A brief history of human disease genetics

Identification of Known and Novel Long Noncoding RNAs Potentially Responsible for the Effects of Bone Mineral Density (BMD) Genomewide Association Study (GWAS) Loci

Osteoporosis, characterized by low bone mineral density (BMD), is the most common complex disease affecting bone and constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 associations influencing BMD. It has been shown that perturbations to long noncoding RNAs (lncRNAs) influence BMD and the activities of bone cells; however, the extent to which lncRNAs are involved in the genetic regulation of BMD is unknown. Here, we combined the analysis of allelic imbalance (AI) in human acetabular bone fragments with a transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) colocalization analysis using data from the Genotype-Tissue Expression (GTEx) project to identify lncRNAs potentially responsible for GWAS associations. We identified 27 lncRNAs in bone that are located in proximity to a BMD GWAS association and harbor single-nucleotide polymorphisms (SNPs) demonstrating AI. Using GTEx data we identified an additional 31 lncRNAs whose expression was associated (false discovery rate [FDR] correction < 0.05) with BMD through TWAS and had a colocalizing eQTL (regional colocalization probability [RCP] > 0.1). The 58 lncRNAs are located in 43 BMD associations. To further support a causal role for the identified lncRNAs, we show that 23 of the 58 lncRNAs are differentially expressed as a function of osteoblast differentiation. Our approach identifies lncRNAs that are potentially responsible for BMD GWAS associations and suggest that lncRNAs play a role in the genetics of osteoporosis. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Non-coding genetic variation in regulatory elements determines thrombosis and hemostasis phenotypes

Since the early inception of genome-wide association studies (GWAS), it became clear that, in all diseases or traits studied, most genetic variants are likely to exert their effect on gene expression mainly by altering the function of regulatory elements. At the same time, the regulation of the gene expression field broadened its boundaries, from the univocal relationship between regulatory elements and genes to include genome organization, long-range DNA interactions, and epigenetics. Next-generation sequencing has introduced genome-wide approaches that have greatly improved our understanding of the general principles of gene expression. However, elucidating how these apply in every single genomic locus still requires painstaking experimental work, in which several independent lines of evidence are required, and often this is helped by rare genetic variants in individuals with rare diseases. This review will focus on the non-coding features of the genome involved in transcriptional regulation, that when altered, leads to known cases of inherited (familial) thrombotic and hemostatic phenotypes, emphasizing the role of enhancers and super-enhancers.

Improvements of nuclease and nickase gene modification techniques for the treatment of genetic diseases

Advancements in genome editing make possible to exploit the functions of enzymes for efficient DNA modifications with tremendous potential to treat human genetic diseases. Several nuclease genome editing strategies including Meganucleases (MNs), Zinc Finger Nucleases (ZFNs), Transcription Activator-like Effector Nucleases (TALENs) and Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated proteins (CRISPR-Cas) have been developed for the correction of genetic mutations. CRISPR-Cas has further been engineered to create nickase genome editing tools including Base editors and Prime editors with much precision and efficacy. In this review, we summarized recent improvements in nuclease and nickase genome editing approaches for the treatment of genetic diseases. We also highlighted some limitations for the translation of these approaches into clinical applications.

Incomplete Penetrance and Variable Expressivity: From Clinical Studies to Population Cohorts

The same genetic variant found in different individuals can cause a range of diverse phenotypes, from no discernible clinical phenotype to severe disease, even among related individuals. Such variants can be said to display incomplete penetrance, a binary phenomenon where the genotype either causes the expected clinical phenotype or it does not, or they can be said to display variable expressivity, in which the same genotype can cause a wide range of clinical symptoms across a spectrum. Both incomplete penetrance and variable expressivity are thought to be caused by a range of factors, including common variants, variants in regulatory regions, epigenetics, environmental factors, and lifestyle. Many thousands of genetic variants have been identified as the cause of monogenic disorders, mostly determined through small clinical studies, and thus, the penetrance and expressivity of these variants may be overestimated when compared to their effect on the general population. With the wealth of population cohort data currently available, the penetrance and expressivity of such genetic variants can be investigated across a much wider contingent, potentially helping to reclassify variants that were previously thought to be completely penetrant. Research into the penetrance and expressivity of such genetic variants is important for clinical classification, both for determining causative mechanisms of disease in the affected population and for providing accurate risk information through genetic counseling. A genotype-based definition of the causes of rare diseases incorporating information from population cohorts and clinical studies is critical for our understanding of incomplete penetrance and variable expressivity. This review examines our current knowledge of the penetrance and expressivity of genetic variants in rare disease and across populations, as well as looking into the potential causes of the variation seen, including genetic modifiers, mosaicism, and polygenic factors, among others. We also considered the challenges that come with investigating penetrance and expressivity.

Cyclic GMP modulating drugs in cardiovascular diseases: mechanism-based network pharmacology

Mechanism-based therapy centred on the molecular understanding of disease-causing pathways in a given patient is still the exception rather than the rule in medicine, even in cardiology. However, recent successful drug developments centred around the second messenger cyclic guanosine-3'-5'-monophosphate (cGMP), which is regulating a number of cardiovascular disease modulating pathways, are about to provide novel targets for such a personalized cardiovascular therapy. Whether cGMP breakdown is inhibited or cGMP synthesis is stimulated via guanylyl cyclases or their upstream regulators in different cardiovascular disease phenotypes, the outcomes seem to be so far uniformly protective. Thus, a network of cGMP-modulating drugs has evolved that act in a mechanism-based, possibly causal manner in a number of cardiac conditions. What remains a challenge is the detection of cGMPopathy endotypes amongst cardiovascular disease phenotypes. Here, we review the growing clinical relevance of cGMP and provide a glimpse into the future on how drugs interfering with this pathway may change how we treat and diagnose cardiovascular diseases altogether.

DecodeME: community recruitment for a large genetics study of myalgic encephalomyelitis / chronic fatigue syndrome

BACKGROUND

Myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) is a common, long-term condition characterised by post-exertional malaise, often with fatigue that is not significantly relieved by rest. ME/CFS has no confirmed diagnostic test or effective treatment and we lack knowledge of its causes. Identification of genes and cellular processes whose disruption adds to ME/CFS risk is a necessary first step towards development of effective therapy.

METHODS

Here we describe DecodeME, an ongoing study co-produced by people with lived experience of ME/CFS and scientists. Together we designed the study and obtained funding and are now recruiting up to 25,000 people in the UK with a clinical diagnosis of ME/CFS. Those eligible for the study are at least 16 years old, pass international study criteria, and lack any alternative diagnoses that can result in chronic fatigue. These will include 5,000 people whose ME/CFS diagnosis was a consequence of SARS-CoV-2 infection. Questionnaires are completed online or on paper. Participants' saliva DNA samples are acquired by post, which improves participation by more severely-affected individuals. Digital marketing and social media approaches resulted in 29,000 people with ME/CFS in the UK pre-registering their interest in participating. We will perform a genome-wide association study, comparing participants' genotypes with those from UK Biobank as controls. This should generate hypotheses regarding the genes, mechanisms and cell types contributing to ME/CFS disease aetiology.

DISCUSSION

The DecodeME study has been reviewed and given a favourable opinion by the North West - Liverpool Central Research Ethics Committee (21/NW/0169). Relevant documents will be available online ( www.decodeme.org.uk ). Genetic data will be disseminated as associated variants and genomic intervals, and as summary statistics. Results will be reported on the DecodeME website and via open access publications.

The contribution of common regulatory and protein-coding TYR variants to the genetic architecture of albinism

Genetic diseases have been historically segregated into rare Mendelian disorders and common complex conditions. Large-scale studies using genome sequencing are eroding this distinction and are gradually unmasking the underlying complexity of human traits. Here, we analysed data from the Genomics England 100,000 Genomes Project and from a cohort of 1313 individuals with albinism aiming to gain insights into the genetic architecture of this archetypal rare disorder. We investigated the contribution of protein-coding and regulatory variants both rare and common. We focused on TYR, the gene encoding tyrosinase, and found that a high-frequency promoter variant, TYR c.-301C>T [rs4547091], modulates the penetrance of a prevalent, albinism-associated missense change, TYR c.1205G>A (p.Arg402Gln) [rs1126809]. We also found that homozygosity for a haplotype formed by three common, functionally-relevant variants, TYR c.[-301C;575C>A;1205G>A], is associated with a high probability of receiving an albinism diagnosis (OR>82). This genotype is also associated with reduced visual acuity and with increased central retinal thickness in UK Biobank participants. Finally, we report how the combined analysis of rare and common variants can increase diagnostic yield and can help inform genetic counselling in families with albinism.

Flashfm-ivis: interactive visualization for fine-mapping of multiple quantitative traits

SUMMARY

flashfm-ivis provides a suite of interactive visualization plots to view potential causal genetic variants that underlie associations that are shared or distinct between multiple quantitative traits and compares results between single- and multi-trait fine-mapping. Unique features include network diagrams that show joint effects between variants for each trait and regional association plots that integrate fine-mapping results, all with user-controlled zoom features for an interactive exploration of potential causal variants across traits.

AVAILABILITY AND IMPLEMENTATION

flashfm-ivis is an open-source software under the MIT license. It is available as an interactive web-based tool (http://shiny.mrc-bsu.cam.ac.uk/apps/flashfm-ivis/) and as an R package. Code and documentation are available at https://github.com/fz-cambridge/flashfm-ivis and https://zenodo.org/record/6376244#.YjnarC-l2X0. Additional features can be downloaded as standalone R libraries to encourage reuse.

SUPPLEMENTARY INFORMATION

Supplementary information are available at Bioinformatics online.

Diversities of allergic pathologies and their modifiers: Report from the second DGAKI-JSA meeting

In October 2021, researchers from the German Society of Allergy and Clinical Immunology (DGAKI) and from the Japanese Society of Allergology (JSA) focused their attention on the pathological conditions and modifiers of various allergic diseases. Topics included 1) the pathophysiology of IgE/mast cell-mediated allergic diseases; 2) the diagnosis and prevention of IgE/mast cell-mediated diseases; 3) the pathophysiology, diagnosis, and treatment of eosinophilic airway diseases; and 4) host-pathogen interaction and allergic diseases. This report summarizes the panel discussions, which highlighted the importance of recognizing the diversity of genetics, immunological mechanisms, and modifying factors underlying allergic diseases.

Nutrition for precision health: The time is now

Precision nutrition has emerged as a boiling area of nutrition research, with a particular focus on revealing the individual variability in response to diets that is determined mainly by the complex interactions of dietary factors with the multi-tiered "omics" makeups. Reproducible findings from the observational studies and diet intervention trials have lent preliminary but consistent evidence to support the fundamental role of gene-diet interactions in determining the individual variability in health outcomes including obesity and weight loss. Recent investigations suggest that the abundance and diversity of the gut microbiome may also modify the dietary effects; however, considerable instability in the results from the microbiome research has been noted. In addition, growing studies suggest that a complicated multiomics algorithm would be developed by incorporating the genome, epigenome, metabolome, proteome, and microbiome in predicting the individual variability in response to diets. Moreover, precision nutrition would also scrutinize the role of biological (circadian) rhythm in determining the individual variability of dietary effects. The evidence gathered from precision nutrition research will be the basis for constructing precision health dietary recommendations, which hold great promise to help individuals and their health care providers create precise and effective diet plans for precision health in the future.

TSABL: Trait Specific Annotation Based Locus predictor

BACKGROUND

The majority of Genome Wide Associate Study (GWAS) loci fall in the non-coding genome, making causal variants difficult to identify and study. We hypothesized that the regulatory features underlying causal variants are biologically specific, identifiable from data, and that the regulatory architecture that influences one trait is distinct compared to biologically unrelated traits.

RESULTS

To better characterize and identify these variants, we used publicly available GWAS loci and genomic annotations to build 17 Trait Specific Annotation Based Locus (TSABL) predictors to identify differences between GWAS loci associated with different phenotypic trait groups. We used a penalized binomial logistic regression model to select trait relevant annotations and tested all models on a holdout set of loci not used for training in any trait. We were able to successfully build models for autoimmune, electrocardiogram, lipid, platelet, red blood cell, and white blood cell trait groups. We used these models both to prioritize variants in existing loci and to identify new genomic regions of interest.

CONCLUSIONS

We found that TSABL models identified biologically relevant regulatory features, and anticipate their future use to enhance the design and interpretation of genetic studies.

The human "contaminome": bacterial, viral, and computational contamination in whole genome sequences from 1000 families

The unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals of both human infection and contamination. Using unmapped and poorly aligned reads from whole genome sequences (WGS) of over 1000 families and nearly 5000 individuals, we present insights into common viral, bacterial, and computational contamination that plague whole genome sequencing studies. We present several notable results: (1) In addition to known contaminants such as Epstein-Barr virus and phiX, sequences from whole blood and lymphocyte cell lines contain many other contaminants, likely originating from storage, prep, and sequencing pipelines. (2) Sequencing plate and biological sample source of a sample strongly influence contamination profile. And, (3) Y-chromosome fragments not on the human reference genome commonly mismap to bacterial reference genomes. Both experiment-derived and computational contamination is prominent in next-generation sequencing data. Such contamination can compromise results from WGS as well as metagenomics studies, and standard protocols for identifying and removing contamination should be developed to ensure the fidelity of sequencing-based studies.

SpG and SpRY variants expand the CRISPR toolbox for genome editing in zebrafish

Precise genetic modifications in model organisms are essential for biomedical research. The recent development of PAM-less base editors makes it possible to assess the functional impact and pathogenicity of nucleotide mutations in animals. Here we first optimize SpG and SpRY systems in zebrafish by purifying protein combined with synthetically modified gRNA. SpG shows high editing efficiency at NGN PAM sites, whereas SpRY efficiently edit PAM-less sites in the zebrafish genome. Then, we generate the SpRY-mediated cytosine base editor SpRY-CBE4max and SpRY-mediated adenine base editor zSpRY-ABE8e. Both target relaxed PAM with up to 96% editing efficiency and high product purity. With these tools, some previously inaccessible disease-relevant genetic variants are generated in zebrafish, supporting the utility of high-resolution targeting across genome-editing applications. Our study significantly improves CRISPR-Cas targeting in the genomic landscape of zebrafish, promoting the application of this model organism in revealing gene function, physiological mechanisms, and disease pathogenesis.

Advances in Single-Cell Multi-Omics and Application in Cardiovascular Research

With the development of ever more powerful and versatile high-throughput sequencing techniques and innovative ways to capture single cells, mapping the multicellular tissues at the single-cell level is becoming routine practice. However, it is still challenging to depict the epigenetic landscape of a single cell, especially the genome-wide chromatin accessibility, histone modifications, and DNA methylation. We summarize the most recent methodologies to profile these epigenetic marks at the single-cell level. We also discuss the development and advancement of several multi-omics sequencing technologies from individual cells. Advantages and limitations of various methods to compare and integrate datasets obtained from different sources are also included with specific practical notes. Understanding the heart tissue at single-cell resolution and multi-modal levels will help to elucidate the cell types and states involved in physiological and pathological events during heart development and disease. The rich information produced from single-cell multi-omics studies will also promote the research of heart regeneration and precision medicine on heart diseases.

Coming of Age: Human Genomics and the Cancer-Immune Set Point

Cancer is largely a disease of the tumor cell genome. As a result, the majority of genetics research in oncology has concentrated on the role of tumor somatic mutations, as well as inherited risk variants, in disease susceptibility and response to targeted treatments. The advent and success of cancer immunotherapies, however, have opened new perspectives for the investigation of the role of inherited genetic variation in codetermining outcome and safety. It is increasingly likely that the entirety of germline genetic variation involved in regulating immune responses accounts for a significant fraction of the observed variability in responses to cancer immunotherapies. Although germline genetic data from patients treated with cancer immunotherapies are still scarce, this line of research benefits from a vast body of knowledge derived from studies into autoimmune and infectious disease phenotypes, thus not requiring a start from a blank slate. Here, we discuss how a thorough investigation of genomic variation relevant for individuals' variability in (auto)immune responses can contribute to the discovery of novel treatment approaches and drug targets, and yield predictive biomarkers to stratify cancer patient populations in precision and personalized medicine settings.

Targeted RNAseq Improves Clinical Diagnosis of Very Early-Onset Pediatric Immune Dysregulation

Despite increased use of whole exome sequencing (WES) for the clinical analysis of rare disease, overall diagnostic yield for most disorders hovers around 30%. Previous studies of mRNA have succeeded in increasing diagnoses for clearly defined disorders of monogenic inheritance. We asked if targeted RNA sequencing could provide similar benefits for primary immunodeficiencies (PIDs) and very early-onset inflammatory bowel disease (VEOIBD), both of which are difficult to diagnose due to high heterogeneity and variable severity. We performed targeted RNA sequencing of a panel of 260 immune-related genes for a cohort of 13 patients (seven suspected PID cases and six VEOIBD) and analyzed variants, splicing, and exon usage. Exonic variants were identified in seven cases, some of which had been previously prioritized by exome sequencing. For four cases, allele specific expression or lack thereof provided additional insights into possible disease mechanisms. In addition, we identified five instances of aberrant splicing associated with four variants. Three of these variants had been previously classified as benign in ClinVar based on population frequency. Digenic or oligogenic inheritance is suggested for at least two patients. In addition to validating the use of targeted RNA sequencing, our results show that rare disease research will benefit from incorporating contributing genetic factors into the diagnostic approach.

Association of Pathogenic Variants in Hereditary Cancer Genes With Multiple Diseases

Importance

Knowledge about the spectrum of diseases associated with hereditary cancer syndromes may improve disease diagnosis and management for patients and help to identify high-risk individuals.

Objective

To identify phenotypes associated with hereditary cancer genes through a phenome-wide association study.

Design, Setting, and Participants

This phenome-wide association study used health data from participants in 3 cohorts. The Electronic Medical Records and Genomics Sequencing (eMERGEseq) data set recruited predominantly healthy individuals from 10 US medical centers from July 16, 2016, through February 18, 2018, with a mean follow-up through electronic health records (EHRs) of 12.7 (7.4) years. The UK Biobank (UKB) cohort recruited participants from March 15, 2006, through August 1, 2010, with a mean (SD) follow-up of 12.4 (1.0) years. The Hereditary Cancer Registry (HCR) recruited patients undergoing clinical genetic testing at Vanderbilt University Medical Center from May 1, 2012, through December 31, 2019, with a mean (SD) follow-up through EHRs of 8.8 (6.5) years.

Exposures

Germline variants in 23 hereditary cancer genes. Pathogenic and likely pathogenic variants for each gene were aggregated for association analyses.

Main Outcomes and Measures

Phenotypes in the eMERGEseq and HCR cohorts were derived from the linked EHRs. Phenotypes in UKB were from multiple sources of health-related data.

Results

A total of 214 020 participants were identified, including 23 544 in eMERGEseq cohort (mean [SD] age, 47.8 [23.7] years; 12 611 women [53.6%]), 187 234 in the UKB cohort (mean [SD] age, 56.7 [8.1] years; 104 055 [55.6%] women), and 3242 in the HCR cohort (mean [SD] age, 52.5 [15.5] years; 2851 [87.9%] women). All 38 established gene-cancer associations were replicated, and 19 new associations were identified. These included the following 7 associations with neoplasms: CHEK2 with leukemia (odds ratio [OR], 3.81 [95% CI, 2.64-5.48]) and plasma cell neoplasms (OR, 3.12 [95% CI, 1.84-5.28]), ATM with gastric cancer (OR, 4.27 [95% CI, 2.35-7.44]) and pancreatic cancer (OR, 4.44 [95% CI, 2.66-7.40]), MUTYH (biallelic) with kidney cancer (OR, 32.28 [95% CI, 6.40-162.73]), MSH6 with bladder cancer (OR, 5.63 [95% CI, 2.75-11.49]), and APC with benign liver/intrahepatic bile duct tumors (OR, 52.01 [95% CI, 14.29-189.29]). The remaining 12 associations with nonneoplastic diseases included BRCA1/2 with ovarian cysts (OR, 3.15 [95% CI, 2.22-4.46] and 3.12 [95% CI, 2.36-4.12], respectively), MEN1 with acute pancreatitis (OR, 33.45 [95% CI, 9.25-121.02]), APC with gastritis and duodenitis (OR, 4.66 [95% CI, 2.61-8.33]), and PTEN with chronic gastritis (OR, 15.68 [95% CI, 6.01-40.92]).

Conclusions and Relevance

The findings of this genetic association study analyzing the EHRs of 3 large cohorts suggest that these new phenotypes associated with hereditary cancer genes may facilitate early detection and better management of cancers. This study highlights the potential benefits of using EHR data in genomic medicine.

Legal Implications of Stroke Biobanking and Genomics Research in Sub-Saharan Africa

Stroke is a major cause of death in Sub-Saharan Africa (SSA) and genetic factors appear to play a part. This has led to stroke biobanking and genomics research in SSA. Existing stroke studies have focused on causes, incidence rates, fatalities and effects. However, scant attention has been paid to the legal issues in stroke biobanking and genomics research in the sub-region. Therefore, this article examines the legal implications of stroke biobanking and genomics research in SSA. The article adopts a textual analysis of primary and secondary sources in law. It reports that there are laws from the perspectives of human right, the common law, and intellectual property. However, there are gaps to be filled. The article therefore argues for legislative intervention. It concludes that pending the time the statute will be enacted, genomics researchers in Africa should adopt the ethical guidelines prepared by Human Heredity and Health in Africa (H3 Africa).

Combining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity

Disease-associated single-nucleotide polymorphisms (SNPs) generally do not implicate target genes, as most disease SNPs are regulatory. Many SNP-to-gene (S2G) linking strategies have been developed to link regulatory SNPs to the genes that they regulate in cis. Here, we developed a heritability-based framework for evaluating and combining different S2G strategies to optimize their informativeness for common disease risk. Our optimal combined S2G strategy (cS2G) included seven constituent S2G strategies and achieved a precision of 0.75 and a recall of 0.33, more than doubling the recall of any individual strategy. We applied cS2G to fine-mapping results for 49 UK Biobank diseases/traits to predict 5,095 causal SNP-gene-disease triplets (with S2G-derived functional interpretation) with high confidence. We further applied cS2G to provide an empirical assessment of disease omnigenicity; we determined that the top 1% of genes explained roughly half of the SNP heritability linked to all genes and that gene-level architectures vary with variant allele frequency.

Triangulating variation in the population to define mechanisms for precision management of genetic disease

To understand mechanistically how the protein fold is shaped by therapeutics to inform precision management of disease, we developed variation-capture (VarC) mapping. VarC triangulates sparse sequence variation information found in the population using Gaussian process regression (GPR)-based machine learning to define the combined pairwise-residue interactions contributing to dynamic protein function in the individual in response to therapeutics. Using VarC mapping, we now reveal the pairwise-residue covariant relationships across the entire protein fold of cystic fibrosis (CF) transmembrane conductance regulator (CFTR) to define the molecular mechanisms of clinically approved CF chemical modulators. We discover an energetically destabilized covariant core containing a di-acidic YKDAD endoplasmic reticulum (ER) exit code that is only weakly corrected by current therapeutics. Our results illustrate that VarC provides a generalizable tool to triangulate information from genetic variation in the population to mechanistically discover therapeutic strategies that guide precision management of the individual.

Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation

The Annotation Query (AnnoQ) (http://annoq.org/) is designed to provide comprehensive and up-to-date functional annotations for human genetic variants. The system is supported by an annotation database with ∼39 million human variants from the Haplotype Reference Consortium (HRC) pre-annotated with sequence feature annotations by WGSA and functional annotations to Gene Ontology (GO) and pathways in PANTHER. The database operates on an optimized Elasticsearch framework to support real-time complex searches. This implementation enables users to annotate data with the most up-to-date functional annotations via simple queries instead of setting up individual tools. A web interface allows users to interactively browse the annotations, annotate variants and search variant data. Its easy-to-use interface and search capabilities are well-suited for scientists with fewer bioinformatics skills such as bench scientists and statisticians. AnnoQ also has an API for users to access and annotate the data programmatically. Packages for programming languages, such as the R package, are available for users to embed the annotation queries in their scripts. AnnoQ serves researchers with a wide range of backgrounds and research interests as an integrated annotation platform.

Large-scale chromatin reorganization reactivates placenta-specific genes that drive cellular aging

Nuclear deformation, a hallmark frequently observed in senescent cells, is presumed to be associated with the erosion of chromatin organization at the nuclear periphery. However, how such gradual changes in higher-order genome organization impinge on local epigenetic modifications to drive cellular mechanisms of aging has remained enigmatic. Here, through large-scale epigenomic analyses of isogenic young, senescent, and progeroid human mesenchymal progenitor cells (hMPCs), we delineate a hierarchy of integrated structural state changes that manifest as heterochromatin loss in repressive compartments, euchromatin weakening in active compartments, switching in interfacing topological compartments, and increasing epigenetic entropy. We found that the epigenetic de-repression unlocks the expression of pregnancy-specific beta-1 glycoprotein (PSG) genes that exacerbate hMPC aging and serve as potential aging biomarkers. Our analyses provide a rich resource for uncovering the principles of epigenomic landscape organization and its changes in cellular aging and for identifying aging drivers and intervention targets with a genome-topology-based mechanism.

Large-Scale Chromatin Rearrangements in Cancer

Simple Summary

Cancers have many genetic mutations such as nucleotide changes, deletions, amplifications, and chromosome gains or losses. Some of these genetic alterations directly contribute to the initiation and progression of tumors. In parallel to these genetic changes, cancer cells acquire modifications to their chromatin landscape, i.e., to the marks that are carried by DNA and the histone proteins it is associated with. These “epimutations” have consequences for gene expression and genome stability, and also contribute to tumoral initiation and progression. Some of these chromatin changes are very local, affecting just one or a few genes. In contrast, some chromatin alterations observed in cancer are more widespread and affect a large part of the genome. In this review, we present different types of large-scale chromatin rearrangements in cancer, explain how they may occur, and why they are relevant for cancer diagnosis and treatment.

Abstract

Epigenetic abnormalities are extremely widespread in cancer. Some of them are mere consequences of transformation, but some actively contribute to cancer initiation and progression; they provide powerful new biological markers, as well as new targets for therapies. In this review, we examine the recent literature and focus on one particular aspect of epigenome deregulation: large-scale chromatin changes, causing global changes of DNA methylation or histone modifications. After a brief overview of the one-dimension (1D) and three-dimension (3D) epigenome in healthy cells and of its homeostasis mechanisms, we use selected examples to describe how many different events (mutations, changes in metabolism, and infections) can cause profound changes to the epigenome and fuel cancer. We then present the consequences for therapies and briefly discuss the role of single-cell approaches for the future progress of the field.

Evaluating human genetic support for hypothesized metabolic disease genes

We investigate the extent to which human genetic data are incorporated into studies that hypothesize novel links between genes and metabolic disease. To lower the barriers to using genetic data, we present an approach to enable researchers to evaluate human genetic support for experimentally determined hypotheses.

Whole-genome sequencing identifies rare missense variants of WNT16 and ERVW-1 causing the systemic lupus erythematosus

Systemic lupus erythematosus (SLE, OMIM 152700) is a rare autoimmune disease with high heritability that affects ~0.1% of the population. Previous studies have revealed several common variants with small effects in European and East Asian SLE patients. However, there is still no rare variant study on Chinese SLE patients using the whole-genome sequencing technology (WGS). Here, we designed a family based WGS study to identify novel rare variants with large effects. Based on large-scale allele frequency data from the gnomAD database, we identified rare protein-coding gene variants with disruptive and sequence-altering impacts in SLE patients. We found that the burden of rare variants was significantly higher than that of common variants in patients, suggesting a larger effect of rare variants on the SLE pathogenesis. We identified the pathogenic risk of rare missense variants with significant odds ratios (p < 0.05) in two genes, including WNT16 (NC_000007.14:g.121329757G > C, NP_057171.2:p.(Ala86Pro) and 7 g.121329760G > C, NP_057171.2:p.(Ala87Pro)), which explains five out of seven patients covering all three families but are absent from all controls, and ERVW-1 (NC_000007.14:g.92469882A > G, NP_001124397.1:p.(Leu167Pro), rs74545114; NC_000007.14:g.92469907G > A, NP_001124397.1:p.(Arg159Cys), rs201142302; NC_000007.14:g.92469919G > A, NP_001124397.1:p.(His155Tyr), rs199552228), which explains the other two patients. None of these variants were identified in any of the controls. These associations are supported by known gene expression studies in SLE patients based on literature review. We further tested the wild and mutant types using the luciferase assays and qPCR in cells. We found that WNT16 can activate the canonical Wnt/β-catenin pathway while the mutant cannot. Additionally, the wild ERVW-1 expression can be significantly up-regulated by cAMP while the mutant cannot. Our study provides the first direct genetic and in vitro evidence for the pathogenic risk of mutant WNT16 and ERVW-1, which may facilitate the design of precision therapy for SLE.

A leukemia-protective germline variant mediates chromatin module formation via transcription factor nucleation

Non-coding variants coordinate transcription factor (TF) binding and chromatin mark enrichment changes over regions spanning >100 kb. These molecularly coordinated regions are named "variable chromatin modules" (VCMs), providing a conceptual framework of how regulatory variation might shape complex traits. To better understand the molecular mechanisms underlying VCM formation, here, we mechanistically dissect a VCM-modulating noncoding variant that is associated with reduced chronic lymphocytic leukemia (CLL) predisposition and disease progression. This common, germline variant constitutes a 5-bp indel that controls the activity of an AXIN2 gene-linked VCM by creating a MEF2 binding site, which, upon binding, activates a super-enhancer-like regulatory element. This triggers a large change in TF binding activity and chromatin state at an enhancer cluster spanning >150 kb, coinciding with subtle, long-range chromatin compaction and robust AXIN2 up-regulation. Our results support a model in which the indel acts as an AXIN2 VCM-activating TF nucleation event, which modulates CLL pathology.

Spatial covariance analysis reveals the residue-by-residue thermodynamic contribution of variation to the CFTR fold

Although the impact of genome variation on the thermodynamic properties of function on the protein fold has been studied in vitro, it remains a challenge to assign these relationships across the entire polypeptide sequence in vivo. Using the Gaussian process regression based principle of Spatial CoVariance, we globally assign on a residue-by-residue basis the biological thermodynamic properties that contribute to the functional fold of CFTR in the cell. We demonstrate the existence of a thermodynamically sensitive region of the CFTR fold involving the interface between NBD1 and ICL4 that contributes to its export from endoplasmic reticulum. At the cell surface a new set of residues contribute uniquely to the management of channel function. These results support a general 'quality assurance' view of global protein fold management as an SCV principle describing the differential pre- and post-ER residue interactions contributing to compartmentalization of the energetics of the protein fold for function. Our results set the stage for future analyses of the quality systems managing protein sequence-to-function-to-structure broadly encompassing genome design leading to protein function in complex cellular relationships responsible for diversity and fitness in biology in response to the environment.

Identification and Somatic Characterization of the Germline PTEN Promoter Variant rs34149102 in a Family with Gastrointestinal and Breast Tumors

Genetic variants located in non-coding regions can affect processes that regulate protein expression, functionally contributing to human disease. Germline heterozygous mutations in the non-coding region of the PTEN gene have been previously identified in patients with PTEN hamartoma tumor syndrome (PHTS) diagnosed with breast, thyroid, and/or endometrial cancer. In this study, we report a PTEN promoter variant (rs34149102 A allele) that was identified by direct sequencing in an Italian family with a history of gastroesophageal junction (GEJ) adenocarcinoma and breast cancer. In order to investigate the putative functional role of the rs34149102 A allele variant, we evaluated the status of PTEN alterations at the somatic level. We found that PTEN protein expression was absent in the GEJ adenocarcinoma tissue of the index case. Moreover, we detected the occurrence of copy number loss involving the PTEN rs34149102 major C allele in tumor tissue, revealing that the second allele was somatically inactivated. This variant is located within an active regulatory region of the PTEN core promoter, and in silico analysis suggests that it may affect the binding of the nuclear transcription factor MAZ and hence PTEN expression. Overall, these results reveal the functional role of the PTEN promoter rs34149102 A allele variant in the modulation of PTEN protein expression and highlight its contribution to hereditary cancer risk.

Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction

Single nucleotide variants (SNVs) are prevalent genetic factors shaping individual trait profiles and disease susceptibility. The recent development and optimizations of base editors, rubber and pencil genome editing tools now promise to enable direct functional assessment of SNVs in model organisms. However, the lack of bioinformatic tools aiding target prediction limits the application of base editing in vivo. Here, we provide a framework for adenine and cytosine base editing in medaka (Oryzias latipes) and zebrafish (Danio rerio), ideal for scalable validation studies. We developed an online base editing tool ACEofBASEs (a careful evaluation of base-edits), to facilitate decision-making by streamlining sgRNA design and performing off-target evaluation. We used state-of-the-art adenine (ABE) and cytosine base editors (CBE) in medaka and zebrafish to edit eye pigmentation genes and transgenic GFP function with high efficiencies. Base editing in the genes encoding troponin T and the potassium channel ERG faithfully recreated known cardiac phenotypes. Deep-sequencing of alleles revealed the abundance of intended edits in comparison to low levels of insertion or deletion (indel) events for ABE8e and evoBE4max. We finally validated missense mutations in novel candidate genes of congenital heart disease (CHD) dapk3, ube2b, usp44, and ptpn11 in F0 and F1 for a subset of these target genes with genotype-phenotype correlation. This base editing framework applies to a wide range of SNV-susceptible traits accessible in fish, facilitating straight-forward candidate validation and prioritization for detailed mechanistic downstream studies.

Identification of Rare Loss-of-Function Genetic Variation Regulating Body Fat Distribution

CONTEXT

Biological and translational insights from large-scale, array-based genetic studies of fat distribution, a key determinant of metabolic health, have been limited by the difficulty in linking predominantly noncoding variants to specific gene targets. Rare coding variant analyses provide greater confidence that a specific gene is involved, but do not necessarily indicate whether gain or loss of function (LoF) would be of most therapeutic benefit.

OBJECTIVE

This work aimed to identify genes/proteins involved in determining fat distribution.

METHODS

We combined the power of genome-wide analysis of array-based rare, nonsynonymous variants in 450 562 individuals in the UK Biobank with exome-sequence-based rare LoF gene burden testing in 184 246 individuals.

RESULTS

The data indicate that the LoF of 4 genes (PLIN1 [LoF variants, P = 5.86 × 10-7], INSR [LoF variants, P = 6.21 × 10-7], ACVR1C [LoF + moderate impact variants, P = 1.68 × 10-7; moderate impact variants, P = 4.57 × 10-7], and PDE3B [LoF variants, P = 1.41 × 10-6]) is associated with a beneficial effect on body mass index-adjusted waist-to-hip ratio and increased gluteofemoral fat mass, whereas LoF of PLIN4 (LoF variants, P = 5.86 × 10-7 adversely affects these parameters. Phenotypic follow-up suggests that LoF of PLIN1, PDE3B, and ACVR1C favorably affects metabolic phenotypes (eg, triglycerides [TGs] and high-density lipoprotein [HDL] cholesterol concentrations) and reduces the risk of cardiovascular disease, whereas PLIN4 LoF has adverse health consequences. INSR LoF is associated with lower TG and HDL levels but may increase the risk of type 2 diabetes.

CONCLUSION

This study robustly implicates these genes in the regulation of fat distribution, providing new and in some cases somewhat counterintuitive insight into the potential consequences of targeting these molecules therapeutically.

Characterization of intrinsically disordered regions in proteins informed by human genetic diversity

All proteomes contain both proteins and polypeptide segments that don’t form a defined three-dimensional structure yet are biologically active—called intrinsically disordered proteins and regions (IDPs and IDRs). Most of these IDPs/IDRs lack useful functional annotation limiting our understanding of their importance for organism fitness. Here we characterized IDRs using protein sequence annotations of functional sites and regions available in the UniProt knowledgebase (“UniProt features”: active site, ligand-binding pocket, regions mediating protein-protein interactions, etc.). By measuring the statistical enrichment of twenty-five UniProt features in 981 IDRs of 561 human proteins, we identified eight features that are commonly located in IDRs. We then collected the genetic variant data from the general population and patient-based databases and evaluated the prevalence of population and pathogenic variations in IDPs/IDRs. We observed that some IDRs tolerate 2 to 12-times more single amino acid-substituting missense mutations than synonymous changes in the general population. However, we also found that 37% of all germline pathogenic mutations are located in disordered regions of 96 proteins. Based on the observed-to-expected frequency of mutations, we categorized 34 IDRs in 20 proteins (DDX3X, KIT, RB1, etc.) as intolerant to mutation. Finally, using statistical analysis and a machine learning approach, we demonstrate that mutation-intolerant IDRs carry a distinct signature of functional features. Our study presents a novel approach to assign functional importance to IDRs by leveraging the wealth of available genetic data, which will aid in a deeper understating of the role of IDRs in biological processes and disease mechanisms.

Genetic associations of protein-coding variants in human disease

Genome-wide association studies (GWAS) have identified thousands of genetic variants linked to the risk of human disease. However, GWAS have so far remained largely underpowered in relation to identifying associations in the rare and low-frequency allelic spectrum and have lacked the resolution to trace causal mechanisms to underlying genes1. Here we combined whole-exome sequencing in 392,814 UK Biobank participants with imputed genotypes from 260,405 FinnGen participants (653,219 total individuals) to conduct association meta-analyses for 744 disease endpoints across the protein-coding allelic frequency spectrum, bridging the gap between common and rare variant studies. We identified 975 associations, with more than one-third being previously unreported. We demonstrate population-level relevance for mutations previously ascribed to causing single-gene disorders, map GWAS associations to likely causal genes, explain disease mechanisms, and systematically relate disease associations to levels of 117 biomarkers and clinical-stage drug targets. Combining sequencing and genotyping in two population biobanks enabled us to benefit from increased power to detect and explain disease associations, validate findings through replication and propose medical actionability for rare genetic variants. Our study provides a compendium of protein-coding variant associations for future insights into disease biology and drug discovery.

Towards Next-Generation Sequencing (NGS)-Based Newborn Screening: A Technical Study to Prepare for the Challenges Ahead

Newborn screening (NBS) aims to identify neonates with severe conditions for whom immediate treatment is required. Currently, a biochemistry-first approach is used to identify these disorders, which are predominantly inherited meta1bolic disorders (IMD). Next-generation sequencing (NGS) is expected to have some advantages over the current approach, for example the ability to detect IMDs that meet all screening criteria but lack an identifiable biochemical footprint. We have now designed a technical study to explore the use of NGS techniques as a first-tier approach in NBS. Here, we describe the aim and set-up of the NGS-first for the NBS (NGSf4NBS) project, which will proceed in three steps. In Step 1, we will identify IMDs eligible for NGS-first testing, based on treatability. In Step 2, we will investigate the feasibility, limitations and comparability of different technical NGS approaches and analysis workflows for NBS, eventually aiming to develop a rapid NGS-based workflow. Finally, in Step 3, we will prepare for the incorporation of this workflow into the existing Dutch NBS program and propose a protocol for referral of a child after a positive NGS test result. The results of this study will be the basis for an additional analytical route within NBS that will be further studied for its applicability within the NBS program, e.g., regarding the ethical, legal, financial and social implications.

The research landscape of tuberous sclerosis complex-associated neuropsychiatric disorders (TAND)-a comprehensive scoping review

BACKGROUND

Tuberous sclerosis complex (TSC)-associated neuropsychiatric disorders (TAND) is an umbrella term for the behavioural, psychiatric, intellectual, academic, neuropsychological and psychosocial manifestations of TSC. Although TAND affects 90% of individuals with TSC during their lifetime, these manifestations are relatively under-assessed, under-treated and under-researched. We performed a comprehensive scoping review of all TAND research to date (a) to describe the existing TAND research landscape and (b) to identify knowledge gaps to guide future TAND research.

METHODS

The study was conducted in accordance with stages outlined within the Arksey and O'Malley scoping review framework. Ten research questions relating to study characteristics, research design and research content of TAND levels and clusters were examined.

RESULTS

Of the 2841 returned searches, 230 articles published between 1987 and 2020 were included (animal studies = 30, case studies = 47, cohort studies = 153), with more than half published since the term TAND was coined in 2012 (118/230; 51%). Cohort studies largely involved children and/or adolescents (63%) as opposed to older adults (16%). Studies were represented across 341 individual research sites from 45 countries, the majority from the USA (89/341; 26%) and the UK (50/341; 15%). Only 48 research sites (14%) were within low-middle income countries (LMICs). Animal studies and case studies were of relatively high/high quality, but cohort studies showed significant variability. Of the 153 cohort studies, only 16 (10%) included interventions. None of these were non-pharmacological, and only 13 employed remote methodologies (e.g. telephone interviews, online surveys). Of all TAND clusters, the autism spectrum disorder-like cluster was the most widely researched (138/230; 60%) and the scholastic cluster the least (53/200; 27%).

CONCLUSIONS

Despite the recent increase in TAND research, studies that represent participants across the lifespan, LMIC research sites and non-pharmacological interventions were identified as future priorities. The quality of cohort studies requires improvement, to which the use of standardised direct behavioural assessments may contribute. In human studies, the academic level in particular warrants further investigation. Remote technologies could help to address many of the TAND knowledge gaps identified.

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.

Symbolic Legislation and the Regulation of Stroke Biobanking and Genomics Research in Sub-Saharan Africa

Stroke is a major cause of death in Sub-Saharan Africa (SSA) and genetic factors appear to play a part. This led to the development of stroke bio-banking and genomics research in SSA. Existing stroke studies have focused on causes, incidence rates, fatalities and effects. However, scant attention has been paid to the legal issues about stroke bio-banking and genomics research in the sub-region. Therefore, this article examines how genomics research and stroke bio-banking in SSA can be regulated through legislation. The article reports that there are germane issues to be addressed such as appropriate consent model, commercial use of biological samples, ownership right in biological samples and return of research results but that the position of the law on these issues is not satisfactory because there are no statute directly regulating them while existing regulations in these countries are either absent, outdated, conservative or difficult to navigate. The article therefore applies the theory of symbolic legislation and argues for legislative intervention through positive symbolic approach. It recommends that the statute to be enacted should only address policy issues by way of legal rules without being detailed while the understanding of the rules should be fostered in explanatory notes. The explanatory notes should contain examples borne of decided cases, cases settled out of court and the ethical guidelines prepared by Human Heredity and Health in Africa (H3 Africa). Where they are inadequate, recourse may be had to other ethical guidelines subject to the demands of local circumstances.

Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy

Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology. Additionally, we discuss the strategy, challenge, and promise of gene therapy. As computational and statistical approaches continue to improve, we will have an opportunity to translate human genetic findings into personalized health care.

Developmental disorders caused by haploinsufficiency of transcriptional regulators: a perspective based on cell fate determination

Many human birth defects and neurodevelopmental disorders are caused by loss-of-function mutations in a single copy of transcription factor (TF) and chromatin regulator genes. Although this dosage sensitivity has long been known, how and why haploinsufficiency (HI) of transcriptional regulators leads to developmental disorders (DDs) is unclear. Here I propose the hypothesis that such DDs result from defects in cell fate determination that are based on disrupted bistability in the underlying gene regulatory network (GRN). Bistability, a crucial systems biology concept to model binary choices such as cell fate decisions, requires both positive feedback and ultrasensitivity, the latter often achieved through TF cooperativity. The hypothesis explains why dosage sensitivity of transcriptional regulators is an inherent property of fate decisions, and why disruption of either positive feedback or cooperativity in the underlying GRN is sufficient to cause disease. I present empirical and theoretical evidence in support of this hypothesis and discuss several issues for which it increases our understanding of disease, such as incomplete penetrance. The proposed framework provides a mechanistic, systems-level explanation of HI of transcriptional regulators, thus unifying existing theories, and offers new insights into outstanding issues of human disease. This article has an associated Future Leader to Watch interview with the author of the paper.

Validation and genetic heritability estimation of known type 2 diabetes related variants in the Korean population

Genome-wide association studies (GWASs) facilitated the discovery of countless disease-associated variants. However, GWASs have mostly been conducted in European ancestry samples. Recent studies have reported that these European-based association results may reduce disease prediction accuracy when applied in non-Europeans. Therefore, previously reported variants should be validated in non-European populations to establish reliable scientific evidence for precision medicine. In this study, we validated known associations with type 2 diabetes (T2D) and related metabolic traits in 125,850 samples from a Korean population genotyped by the Korea Biobank Array (KBA). At the end of December 2020, there were 8,823 variants associated with glycemic traits, lipids, liver enzymes, and T2D in the GWAS catalog. Considering the availability of imputed datasets in the KBA genome data, publicly available East-Asian T2D summary statistics, and the linkage disequilibrium among the variants (r2 < 0.2), 2,900 independent variants were selected for further analysis. Among these, 1,837 variants (63.3%) were statistically significant (p ≤ 0.05). Most of the non-replicated variants (n = 1,063) showed insufficient statistical power and decreased minor allele frequencies compared with the replicated variants. Moreover, most of known variants showed <10% genetic heritability. These results could provide valuable scientific evidence for future study designs, the current power of GWASs, and future applications in precision medicine in the Korean population.

Improving one-step scarless genome editing in Drosophila melanogaster by combining ovoD co-CRISPR selection with sgRNA target site masking

The precise and rapid construction of alleles through CRISPR/Cas9-mediated genome engineering renders Drosophila melanogaster a powerful animal system for molecular structure–function analyses and human disease models. Application of the ovo^D co-selection method offers expedited generation and enrichment of scarlessly edited alleles without the need for linked transformation markers, which specifically in the case of exon editing can impact allele usability. However, we found that knockin procedures by homology-directed repair (HDR) under ovo^D co-selection resulted in low transformation efficiency. This is likely due to repeated rounds of Cas9 cleavage of HDR donor and/or engineered genomic locus DNA, as noted for other CRISPR/Cas9 editing strategies before, impeding the recovery of correctly edited alleles. Here we provide a one-step protocol to improve the generation of scarless alleles by ovo^D-co-selection with single-guide RNA (sgRNA) binding site masking. Using this workflow, we constructed human disease alleles for two Drosophila genes, unc-13/CG2999 and armadillo/CG11579. We show and quantify how a known countermeasure, the insertion of silent point mutations into protospacer adjacent motif (PAM) or sgRNA homology regions, can potently suppress unintended sequence modifications during CRISPR/Cas9 genome editing of D. melanogaster under ovo^D co-selection. This strongly increased the recovery frequency of disease alleles.

Appraisal of Gene-Environment Interactions in GWAS for Evidence-Based Precision Nutrition Implementation

PURPOSE OF REVIEW

This review aims to analyse the currently reported gene-environment (G × E) interactions in genome-wide association studies (GWAS), involving environmental factors such as lifestyle and dietary habits related to metabolic syndrome phenotypes. For this purpose, the present manuscript reviews the available GWAS registered on the GWAS Catalog reporting the interaction between environmental factors and metabolic syndrome traits.

RECENT FINDINGS

Advances in omics-related analytical and computational approaches in recent years have led to a better understanding of the biological processes underlying these G × E interactions. A total of 42 GWAS were analysed, reporting over 300 loci interacting with environmental factors. Alcohol consumption, sleep time, smoking habit and physical activity were the most studied environmental factors with significant G × E interactions. The implementation of more comprehensive GWAS will provide a better understanding of the metabolic processes that determine individual responses to environmental exposures and their association with the development of chronic diseases such as obesity and the metabolic syndrome. This will facilitate the development of precision approaches for better prevention, management and treatment of these diseases.

Advances in profiling chromatin architecture shed light on the regulatory dynamics underlying brain disorders

Understanding the exquisitely complex nature of the three-dimensional organization of the genome and how it affects gene regulation remains a central question in biology. Recent advances in sequencing- and imaging-based approaches in decoding the three-dimensional chromatin landscape have enabled a systematic characterization of gene regulatory architecture. In this review, we outline how chromatin architecture provides a reference atlas to predict the functional consequences of non-coding variants associated with human traits and disease. High-throughput perturbation assays such as massively parallel reporter assays (MPRA) and CRISPR-based genome engineering in combination with a reference atlas opened an avenue for going beyond observational studies to experimentally validating the regulatory principles of the genome. We conclude by providing a suggested path forward by calling attention to barriers that can be addressed for a more complete understanding of the regulatory landscape of the human brain.

A systematic review and analysis of the use of polygenic scores in pharmacogenomics

Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

Iron homeostasis pathway DNA methylation trajectories reveal a role for STEAP3 metalloreductase in patient outcomes after aneurysmal subarachnoid hemorrhage

BACKGROUND

Following aneurysmal subarachnoid hemorrhage (aSAH), the brain is susceptible to ferroptosis, a type of iron-dependent cell death. Therapeutic intervention targeting the iron homeostasis pathway shows promise for mitigating ferroptosis and improving recovery in animal models, but little work has been conducted in humans. DNA methylation (DNAm) plays a key role in gene expression and brain function, plasticity, and injury recovery, making it a potentially useful biomarker of outcomes or therapeutic target for intervention. Therefore, in this longitudinal, observational study, we examined the relationships between trajectories of DNAm in candidate genes related to iron homeostasis and acute (cerebral vasospasm and delayed cerebral ischemia) and long-term (Glasgow Outcome Scale [GOS, unfavorable = 1-3] and death) patient outcomes after aSAH.

RESULTS

Longitudinal, genome-wide DNAm data were generated from DNA extracted from post-aSAH cerebrospinal fluid (n = 260 participants). DNAm trajectories of 637 CpG sites in 36 candidate genes related to iron homeostasis were characterized over 13 days post-aSAH using group-based trajectory analysis, an unsupervised clustering method. Significant associations were identified between inferred DNAm trajectory groups at several CpG sites and acute and long-term outcomes. Among our results, cg25713625 in the STEAP3 metalloreductase gene (STEAP3) stood out. Specifically, in comparing the highest cg25713625 DNAm trajectory group with the lowest, we observed significant associations (i.e., based on p-values less than an empirical significance threshold) with unfavorable GOS at 3 and 12 months (OR = 11.7, p = 0.0006 and OR = 15.6, p = 0.0018, respectively) and death at 3 and 12 months (OR = 19.1, p = 0.0093 and OR = 12.8, p = 0.0041, respectively). These results were replicated in an independent sample (n = 100 participants) observing significant associations with GOS at 3 and 12 months (OR = 8.2, p = 0.001 and OR = 6.3, p = 0.0.0047, respectively) and death at 3 months (OR = 2.3, p = 0.008) and a suggestive association (i.e., p-value < 0.05 not meeting an empirical significance threshold) with death at 12 months (OR = 2.0, p = 0.0272). In both samples, an additive effect of the DNAm trajectory group was observed as the percentage of participants with unfavorable long-term outcomes increased substantially with higher DNAm trajectory groups.

CONCLUSION

Our results support a role for DNAm of cg25713625/STEAP3 in recovery following aSAH. Additional research is needed to further explore the role of DNAm of cg25713625/STEAP3 as a biomarker of unfavorable outcomes, or therapeutic target to improve outcomes, to translate these findings clinically.

A Genetic Map of the Modern Urban Society of Amsterdam

Genetic differences between individuals underlie susceptibility to many diseases. Genome-wide association studies (GWAS) have discovered many susceptibility genes but were often limited to cohorts of predominantly European ancestry. Genetic diversity between individuals due to different ancestries and evolutionary histories shows that this approach has limitations. In order to gain a better understanding of the associated genetic variation, we need a more global genomics approach including a greater diversity. Here, we introduce the Healthy Life in an Urban Setting (HELIUS) cohort. The HELIUS cohort consists of participants living in Amsterdam, with a level of diversity that reflects the Dutch colonial and recent migration past. The current study includes 10,283 participants with genetic data available from seven groups of inhabitants, namely, Dutch, African Surinamese, South-Asian Surinamese, Turkish, Moroccan, Ghanaian, and Javanese Surinamese. First, we describe the genetic variation and admixture within the HELIUS cohort. Second, we show the challenges during imputation when having a genetically diverse cohort. Third, we conduct a body mass index (BMI) and height GWAS where we investigate the effects of a joint analysis of the entire cohort and a meta-analysis approach for the different subgroups. Finally, we construct polygenic scores for BMI and height and compare their predictive power across the different ethnic groups. Overall, we give a comprehensive overview of a genetically diverse cohort from Amsterdam. Our study emphasizes the importance of a less biased and more realistic representation of urban populations for mapping genetic associations with complex traits and disease risk for all.