association studies (GWAS) data to prioritize putative causal variants and regulatory elements for a given risk locus (i.e., fine-mapping analysis). As an initial example, we applied this method to a GWAS dataset of human height and found that the prioritized putative variants and elements are correlated with the phenotype (i.e., heights of individuals) better than others.