Evaluating drug targets through human loss-of-function genetic variation

Context-specific functions of chromatin remodellers in development and disease

Chromatin remodellers were once thought to be highly redundant and nonspecific in their actions. However, recent human genetic studies demonstrate remarkable biological specificity and dosage sensitivity of the thirty-two adenosine triphosphate (ATP)-dependent chromatin remodellers encoded in the human genome. Mutations in remodellers produce many human developmental disorders and cancers, motivating efforts to investigate their distinct functions in biologically relevant settings. Exquisitely specific biological functions seem to be an emergent property in mammals, and in many cases are based on the combinatorial assembly of subunits and the generation of stable, composite surfaces. Critical interactions between remodelling complex subunits, the nucleosome and other transcriptional regulators are now being defined from structural and biochemical studies. In addition, in vivo analyses of remodellers at relevant genetic loci have provided minute-by-minute insights into their dynamics. These studies are proposing new models for the determinants of remodeller localization and function on chromatin.

Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing

We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.

Refining the impact of genetic evidence on clinical success

The cost of drug discovery and development is driven primarily by failure1, with only about 10% of clinical programmes eventually receiving approval2-4. We previously estimated that human genetic evidence doubles the success rate from clinical development to approval5. In this study we leverage the growth in genetic evidence over the past decade to better understand the characteristics that distinguish clinical success and failure. We estimate the probability of success for drug mechanisms with genetic support is 2.6 times greater than those without. This relative success varies among therapy areas and development phases, and improves with increasing confidence in the causal gene, but is largely unaffected by genetic effect size, minor allele frequency or year of discovery. These results indicate we are far from reaching peak genetic insights to aid the discovery of targets for more effective drugs.

Development of a First-in-Class RIPK1 Degrader to Enhance Antitumor Immunity

The scaffolding function of receptor interacting protein kinase 1 (RIPK1) confers intrinsic and extrinsic resistance to immune checkpoint blockades (ICBs) and has emerged as a promising target for improving cancer immunotherapies. To address the challenge posed by a poorly defined binding pocket within the intermediate domain, we harnessed proteolysis targeting chimera (PROTAC) technology to develop a first-in-class RIPK1 degrader, LD4172. LD4172 exhibited potent and selective RIPK1 degradation both in vitro and in vivo. Degradation of RIPK1 by LD4172 triggered immunogenic cell death (ICD) and enriched tumor-infiltrating lymphocytes and substantially sensitized the tumors to anti-PD1 therapy. This work reports the first RIPK1 degrader that serves as a chemical probe for investigating the scaffolding functions of RIPK1 and as a potential therapeutic agent to enhance tumor responses to immune checkpoint blockade therapy.

Immediate-Early Genes as Influencers in Genetic Networks and their Role in Alzheimer's Disease

Immediate-early genes (IEGs) are a class of activity-regulated genes (ARGs) that are transiently and rapidly activated in the absence of de novo protein synthesis in response to neuronal activity. We explored the role of IEGs in genetic networks to pinpoint potential drug targets for Alzheimer's disease (AD). Using a combination of network analysis and genome-wide association study (GWAS) summary statistics we show that (1) IEGs exert greater topological influence across different human and mouse gene networks compared to other ARGs, (2) ARGs are sparsely involved in diseases and significantly more mutational constrained compared to non-ARGs, (3) Many AD-linked variants are in ARGs gene regions, mainly in MARK4 near FOSB, with an AD risk eQTL that increases MARK4 expression in cortical areas, (4) MARK4 holds an influential place in a dense AD multi-omic network and a high AD druggability score. Our work on IEGs' influential network role is a valuable contribution to guiding interventions for diseases marked by dysregulation of their downstream targets and highlights MARK4 as a promising underexplored AD-target.

The Role of Genetics in Advancing Cardiometabolic Drug Development

PURPOSE OF REVIEW

The objective of this review is to explore the role of genetics in cardiometabolic drug development. The declining costs of sequencing and the availability of large-scale genomic data have deepened our understanding of cardiometabolic diseases, revolutionizing drug discovery and development methodologies. We highlight four key areas in which genetics is empowering drug development for cardiometabolic disease: (1) identifying drug candidates, (2) anticipating drug target failures, (3) silencing and editing genes, and (4) enriching clinical trials.

RECENT FINDINGS

Identifying novel drug targets through genetic discovery studies and the use of genetic variants as indicators of potential drug efficacy and safety have become critical components of cardiometabolic drug discovery. We highlight the successes of genetically-informed therapeutic strategies, such as PCSK9 and ANGPTL3 inhibitors in lipid lowering and the emerging role of polygenic risk scores in improving the efficiency of clinical trials. Additionally, we explore the potential of gene silencing and editing technologies, such as antisense oligonucleotides and small interfering RNA, showcasing their promise in addressing diseases refractory to conventional treatments. In this review, we highlight four use cases that demonstrate the vital role of genetics in cardiometabolic drug development: (1) identifying drug candidates, (2) anticipating drug target failures, (3) silencing and editing genes, and (4) enriching clinical trials. Through these advances, genetics has paved the way to increased efficiency of drug development as well as the discovery of more personalized and effective treatments for cardiometabolic disease.

RNA interference in the era of nucleic acid therapeutics

Two decades of research on RNA interference (RNAi) have transformed a breakthrough discovery in biology into a robust platform for a new class of medicines that modulate mRNA expression. Here we provide an overview of the trajectory of small-interfering RNA (siRNA) drug development, including the first approval in 2018 of a liver-targeted siRNA interference (RNAi) therapeutic in lipid nanoparticles and subsequent approvals of five more RNAi drugs, which used metabolically stable siRNAs combined with N-acetylgalactosamine ligands for conjugate-based liver delivery. We also consider the remaining challenges in the field, such as delivery to muscle, brain and other extrahepatic organs. Today's RNAi therapeutics exhibit high specificity, potency and durability, and are transitioning from applications in rare diseases to widespread, chronic conditions.

Prioritising genetic findings for drug target identification and validation

The decreasing costs of high-throughput genetic sequencing and increasing abundance of sequenced genome data have paved the way for the use of genetic data in identifying and validating potential drug targets. However, the number of identified potential drug targets is often prohibitively large to experimentally evaluate in wet lab experiments, highlighting the need for systematic approaches for target prioritisation. In this review, we discuss principles of genetically guided drug development, specifically addressing loss-of-function analysis, colocalization and Mendelian randomisation (MR), and the contexts in which each may be most suitable. We subsequently present a range of biomedical resources which can be used to annotate and prioritise disease-associated proteins identified by these studies including 1) ontologies to map genes, proteins, and disease, 2) resources for determining the druggability of a potential target, 3) tissue and cell expression of the gene encoding the potential target, and 4) key biological pathways involving the potential target. We illustrate these concepts through a worked example, identifying a prioritised set of plasma proteins associated with non-alcoholic fatty liver disease (NAFLD). We identified five proteins with strong genetic support for involvement with NAFLD: CYB5A, NT5C, NCAN, TGFBI and DAPK2. All of the identified proteins were expressed in both liver and adipose tissues, with TGFBI and DAPK2 being potentially druggable. In conclusion, the current review provides an overview of genetic evidence for drug target identification, and how biomedical databases can be used to provide actionable prioritisation, fully informing downstream experimental validation.

Comparative study on genomic and epigenomic profiles of retinoblastoma or tuberous sclerosis complex via nanopore sequencing and a joint screening framework

Recurrence and extraocular metastasis in advanced intraocular retinoblastoma (RB) are still major obstacles for successful treatment of Chinese children. Tuberous sclerosis complex (TSC) is a very rare, multisystemic genetic disorder characterized by hamartomatous growth. In this study, we aimed to compare genomic and epigenomic profiles with human RB or TSC using recently developed nanopore sequencing, and to identify disease-associated variations or genes. Peripheral blood samples were collected from either RB or RB/TSC patients plus their normal siblings, followed by nanopore sequencing and identification of disease-specific structural variations (SVs) and differentially methylated regions (DMRs) by a systematic biology strategy named as multiomics-based joint screening framework. In total, 316 RB- and 1295 TSC-unique SVs were identified, as well as 1072 RB- and 1114 TSC-associated DMRs, respectively. We eventually identified 6 key genes for RB for further functional validation. Knockdown of CDK19 with specific siRNAs significantly inhibited Y79 cellular proliferation and increased sensitivity to carboplatin, whereas downregulation of AHNAK2 promoted the cell growth as well as drug resistance. Those two genes might serve as potential diagnostic markers or therapeutic targets of RB. The systematic biology strategy combined with functional validation might be an effective approach for rare pediatric malignances with limited samples and challenging collection process.

Translational bioinformatics approach to combat cardiovascular disease and cancers

Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.

Modulation of prion protein expression through cryptic splice site manipulation

Lowering expression of prion protein (PrP) is a well-validated therapeutic strategy in prion disease, but additional modalities are urgently needed. In other diseases, small molecules have proven capable of modulating pre-mRNA splicing, sometimes by forcing inclusion of cryptic exons that reduce gene expression. Here, we characterize a cryptic exon located in human PRNP's sole intron and evaluate its potential to reduce PrP expression through incorporation into the 5' untranslated region (5'UTR). This exon is homologous to exon 2 in non-primate species, but contains a start codon that would yield an upstream open reading frame (uORF) with a stop codon prior to a splice site if included in PRNP mRNA, potentially downregulating PrP expression through translational repression or nonsense-mediated decay. We establish a minigene transfection system and test a panel of splice site alterations, identifying mutants that reduce PrP expression by as much as 78%. Our findings nominate a new therapeutic target for lowering PrP.

Association Analyses of Predicted Loss-of-Function Variants Prioritized 15 Genes as Blood Pressure Regulators

BACKGROUND

Hypertension, clinically defined by elevated blood pressure (BP), is an important cause of mortality and morbidity worldwide. Many risk factors for hypertension are known, including a positive family history, which suggests that genetics contribute to interindividual BP variation. Genome-wide association studies (GWAS) have identified > 1000 loci associated with BP, yet the identity of the genes responsible for these associations remains largely unknown.

METHODS

To pinpoint genes that causally affect variation of BP in humans, we analyzed predicted loss-of-function (pLoF) variants in the UK Biobank whole-exome sequencing dataset (n = 454,709 participants, 6% non-European ancestry). We analyzed genetic associations between systolic or diastolic BP (SBP/DBP) and single pLoF variants (additive and recessive genetic models) as well as with the burden of very rare pLoF variants (minor allele frequency [MAF] < 0.01%).

RESULTS

Single pLoF variants in 10 genes were associated with BP (ANKDD1B, ENPEP, PNCK, BTN3A2, C1orf145 [OBSCN-AS1], CASP9, DBH, KIAA1161 [MYORG], OR4X1, and TMC3). We also found a burden of rare pLoF variants in 5 additional genes associated with BP (TTN, NOS3, FES, SMAD6, COL21A1). Except for PNCK, which is located on the X-chromosome, these genes map near variants previously associated with BP by GWAS, validating the study of pLoF variants to prioritize causal genes at GWAS loci.

CONCLUSIONS

Our study highlights 15 genes that likely modulate BP in humans, including 5 genes that harbour pLoF variants associated with lower BP.

Assessing the safety of lipid-modifying medications among Chinese adolescents: a drug-target Mendelian randomization study

BACKGROUND

With increasing hypercholesterolemia prevalence in East Asian adolescents, pharmacologic interventions (e.g., HMGCR inhibitors (statins) and PCSK9 inhibitors) may have to be considered although their longer-term safety in the general adolescent population is unclear. This study aims to investigate the longer-term safety of HMGCR inhibitors and PCSK9 inhibitors among East Asian adolescents using genetics.

METHODS

A drug-target Mendelian randomization study leveraging the Global Lipid Genetics Consortium (East Asian, n = 146,492) and individual-level data from Chinese participants in the Biobank clinical follow-up of Hong Kong's "Children of 1997" birth cohort (n = 3443, aged ~ 17.6 years). Safety outcomes (n = 100) included anthropometric and hematological traits, renal, liver, lung function, and other nuclear magnetic resonance metabolomics. Positive control outcomes were cholesterol markers from the "Children of 1997" birth cohort and coronary artery disease from Biobank Japan.

RESULTS

Genetic inhibition of HMGCR and PCSK9 were associated with reduction in cholesterol-related NMR metabolomics, e.g., apolipoprotein B (HMGCR: beta [95% CI], - 1.06 [- 1.52 to - 0.60]; PCSK9: - 0.93 [- 1.56 to - 0.31]) and had the expected effect on the positive control outcomes. After correcting for multiple comparisons (p-value < 0.006), genetic inhibition of HMGCR was associated with lower linoleic acid - 0.79 [- 1.25 to - 0.35]. Genetic inhibition of PCSK9 was not associated with the safety outcomes assessed.

CONCLUSIONS

Statins and PCSK9 inhibitors in East Asian adolescents appeared to be safe based on the outcomes concerned. Larger studies were warranted to verify these findings. This study serves as a proof of principle study to inform the medication safety among adolescents via genetics.

An RNA-informed dosage sensitivity map reflects the intrinsic functional nature of genes

Understanding dosage sensitivity or why Mendelian diseases have dominant vs. recessive modes of inheritance is crucial for uncovering the etiology of human disease. Previous knowledge of dosage sensitivity is mainly based on observations of rare loss-of-function mutations or copy number changes, which are underpowered due to ultra rareness of such variants. Thus, the functional underpinnings of dosage constraint remain elusive. In this study, we aim to systematically quantify dosage perturbations from cis-regulatory variants in the general population to yield a tissue-specific dosage constraint map of genes and further explore their underlying functional logic. We reveal an inherent divergence of dosage constraints in genes by functional categories with signaling genes (transcription factors, protein kinases, ion channels, and cellular machinery) being dosage sensitive, while effector genes (transporters, metabolic enzymes, cytokines, and receptors) are generally dosage resilient. Instead of being a metric of functional dispensability, we show that dosage constraint reflects underlying homeostatic constraints arising from negative feedback. Finally, we employ machine learning to integrate DNA and RNA metrics to generate a comprehensive, tissue-specific map of dosage sensitivity (MoDs) for autosomal genes.

Advanced variant classification framework reduces the false positive rate of predicted loss-of-function variants in population sequencing data

Predicted loss of function (pLoF) variants are often highly deleterious and play an important role in disease biology, but many pLoF variants may not result in loss of function (LoF). Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines' PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 genes associated with autosomal-recessive disease from the Genome Aggregation Database (gnomAD v.2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in a low proportion expressed across transcripts (pext) scored region, or the presence of cryptic in-frame splice rescues. Variants predicted to evade LoF or to be potential artifacts were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of pLoF variants predicted as likely not LoF/not LoF, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Essential genes: a cross-species perspective

Protein coding genes exhibit different degrees of intolerance to loss-of-function variation. The most intolerant genes, whose function is essential for cell or/and organism survival, inform on fundamental biological processes related to cell proliferation and organism development and provide a window on the molecular mechanisms of human disease. Here we present a brief overview of the resources and knowledge gathered around gene essentiality, from cancer cell lines to model organisms to human development. We outline the implications of using different sources of evidence and definitions to determine which genes are essential and highlight how information on the essentiality status of a gene can inform novel disease gene discovery and therapeutic target identification.

From target discovery to clinical drug development with human genetics

The substantial investments in human genetics and genomics made over the past three decades were anticipated to result in many innovative therapies. Here we investigate the extent to which these expectations have been met, excluding cancer treatments. In our search, we identified 40 germline genetic observations that led directly to new targets and subsequently to novel approved therapies for 36 rare and 4 common conditions. The median time between genetic target discovery and drug approval was 25 years. Most of the genetically driven therapies for rare diseases compensate for disease-causing loss-of-function mutations. The therapies approved for common conditions are all inhibitors designed to pharmacologically mimic the natural, disease-protective effects of rare loss-of-function variants. Large biobank-based genetic studies have the power to identify and validate a large number of new drug targets. Genetics can also assist in the clinical development phase of drugs-for example, by selecting individuals who are most likely to respond to investigational therapies. This approach to drug development requires investments into large, diverse cohorts of deeply phenotyped individuals with appropriate consent for genetically assisted trials. A robust framework that facilitates responsible, sustainable benefit sharing will be required to capture the full potential of human genetics and genomics and bring effective and safe innovative therapies to patients quickly.

Drug approval prediction based on the discrepancy in gene perturbation effects between cells and humans

BACKGROUND

Poor translation between in vitro and clinical studies due to the cells/humans discrepancy in drug target perturbation effects leads to safety failures in clinical trials, thus increasing drug development costs and reducing patients' life quality. Therefore, developing a predictive model for drug approval considering the cells/humans discrepancy is needed to reduce drug attrition rates in clinical trials.

METHODS

Our machine learning framework predicts drug approval in clinical trials based on the cells/humans discrepancy in drug target perturbation effects. To evaluate the discrepancy to predict drug approval (1404 approved and 1070 unapproved drugs), we analysed CRISPR-Cas9 knockout and loss-of-function mutation rate-based gene perturbation effects on cells and humans, respectively. To validate the risk of drug targets with the cells/humans discrepancy, we examined the targets of failed and withdrawn drugs due to safety problems.

FINDINGS

Drug approvals in clinical trials were correlated with the cells/humans discrepancy in gene perturbation effects. Genes tolerant to perturbation effects on cells but intolerant to those on humans were associated with failed drug targets. Furthermore, genes with the cells/humans discrepancy were related to drugs withdrawn due to severe side effects. Motivated by previous studies assessing drug safety through chemical properties, we improved drug approval prediction by integrating chemical information with the cells/humans discrepancy.

INTERPRETATION

The cells/humans discrepancy in gene perturbation effects facilitates drug approval prediction and explains drug safety failures in clinical trials.

FUNDING

S.K. received grants from the Korean National Research Foundation (2021R1A2B5B01001903 and 2020R1A6A1A03047902) and IITP (2019-0-01906, Artificial Intelligence Graduate School Program, POSTECH).

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank

Exome-sequencing association studies have successfully linked rare protein-coding variation to risk of thousands of diseases. However, the relationship between rare deleterious compound heterozygous (CH) variation and their phenotypic impact has not been fully investigated. Here, we leverage advances in statistical phasing to accurately phase rare variants (MAF ~ 0.001%) in exome sequencing data from 175,587 UK Biobank (UKBB) participants, which we then systematically annotate to identify putatively deleterious CH coding variation. We show that 6.5% of individuals carry such damaging variants in the CH state, with 90% of variants occurring at MAF < 0.34%. Using a logistic mixed model framework, systematically accounting for relatedness, polygenic risk, nearby common variants, and rare variant burden, we investigate recessive effects in common complex diseases. We find six exome-wide significant (P < 1.68 × 10 - 7 ) and 17 nominally significant (P < 5.25 × 10 - 5 ) gene-trait associations. Among these, only four would have been identified without accounting for CH variation in the gene. We further incorporate age-at-diagnosis information from primary care electronic health records, to show that genetic phase influences lifetime risk of disease across 20 gene-trait combinations (FDR < 5%). Using a permutation approach, we find evidence for genetic phase contributing to disease susceptibility for a collection of gene-trait pairs, including FLG-asthma (P = 0.00205 ) and USH2A-visual impairment (P = 0.0084 ). Taken together, we demonstrate the utility of phasing large-scale genetic sequencing cohorts for robust identification of the phenome-wide consequences of compound heterozygosity.

Human prion disease: molecular pathogenesis, and possible therapeutic targets and strategies

INTRODUCTION

Human prion diseases are heterogeneous, and often rapidly progressive, transmissible neurodegenerative disorders associated with misfolded prion protein (PrP) aggregation and self-propagation. Despite their rarity, prion diseases comprise a broad spectrum of phenotypic variants determined at the molecular level by different conformers of misfolded PrP and host genotype variability. Moreover, they uniquely occur in idiopathic, genetically determined, and acquired forms with distinct etiologies.

AREA COVERED

This review provides an up-to-date overview of potential therapeutic targets in prion diseases and the main results obtained in cell and animal models and human trials. The open issues and challenges associated with developing effective therapies and informative clinical trials are also discussed.

EXPERT OPINION

Currently tested therapeutic strategies target the cellular PrP to prevent the formation of misfolded PrP or to favor its elimination. Among them, passive immunization and gene therapy with antisense oligonucleotides against prion protein mRNA are the most promising. However, the disease's rarity, heterogeneity, and rapid progression profoundly frustrate the successful undertaking of well-powered therapeutic trials and patient identification in the asymptomatic or early stage before the development of significant brain damage. Thus, the most promising therapeutic goal to date is preventing or delaying phenoconversion in carriers of pathogenic mutations by lowering prion protein expression.

Penetrance of pathogenic genetic variants associated with premature ovarian insufficiency

Premature ovarian insufficiency (POI) affects 1% of women and is a leading cause of infertility. It is often considered to be a monogenic disorder, with pathogenic variants in ~100 genes described in the literature. We sought to systematically evaluate the penetrance of variants in these genes using exome sequence data in 104,733 women from the UK Biobank, 2,231 (1.14%) of whom reported at natural menopause under the age of 40 years. We found limited evidence to support any previously reported autosomal dominant effect. For nearly all heterozygous effects on previously reported POI genes, we ruled out even modest penetrance, with 99.9% (13,699 out of 13,708) of all protein-truncating variants found in reproductively healthy women. We found evidence of haploinsufficiency effects in several genes, including TWNK (1.54 years earlier menopause, P = 1.59 × 10-6) and SOHLH2 (3.48 years earlier menopause, P = 1.03 × 10-4). Collectively, our results suggest that, for the vast majority of women, POI is not caused by autosomal dominant variants either in genes previously reported or currently evaluated in clinical diagnostic panels. Our findings, plus previous studies, suggest that most POI cases are likely oligogenic or polygenic in nature, which has important implications for future clinical genetic studies, and genetic counseling for families affected by POI.

Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank

Phasing involves distinguishing the two parentally inherited copies of each chromosome into haplotypes. Here, we introduce SHAPEIT5, a new phasing method that quickly and accurately processes large sequencing datasets and applied it to UK Biobank (UKB) whole-genome and whole-exome sequencing data. We demonstrate that SHAPEIT5 phases rare variants with low switch error rates of below 5% for variants present in just 1 sample out of 100,000. Furthermore, we outline a method for phasing singletons, which, although less precise, constitutes an important step towards future developments. We then demonstrate that the use of UKB as a reference panel improves the accuracy of genotype imputation, which is even more pronounced when phased with SHAPEIT5 compared with other methods. Finally, we screen the UKB data for loss-of-function compound heterozygous events and identify 549 genes where both gene copies are knocked out. These genes complement current knowledge of gene essentiality in the human genome.

Genetics of Inborn Errors of Immunity in highly consanguineous Middle Eastern and North African populations

Consanguineous marriages in Middle Eastern and North African (MENA) countries are deeply-rooted tradition and highly prevalent resulting into increased prevalence of autosomal recessive diseases including Inborn Errors of Immunity (IEIs). Molecular genetic testing is an important diagnostic tool for IEIs since it provides a definite diagnosis, genotype-phenotype correlation, and guide therapy. In this review, we will discuss the current state and challenges of genomic and variome studies in MENA region populations, as well as the importance of funding advanced genome projects. In addition, we will review the MENA underlying molecular genetic defects of over 2457 patients published with the common IEIs, where autosomal recessive mode of inheritance accounts for 76% of cases with increased prevalence of combined immunodeficiency diseases (50%). The efforts made in the last three decades in terms of international collaboration and of in situ capacity building in MENA region countries led to the discovery of more than 150 novel genes involved in IEIs. Expanding sequencing studies within the MENA will undoubtedly be a unique asset for the IEI genetics which can advance research, and support precise genomic diagnostics and therapeutics.

Mannose metabolism inhibition sensitizes acute myeloid leukaemia cells to therapy by driving ferroptotic cell death

Resistance to standard and novel therapies remains the main obstacle to cure in acute myeloid leukaemia (AML) and is often driven by metabolic adaptations which are therapeutically actionable. Here we identify inhibition of mannose-6-phosphate isomerase (MPI), the first enzyme in the mannose metabolism pathway, as a sensitizer to both cytarabine and FLT3 inhibitors across multiple AML models. Mechanistically, we identify a connection between mannose metabolism and fatty acid metabolism, that is mediated via preferential activation of the ATF6 arm of the unfolded protein response (UPR). This in turn leads to cellular accumulation of polyunsaturated fatty acids, lipid peroxidation and ferroptotic cell death in AML cells. Our findings provide further support to the role of rewired metabolism in AML therapy resistance, unveil a connection between two apparently independent metabolic pathways and support further efforts to achieve eradication of therapy-resistant AML cells by sensitizing them to ferroptotic cell death.

Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis

Observational studies and randomized controlled trials presented inconsistent findings on the effects of cholesterol-lowering statins on depression. It therefore remains unclear whether statins have any beneficial effects on depression, and if so, what the underlying molecular mechanisms are. Here, we aimed to use genomic approaches to investigate this further. Using Connectivity Map (CMap), we first investigated whether statins and antidepressants shared pharmacological effects by interrogating gene expression responses to drug exposure in human cell lines. Second, using Mendelian randomization analysis, we investigated both on-target (through HMGCR inhibition) and potential off-target (through ITGAL and HDAC2 inhibition) causal effects of statins on depression risk and depressive symptoms, and traits related to the shared biological pathways identified from CMap analysis. Compounds inducing highly similar gene expression responses to statins in HA1E cells (indicated by an average connectivity score with statins > 90) were found to be enriched for antidepressants (12 out of 38 antidepressants; p = 9E-08). Genes perturbed in the same direction by both statins and antidepressants were significantly enriched for diverse cellular and metabolic pathways, and various immune activation, development and response processes. MR analysis did not identify any significant associations between statin exposure and depression risk or symptoms after multiple testing correction. However, genetically proxied HMGCR inhibition was strongly associated with alterations in platelets (a prominent serotonin reservoir) and monocyte percentage, which have previously been implicated in depression. Genetically proxied ITGAL inhibition was strongly associated with basophil, monocyte and neutrophil counts. We identified biological pathways that are commonly perturbed by both statins and antidepressants, and haematological biomarkers genetically associated with statin targets. Our findings warrant pre-clinical investigation of the causal role of these shared pathways in depression and potential as therapeutic targets, and investigation of whether blood biomarkers may be important considerations in clinical trials investigating effects of statins on depression.

Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data

Predicted loss of function (pLoF) variants are highly deleterious and play an important role in disease biology, but many of these variants may not actually result in loss-of-function. Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines's PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 autosomal recessive disease-genes from the Genome Aggregation Database (gnomAD, v2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in low per-base expression (pext) score regions, or the presence of cryptic splice rescues. Variants predicted to be potential artifacts or to evade LoF were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of LoF evading variants assessed, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines, and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Study of effect modifiers of genetically predicted CETP reduction

Genetic variants in drug targets can be used to predict the long-term, on-target effect of drugs. Here, we extend this principle to assess how sex and body mass index may modify the effect of genetically predicted lower CETP levels on biomarkers and cardiovascular outcomes. We found sex and body mass index (BMI) to be modifiers of the association between genetically predicted lower CETP and lipid biomarkers in UK Biobank participants. Female sex and lower BMI were associated with higher high-density lipoprotein cholesterol and lower low-density lipoprotein cholesterol for the same genetically predicted reduction in CETP concentration. We found that sex also modulated the effect of genetically lower CETP on cholesterol efflux capacity in samples from the Montreal Heart Institute Biobank. However, these modifying effects did not extend to sex differences in cardiovascular outcomes in our data. Our results provide insight into the clinical effects of CETP inhibitors in the presence of effect modification based on genetic data. The approach can support precision medicine applications and help assess the external validity of clinical trials.

Mendelian inheritance revisited: dominance and recessiveness in medical genetics

Understanding the consequences of genotype for phenotype (which ranges from molecule-level effects to whole-organism traits) is at the core of genetic diagnostics in medicine. Many measures of the deleteriousness of individual alleles exist, but these have limitations for predicting the clinical consequences. Various mechanisms can protect the organism from the adverse effects of functional variants, especially when the variant is paired with a wild type allele. Understanding why some alleles are harmful in the heterozygous state - representing dominant inheritance - but others only with the biallelic presence of pathogenic variants - representing recessive inheritance - is particularly important when faced with the deluge of rare genetic alterations identified by high throughput DNA sequencing. Both awareness of the specific quantitative and/or qualitative effects of individual variants and the elucidation of allelic and non-allelic interactions are essential to optimize genetic diagnosis and counselling.

Hypothesis-free phenotype prediction within a genetics-first framework

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed 'rare', even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population. Associative methods give some understanding how rare genetic variants influence disease and organism-level phenotypes. But here we show that additional discoveries can be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible genetic causes for developmental disorders that have eluded other established methods and present molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.

Using human genetics to improve safety assessment of therapeutics

Human genetics research has discovered thousands of proteins associated with complex and rare diseases. Genome-wide association studies (GWAS) and studies of Mendelian disease have resulted in an increased understanding of the role of gene function and regulation in human conditions. Although the application of human genetics has been explored primarily as a method to identify potential drug targets and support their relevance to disease in humans, there is increasing interest in using genetic data to identify potential safety liabilities of modulating a given target. Human genetic variants can be used as a model to anticipate the effect of lifelong modulation of therapeutic targets and identify the potential risk for on-target adverse events. This approach is particularly useful for non-clinical safety evaluation of novel therapeutics that lack pharmacologically relevant animal models and can contribute to the intrinsic safety profile of a drug target. This Review illustrates applications of human genetics to safety studies during drug discovery and development, including assessing the potential for on- and off-target associated adverse events, carcinogenicity risk assessment, and guiding translational safety study designs and monitoring strategies. A summary of available human genetic resources and recommended best practices is provided. The challenges and future perspectives of translating human genetic information to identify risks for potential drug effects in preclinical and clinical development are discussed.

Harnessing the Power of Electronic Health Records and Genomics for Drug Discovery

A long-standing recognition that information from human genetics studies has the potential to accelerate drug discovery has led to decades of research on how to leverage genetic and phenotypic information for drug discovery. Established simple and advanced statistical methods that allow the simultaneous analysis of genotype and clinical phenotype data by genome- and phenome-wide analyses, colocalization analyses with quantitative trait loci data from transcriptomics and proteomics data sets from different tissues, and Mendelian randomization are essential tools for drug development in the postgenomic era. Numerous studies have demonstrated how genomic data provide opportunities for the identification of new drug targets, the repurposing of drugs, and drug safety analyses. With an increase in the number of biobanks that enable linking in-depth omics data with rich repositories of phenotypic traits via electronic health records, more powerful ways for the evaluation and validation of drug targets will continue to expand across different disciplines of clinical research.

How to Design Peptides

Novel design of proteins to target receptors for treatment or tissue augmentation has come to the fore owing to advancements in computing power, modeling frameworks, and translational successes. Shorter proteins, or peptides, can offer combinatorial synergies with dendrimer, polymer, or other peptide carriers for enhanced local signaling, which larger proteins may sterically hinder. Here, we present a generalized method for designing a novel peptide. We first show how to create a script protocol that can be used to iteratively optimize and screen novel peptide sequences for binding a target protein. We present a step-by-step introduction to utilizing file repositories, data bases, and the Rosetta software suite. RosettaScripts, an .xml interface that allows for sequential functions to be performed, is used to order the functions for repeatable performance. These strategies may lead to more groups venturing into computational design, which may result in synergies from artificial intelligence/machine learning (AI/ML) to phage display and screening. Importantly, the beginner is expected to be able to design their first peptide ligand and begin their journey in peptide drug discovery. Generally, these peptides potentially could be used to interact with any enzyme or receptor, for example, in the study of chemokines and their interactions with glycosoaminoglycans and their receptors.

Association of germline TYK2 variation with lung cancer and non-Hodgkin lymphoma risk

Deucravacitinib, a novel, selective inhibitor of TYK2 is currently under review at the FDA and EMA for treatment of moderate-to-severe plaque psoriasis. It is unclear whether recent safety concerns (ie, elevated rates of lung cancer and lymphoma) related to similar medications (ie, other JAK inhibitors) are shared with this novel TYK2 inhibitor. We used a partial loss-of-function variant in TYK2 (rs34536443), previously shown to protect against psoriasis and other autoimmune diseases, to evaluate the potential effect of therapeutic TYK2 inhibition on risk of lung cancer and non-Hodgkin lymphoma. Summary genetic association data on lung cancer risk were obtained from a GWAS meta-analysis of 29 266 cases and 56 450 controls in the Integrative Analysis of Lung Cancer Risk and Aetiology (INTEGRAL) consortium. Summary genetic association data on non-Hodgkin lymphoma risk were obtained from a GWAS meta-analysis of 8489 cases and 374 506 controls in the UK Biobank and InterLymph consortium. In the primary analysis, each copy of the minor allele of rs34536443, representing partial TYK2 inhibition, was associated with an increased risk of lung cancer (OR 1.15, 95% CI 1.09-1.23, P = 2.29 × 10-6 ) and non-Hodgkin lymphoma (OR 1.18, 95% CI 1.05-1.33, P = 5.25 × 10-3 ). Our analyses using an established partial loss-of-function mutation to mimic TYK2 inhibition provide genetic evidence that therapeutic TYK2 inhibition may increase risk of lung cancer and non-Hodgkin lymphoma. These findings, consistent with recent reports from postmarketing trials of similar JAK inhibitors, could have important implications for future safety assessment of deucravacitinib and other TYK2 inhibitors in development.

Identification of PCSK9-like human gene knockouts using metabolomics, proteomics, and whole-genome sequencing in a consanguineous population

Natural human knockouts of genes associated with desirable outcomes, such as PCSK9 with low levels of LDL-cholesterol, can lead to the discovery of new drug targets and treatments. Rare loss-of-function variants are more likely to be found in the homozygous state in consanguineous populations, and deep molecular phenotyping of blood samples from homozygous carriers can help to discriminate between silent and functional variants. Here, we combined whole-genome sequencing with proteomics and metabolomics for 2,935 individuals from the Qatar Biobank (QBB) to evaluate the power of this approach for finding genes of clinical and pharmaceutical interest. As proof-of-concept, we identified a homozygous carrier of a very rare PCSK9 variant with extremely low circulating PCSK9 levels and low LDL. Our study demonstrates that the chances of finding such variants are about 168 times higher in QBB compared with GnomAD and emphasizes the potential of consanguineous populations for drug discovery.

Cellular Prion Protein Role in Cancer Biology: Is It A Potential Therapeutic Target?

Cancers are worldwide health concerns, whether they are sporadic or hereditary. The fundamental mechanism that causes somatic or oncogenic mutations and ultimately aids cancer development is still unknown. However, mammalian cells with protein-only somatic inheritance may also contribute to cancerous malignancies. Emerging data from a recent study show that prion-like proteins and prions (PrP^C) are crucial entities that have a functional role in developing neurological disorders and cancer. Furthermore, excessive PrP^C expression profiling has also been detected in non-neuronal tissues, such as the lymphoid cells, kidney, GIT, lung, muscle, and mammary glands. PrP^C expression is strongly linked with the proliferation and metastasis of pancreatic, prostate, colorectal, and breast malignancies. Similarly, experimental investigation presented that the PrP^C expression, including the prion protein-coding gene (PRNP) and p53 ag are directly associated with tumorigenicity and metastasis (tumor suppressor gene). The ERK2 (extracellular signal-regulated kinase) pathway also confers a robust metastatic capability for PrP^C-induced epithelial to mesenchymal transition. Additionally, prions could alter the epigenetic regulation of genes and overactive the mitogen-activated protein kinase (MAPK) signaling pathway, which promotes the development of cancer in humans. Protein overexpression or suppression caused by a prion and prion-like proteins has also been linked to oncogenesis and metastasis. Meanwhile, additional studies have discovered resistance to therapeutic targets, highlighting the significance of protein expression levels as potential diagnostic indicators and therapeutic targets.

Mendelian gene identification through mouse embryo viability screening

BACKGROUND

The diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property.

METHODS

Here we further dissected this spectrum by assessing the embryonic stage at which homozygous loss-of-function results in lethality in mice from the International Mouse Phenotyping Consortium, classifying the set of lethal genes into one of three windows of lethality: early, mid, or late gestation lethal. We studied the correlation between these windows of lethality and various gene features including expression across development, paralogy and constraint metrics together with human disease phenotypes. We explored a gene similarity approach for novel gene discovery and investigated unsolved cases from the 100,000 Genomes Project.

RESULTS

We found that genes in the early gestation lethal category have distinct characteristics and are enriched for genes linked with recessive forms of inherited metabolic disease. We identified several genes sharing multiple features with known biallelic forms of inborn errors of the metabolism and found signs of enrichment of biallelic predicted pathogenic variants among early gestation lethal genes in patients recruited under this disease category. We highlight two novel gene candidates with phenotypic overlap between the patients and the mouse knockouts.

CONCLUSIONS

Information on the developmental period at which embryonic lethality occurs in the knockout mouse may be used for novel disease gene discovery that helps to prioritise variants in unsolved rare disease cases.

Wnt Signaling Interactor WTIP (Wilms Tumor Interacting Protein) Underlies Novel Mechanism for Cardiac Hypertrophy

BACKGROUND

The study of hypertrophic cardiomyopathy (HCM) can yield insight into the mechanisms underlying the complex trait of cardiac hypertrophy. To date, most genetic variants associated with HCM have been found in sarcomeric genes. Here, we describe a novel HCM-associated variant in the noncanonical Wnt signaling interactor WTIP (Wilms tumor interacting protein) and provide evidence of a role for WTIP in complex disease.

METHODS

In a family affected by HCM, we used exome sequencing and identity-by-descent analysis to identify a novel variant in WTIP (p.Y233F). We knocked down WTIP in isolated neonatal rat ventricular myocytes with lentivirally delivered short hairpin ribonucleic acids and in Danio rerio via morpholino injection. We performed weighted gene coexpression network analysis for WTIP in human cardiac tissue, as well as association analysis for WTIP variation and left ventricular hypertrophy. Finally, we generated induced pluripotent stem cell-derived cardiomyocytes from patient tissue, characterized size and calcium cycling, and determined the effect of verapamil treatment on calcium dynamics.

RESULTS

WTIP knockdown caused hypertrophy in neonatal rat ventricular myocytes and increased cardiac hypertrophy, peak calcium, and resting calcium in D rerio. Network analysis of human cardiac tissue indicated WTIP as a central coordinator of prohypertrophic networks, while common variation at the WTIP locus was associated with human left ventricular hypertrophy. Patient-derived WTIP p.Y233F-induced pluripotent stem cell-derived cardiomyocytes recapitulated cellular hypertrophy and increased resting calcium, which was ameliorated by verapamil.

CONCLUSIONS

We demonstrate that a novel genetic variant found in a family with HCM disrupts binding to a known Wnt signaling protein, misregulating cardiomyocyte calcium dynamics. Further, in orthogonal model systems, we show that expression of the gene WTIP is important in complex cardiac hypertrophy phenotypes. These findings, derived from the observation of a rare Mendelian disease variant, uncover a novel disease mechanism with implications across diverse forms of cardiac hypertrophy.

A minority of somatically mutated genes in pre-existing fatty liver disease have prognostic importance in the development of NAFLD

BACKGROUND

Understanding the genetics of liver disease has the potential to facilitate clinical risk stratification. We recently identified acquired somatic mutations in six genes and one lncRNA in pre-existing fatty liver disease. We hypothesised that germline variation in these genes might be associated with the risk of developing steatosis and contribute to the prediction of disease severity.

METHODS

Genome-wide association study (GWAS) summary statistics were extracted from seven studies (>1.7 million participants) for variants near ACVR2A, ALB, CIDEB, FOXO1, GPAM, NEAT1 and TNRC6B for: aminotransferases, liver fat, HbA1c, diagnosis of NAFLD, ARLD and cirrhosis. Findings were replicated using GWAS data from multiple independent cohorts. A phenome-wide association study was performed to examine for related metabolic traits, using both common and rare variants, including gene-burden testing.

RESULTS

There was no evidence of association between rare germline variants or SNPs near five genes (ACVR2A, ALB, CIDEB, FOXO1 and TNRC6B) and risk or severity of liver disease. Variants in GPAM (proxies for p.Ile43Val) were associated with liver fat (p = 3.6 × 10-13 ), ALT (p = 2.8 × 10-39 ) and serum lipid concentrations. Variants in NEAT1 demonstrated borderline significant associations with ALT (p = 1.9 × 10-11 ) and HbA1c, but not with liver fat, as well as influencing waist-to-hip ratio, adjusted for BMI.

CONCLUSIONS

Despite the acquisition of somatic mutations at these loci during progressive fatty liver disease, we did not find associations between germline variation and markers of liver disease, except in GPAM. In the future, larger sample sizes may identify associations. Currently, germline polygenic risk scores will not capture data from genes affected by somatic mutations.

SNP-to-gene linking strategies reveal contributions of enhancer-related and candidate master-regulator genes to autoimmune disease

We assess contributions to autoimmune disease of genes whose regulation is driven by enhancer regions (enhancer-related) and genes that regulate other genes in trans (candidate master-regulator). We link these genes to SNPs using several SNP-to-gene (S2G) strategies and apply heritability analyses to draw three conclusions about 11 autoimmune/blood-related diseases/traits. First, several characterizations of enhancer-related genes using functional genomics data are informative for autoimmune disease heritability after conditioning on a broad set of regulatory annotations. Second, candidate master-regulator genes defined using trans-eQTL in blood are also conditionally informative for autoimmune disease heritability. Third, integrating enhancer-related and master-regulator gene sets with protein-protein interaction (PPI) network information magnified their disease signal. The resulting PPI-enhancer gene score produced >2-fold stronger heritability signal and >2-fold stronger enrichment for drug targets, compared with the recently proposed enhancer domain score. In each case, functionally informed S2G strategies produced 4.1- to 13-fold stronger disease signals than conventional window-based strategies.

ACLY and CKD: A Mendelian Randomization Analysis

Introduction

Adenosine triphosphate-citrate lyase (ACLY) inhibition is a therapeutic strategy under investigation for atherosclerotic cardiovascular disease, nonalcoholic steatohepatitis, and metabolic syndrome. Mouse models suggest that ACLY inhibition could reduce inflammation and kidney fibrosis. Genetic analysis of ACLY in chronic kidney disease (CKD) has not been performed.

Methods

We constructed a genetic instrument by selecting variants associated with ACLY expression in the expression quantitative trait loci genetics consortium (eQTLGen) from blood samples from 31,684 participants. In a 2-sample Mendelian randomization analysis, we evaluated the effect of genetically predicted ACLY expression on the risk of CKD, estimated glomerular filtration rate (eGFR), and albumin-to-creatinine ratio (ACR) using the CKD Genetics (CKDGen) consortium, UK Biobank, and the Finnish Genetics (FinnGen) consortium totaling 66,396 CKD cases and 958,517 controls.

Results

ACLY is constitutively expressed in all cell types including in whole blood. The genetic instrument included 13 variants and explained 1.5% of the variation in whole blood ACLY gene expression. A 34% reduction in ACLY expression score was associated with a 0.04 mmol/l reduced low-density lipoprotein (LDL) cholesterol (P = 3.4 × 10^-4) and a 9% reduced risk of CKD (stages 3, 4, 5, dialysis, or eGFR < 60 ml/min per 1.73 m²) (odds ratio [OR] = 0.91, 95% CI: 0.85-0.98, P = 0.008), but no association was observed with either eGFR or ACR.

Conclusion

Mendelian randomization analyses revealed that genetically reduced ACLY expression was associated with reduced risk of CKD but had no effect on either eGFR or ACR. Further evaluation of ACLY in kidney disease is warranted.

Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology

Advances in genome sequencing technologies have unlocked new possibilities in identifying disease-associated and causative genetic markers, which may in turn enhance disease diagnosis and improve prognostication and management strategies. With the capability of examining genetic variations ranging from single-nucleotide mutations to large structural variants, whole-genome sequencing (WGS) is an increasingly adopted approach to dissect the complex genetic architecture of neurologic diseases. There is emerging evidence for different structural variants and their roles in major neurologic and neurodevelopmental diseases. This review first describes different structural variants and their implicated roles in major neurologic and neurodevelopmental diseases, and then discusses the clinical relevance of WGS applications in neurology. Notably, WGS-based detection of structural variants has shown promising potential in enhancing diagnostic power of genetic tests in clinical settings. Ongoing WGS-based research in structural variations and quantifying mutational constraints can also yield clinical benefits by improving variant interpretation and disease diagnosis, while supporting biomarker discovery and therapeutic development. As a result, wider integration of WGS technologies into health care will likely increase diagnostic yields in difficult-to-diagnose conditions and define potential therapeutic targets or intervention points for genome-editing strategies.

Opportunities and challenges for the use of common controls in sequencing studies

Genome-wide association studies using large-scale genome and exome sequencing data have become increasingly valuable in identifying associations between genetic variants and disease, transforming basic research and translational medicine. However, this progress has not been equally shared across all people and conditions, in part due to limited resources. Leveraging publicly available sequencing data as external common controls, rather than sequencing new controls for every study, can better allocate resources by augmenting control sample sizes or providing controls where none existed. However, common control studies must be carefully planned and executed as even small differences in sample ascertainment and processing can result in substantial bias. Here, we discuss challenges and opportunities for the robust use of common controls in high-throughput sequencing studies, including study design, quality control and statistical approaches. Thoughtful generation and use of large and valuable genetic sequencing data sets will enable investigation of a broader and more representative set of conditions, environments and genetic ancestries than otherwise possible.

Loss of Sucrase-Isomaltase Function Increases Acetate Levels and Improves Metabolic Health in Greenlandic Cohorts

BACKGROUND & AIMS

The sucrase-isomaltase (SI) c.273_274delAG loss-of-function variant is common in Arctic populations and causes congenital sucrase-isomaltase deficiency, which is an inability to break down and absorb sucrose and isomaltose. Children with this condition experience gastrointestinal symptoms when dietary sucrose is introduced. We aimed to describe the health of adults with sucrase-isomaltase deficiency.

METHODS

The association between c.273_274delAG and phenotypes related to metabolic health was assessed in 2 cohorts of Greenlandic adults (n = 4922 and n = 1629). A sucrase-isomaltase knockout (Sis-KO) mouse model was used to further elucidate the findings.

RESULTS

Homozygous carriers of the variant had a markedly healthier metabolic profile than the remaining population, including lower body mass index (β [standard error], -2.0 [0.5] kg/m²; P = 3.1 × 10^-5), body weight (-4.8 [1.4] kg; P = 5.1 × 10^-4), fat percentage (-3.3% [1.0%]; P = 3.7 × 10^-4), fasting triglyceride (-0.27 [0.07] mmol/L; P = 2.3 × 10^-6), and remnant cholesterol (-0.11 [0.03] mmol/L; P = 4.2 × 10^-5). Further analyses suggested that this was likely mediated partly by higher circulating levels of acetate observed in homozygous carriers (β [standard error], 0.056 [0.002] mmol/L; P = 2.1 × 10^-26), and partly by reduced sucrose uptake, but not lower caloric intake. These findings were verified in Sis-KO mice, which, compared with wild-type mice, were leaner on a sucrose-containing diet, despite similar caloric intake, had significantly higher plasma acetate levels in response to a sucrose gavage, and had lower plasma glucose level in response to a sucrose-tolerance test.

CONCLUSIONS

These results suggest that sucrase-isomaltase constitutes a promising drug target for improvement of metabolic health, and that the health benefits are mediated by reduced dietary sucrose uptake and possibly also by higher levels of circulating acetate.

Analyzing human knockouts to validate GPR151 as a therapeutic target for reduction of body mass index

Novel drug targets for sustained reduction in body mass index (BMI) are needed to curb the epidemic of obesity, which affects 650 million individuals worldwide and is a causal driver of cardiovascular and metabolic disease and mortality. Previous studies reported that the Arg95Ter nonsense variant of GPR151, an orphan G protein-coupled receptor, is associated with reduced BMI and reduced risk of Type 2 Diabetes (T2D). Here, we further investigate GPR151 with the Pakistan Genome Resource (PGR), which is one of the largest exome biobanks of human homozygous loss-of-function carriers (knockouts) in the world. Among PGR participants, we identify eleven GPR151 putative loss-of-function (plof) variants, three of which are present at homozygosity (Arg95Ter, Tyr99Ter, and Phe175LeufsTer7), with a cumulative allele frequency of 2.2%. We confirm these alleles in vitro as loss-of-function. We test if GPR151 plof is associated with BMI, T2D, or other metabolic traits and find that GPR151 deficiency in complete human knockouts is not associated with clinically significant differences in these traits. Relative to Gpr151+/+ mice, Gpr151-/- animals exhibit no difference in body weight on normal chow and higher body weight on a high-fat diet. Together, our findings indicate that GPR151 antagonism is not a compelling therapeutic approach to treatment of obesity.

Sulforaphane reduces obesity by reversing leptin resistance

The ascending prevalence of obesity in recent decades is commonly associated with soaring morbidity and mortality rates, resulting in increased health-care costs and decreased quality of life. A systemic state of stress characterized by low-grade inflammation and pathological formation of reactive oxygen species (ROS) usually manifests in obesity. The transcription factor nuclear factor erythroid-derived 2-like 2 (NRF2) is the master regulator of the redox homeostasis and plays a critical role in the resolution of inflammation. Here, we show that the natural isothiocyanate and potent NRF2 activator sulforaphane reverses diet-induced obesity through a predominantly, but not exclusively, NRF2-dependent mechanism that requires a functional leptin receptor signaling and hyperleptinemia. Sulforaphane does not reduce the body weight or food intake of lean mice but induces an anorectic response when coadministered with exogenous leptin. Leptin-deficient Lep^ob/ob mice and leptin receptor mutant Lepr^db/db mice display resistance to the weight-reducing effect of sulforaphane, supporting the conclusion that the antiobesity effect of sulforaphane requires functional leptin receptor signaling. Furthermore, our results suggest the skeletal muscle as the most notable site of action of sulforaphane whose peripheral NRF2 action signals to alleviate leptin resistance. Transcriptional profiling of six major metabolically relevant tissues highlights that sulforaphane suppresses fatty acid synthesis while promoting ribosome biogenesis, reducing ROS accumulation, and resolving inflammation, therefore representing a unique transcriptional program that leads to protection from obesity. Our findings argue for clinical evaluation of sulforaphane for weight loss and obesity-associated metabolic disorders.

Human Genomics and Drug Development

Insights into the genetic basis of human disease are helping to address some of the key challenges in new drug development including the very high rates of failure. Here we review the recent history of an emerging, genomics-assisted approach to pharmaceutical research and development, and its relationship to Mendelian randomization (MR), a well-established analytical approach to causal inference. We demonstrate how human genomic data linked to pharmaceutically relevant phenotypes can be used for (1) drug target identification (mapping relevant drug targets to diseases), (2) drug target validation (inferring the likely effects of drug target perturbation), (3) evaluation of the effectiveness and specificity of compound-target engagement (inferring the extent to which the effects of a compound are exclusive to the target and distinguishing between on-target and off-target compound effects), and (4) the selection of end points in clinical trials (the diseases or conditions to be evaluated as trial outcomes). We show how genomics can help identify indication expansion opportunities for licensed drugs and repurposing of compounds developed to clinical phase that proved safe but ineffective for the original intended indication. We outline statistical and biological considerations in using MR for drug target validation (drug target MR) and discuss the obstacles and challenges for scaled applications of these genomics-based approaches.

Imputation Performance in Latin American Populations: Improving Rare Variants Representation With the Inclusion of Native American Genomes

Current Genome-Wide Association Studies (GWAS) rely on genotype imputation to increase statistical power, improve fine-mapping of association signals, and facilitate meta-analyses. Due to the complex demographic history of Latin America and the lack of balanced representation of Native American genomes in current imputation panels, the discovery of locally relevant disease variants is likely to be missed, limiting the scope and impact of biomedical research in these populations. Therefore, the necessity of better diversity representation in genomic databases is a scientific imperative. Here, we expand the 1,000 Genomes reference panel (1KGP) with 134 Native American genomes (1KGP + NAT) to assess imputation performance in Latin American individuals of mixed ancestry. Our panel increased the number of SNPs above the GWAS quality threshold, thus improving statistical power for association studies in the region. It also increased imputation accuracy, particularly in low-frequency variants segregating in Native American ancestry tracts. The improvement is subtle but consistent across countries and proportional to the number of genomes added from local source populations. To project the potential improvement with a higher number of reference genomes, we performed simulations and found that at least 3,000 Native American genomes are needed to equal the imputation performance of variants in European ancestry tracts. This reflects the concerning imbalance of diversity in current references and highlights the contribution of our work to reducing it while complementing efforts to improve global equity in genomic research.

An updated ANGPTL3-4-8 model as a mechanism of triglyceride partitioning between fat and oxidative tissues

In mammals, triglyceride (TG), the main form of lipids for storing and providing energy, is stored in white adipose tissue (WAT) after food intake, while during fasting it is routed to oxidative tissues (heart and skeletal muscle) for energy production, a process referred to as TG partitioning. Lipoprotein lipase (LPL), a rate-limiting enzyme in this fundamental physiological process, hydrolyzes circulating TG to generate free fatty acids that are taken up by peripheral tissues. The postprandial activity of LPL declines in oxidative tissues but rises in WAT, directing TG to WAT; the reverse is true during fasting. However, the molecular mechanism in regulating tissue-specific LPL activity during the fed-fast cycle has not been completely understood. Research on angiopoietin-like (ANGPTL) proteins (A3, A4, and A8) has resulted in an ANGPTL3-4-8 model to explain the TG partitioning between WAT and oxidative tissues. Food intake induces A8 expression in the liver and WAT. Liver A8 activates A3 by forming the A3-8 complex, which is then secreted into the circulation. The A3-8 complex acts in an endocrine manner to inhibit LPL in oxidative tissues. WAT A8 forms the A4-8 complex, which acts locally to block A4's LPL-inhibiting activity. Therefore, the postprandial activity of LPL is low in oxidative tissues but high in WAT, directing circulating TG to WAT. Conversely, during fasting, reduced A8 expression in the liver and WAT disables A3 from inhibiting oxidative-tissue LPL and restores WAT A4's LPL-inhibiting activity, respectively. Thus, the fasting LPL activity is high in oxidative tissues but low in WAT, directing TG to the former. According to the model, we hypothesize that A8 antagonism has the potential to simultaneously reduce TG and increase HDL-cholesterol plasma levels. Future research on A3, A4, and A8 can hopefully provide more insights into human health, disease, and therapeutics.

Targeted therapies in genetic dilated and hypertrophic cardiomyopathies: From molecular mechanisms to therapeutic targets

Genetic cardiomyopathies are disorders of the cardiac muscle, most often explained by pathogenic mutations in genes encoding sarcomere, cytoskeleton, or ion channel proteins. Clinical phenotypes such as heart failure and arrhythmia are classically treated with generic drugs, but aetiology‐specific and targeted treatments are lacking. As a result, cardiomyopathies still present a major burden to society, and affect many young and older patients. The Translational Committee of the Heart Failure Association (HFA) and the Working Group of Myocardial Function of the European Society of Cardiology (ESC) organized a workshop to discuss recent advances in molecular and physiological studies of various forms of cardiomyopathies. The study of cardiomyopathies has intensified after several new study setups became available, such as induced pluripotent stem cells, three‐dimensional printing of cells, use of scaffolds and engineered heart tissue, with convincing human validation studies. Furthermore, our knowledge on the consequences of mutated proteins has deepened, with relevance for cellular homeostasis, protein quality control and toxicity, often specific to particular cardiomyopathies, with precise effects explaining the aberrations. This has opened up new avenues to treat cardiomyopathies, using contemporary techniques from the molecular toolbox, such as gene editing and repair using CRISPR‐Cas9 techniques, antisense therapies, novel designer drugs, and RNA therapies. In this article, we discuss the connection between biology and diverse clinical presentation, as well as promising new medications and therapeutic avenues, which may be instrumental to come to precision medicine of genetic cardiomyopathies.