Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease

The Orphan Receptor GPR151: Discovery, Expression, and Emerging Biological Significance

G protein-coupled receptors (GPCRs) are among the most prominent druggable targets in the human genome, accounting for approximately 40% of marketed drugs. Despite this, current GPCR-targeted therapies address only about 10% of the GPCRs encoded in the genome. Expanding our knowledge of the remaining "orphan" GPCRs represents a critical frontier in drug discovery. GPR151 emerges as a compelling target due to its distinct expression in the habenula complex, spinal cord neurons, and dorsal root ganglia. This receptor is highly conserved across mammals and possesses orthologs in species such as zebrafish and chickens, underscoring its evolutionarily conserved role in fundamental mammalian processes. Although the precise function of GPR151 remains unknown, it has been strongly implicated in pain modulation and reward-seeking behavior. These attributes position GPR151 as a promising candidate for the development of targeted and specialized pharmacological therapies. This review summarizes the current literature on GPR151, including its discovery, structure, mechanisms, anatomical distribution, and functional roles, while also exploring potential directions for future research.

Leveraging genetics to understand ADAR1-mediated RNA editing in health and disease

Endogenous, long double-stranded RNA (dsRNA) can resemble viral dsRNA and be recognized by cytosolic dsRNA sensors, triggering autoimmunity. Genetic studies of rare, inherited human diseases and experiments using mouse models have established the importance of adenosine-to-inosine RNA editing by the enzyme adenosine deaminase acting on RNA 1 (ADAR1) as a critical safeguard against autoinflammatory responses to cellular dsRNA. More recently, human genetic studies have revealed that dsRNA editing and sensing mechanisms are involved in common inflammatory diseases, emphasizing the broader role of dsRNA in modulating immune responses and disease pathogenesis. These findings have highlighted the therapeutic potential of targeting dsRNA editing and sensing, as exemplified by the emergence of ADAR1 inhibition in cancer therapy.

Exploring the association between familial hemiplegic migraine genes (CACNA1A, ATP1A2 and SCN1A) with migraine and epilepsy: A UK Biobank exome-wide association study

BACKGROUND

Familial hemiplegic migraine (FHM) types 1-3 are associated with protein-altering genetic variants in CACNA1A, ATP1A2 and SCN1A, respectively. These genes have also been linked to epilepsy. Previous studies primarily focused on phenotypes, examining genetic variants in individuals with characteristic FHM symptoms. This study aimed to investigate the association of FHM genetic variation with migraine and epilepsy, utilizing a genotype-first approach.

METHODS

Whole-exome sequence data from 454,706 individuals from the UK Biobank were examined for self-reported and inpatient-diagnosed migraine and epilepsy. Carriers were compared with non-carriers in a burden analysis using logistic regression while accounting for age, biological sex and UK Biobank assessment center. A machine learning-based approach was employed to predict whether variants resulted in gain-of-function (GoF), loss-of-function (LoF) or neutral effects.

RESULTS

Heterozygous carriers of GoF CACNA1A variants, LoF ATP1A2 variants or neutral SCN1A variants were at increased risk of migraine. Homozygous carriers of neutral SCN1A variants were also associated with migraine but these carriers showed a reduced disease risk of epilepsy.

CONCLUSIONS

Heterozygous genotypes in all three FHM genes were associated with migraine but not epilepsy in this genotype-focused study. Homozygous SCN1A genotypes also showed increased disease risk of migraine, yet these carriers were protected against epilepsy.

STZ-induced hyperglycemia differentially influences mitochondrial distribution and morphology in the habenulointerpeduncular circuit

Introduction

Diabetes is a metabolic disorder of glucose homeostasis that is a significant risk factor for neurodegenerative diseases, such as Alzheimer's disease, as well as mood disorders, which often precede neurodegenerative conditions. We examined the medial habenulainterpeduncular nucleus (MHb-IPN), as this circuit plays crucial roles in mood regulation, has been linked to the development of diabetes after smoking, and is rich in cholinergic neurons, which are affected in other brain areas in Alzheimer's disease.

Methods

This study aimed to investigate the impact of streptozotocin (STZ)-induced hyperglycemia, a type 1 diabetes model, on mitochondrial and lipid homeostasis in 4% paraformaldehyde-fixed sections from the MHb and IPN of C57BL/6 J male mice, using a recently developed automated pipeline for mitochondrial analysis in confocal images. We examined different time points after STZ-induced diabetes onset to determine how the brain responded to chronic hyperglycemia, with the limitation that mitochondria and lipids were not examined with respect to cell type or intracellular location.

Results

Mitochondrial distribution and morphology differentially responded to hyperglycemia depending on time and brain area. Six weeks after STZ treatment, mitochondria in the ventral MHb and dorsal IPN increased in number and exhibited altered morphology, but no changes were observed in the lateral habenula (LHb) or ventral IPN. Strikingly, mitochondrial numbers returned to normal dynamics at 12 weeks. Both blood glucose level and glycated hemoglobin (HbA1C) correlated with mitochondrial dynamics in ventral MHb, whereas only HbA1C correlated in the IPN. We also examined lipid homeostasis using BODIPY staining for neutral lipids in this model given that diabetes is associated with disrupted lipid homeostasis. BODIPY staining intensity was unchanged in the vMHb of STZ-treated mice but increased in the IPN and VTA and decreased in the LHb at 12 weeks. Interestingly, areas that demonstrated changes in mitochondria had little change in lipid staining and vice versa.

Discussion

This study is the first to describe the specific impacts of diabetes on mitochondria in the MHb-IPN circuit and suggests that the cholinergic MHb is uniquely sensitive to diabetesinduced hyperglycemia. Further studies are needed to understand the functional and behavioral implications of these findings.

Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags

Balancing the tradeoff between quantity and quality of phenotypic data is critical in omics studies. Measurements below the limit of quantification (BLQ) are often tagged in quality control fields, but these flags are currently underutilized in human genetics studies. Extreme phenotype sampling is advantageous for mapping rare variant effects. We hypothesize that genetic drivers, along with environmental and technical factors, contribute to the presence of BLQ flags. Here, we introduce "hypometric genetics" (hMG) analysis and uncover a genetic basis for BLQ flags, indicating an additional source of genetic signal for genetic discovery, especially from phenotypic extremes. Applying our hMG approach to n = 227,469 UK Biobank individuals with metabolomic profiles, we reveal more than 5% heritability for BLQ flags and report biologically relevant associations, for example, at APOC3, APOA5, and PDE3B loci. For common variants, polygenic scores trained only for BLQ flags predict the corresponding quantitative traits with 91% accuracy, validating the genetic basis. For rare coding variant associations, we find an asymmetric 65.4% higher enrichment of metabolite-lowering associations for BLQ flags, highlighting the impact of putative loss-of-function variants with large effects on phenotypic extremes. Joint analysis of binarized BLQ flags and the corresponding quantitative metabolite measurements improves power in Bayesian rare variant aggregation tests, resulting in an average of 181% more prioritized genes. Our approach is broadly applicable to omics profiling. Overall, our results underscore the benefit of integrating quality control flags and quantitative measurements and highlight the advantage of joint analysis of population-based samples and phenotypic extremes in human genetics studies.

Smooth muscle expression of RNA editing enzyme ADAR1 controls activation of RNA sensor MDA5 in atherosclerosis

Mapping the genomic architecture of complex disease has been predicated on the understanding that genetic variants influence disease risk through modifying gene expression. However, recent discoveries have revealed that a significant burden of disease heritability in common autoinflammatory disorders and coronary artery disease is mediated through genetic variation modifying post-transcriptional modification of RNA through adenosine-to-inosine (A-to-I) RNA editing. This common RNA modification is catalyzed by ADAR enzymes, where ADAR1 edits specific immunogenic double stranded RNA (dsRNA) to prevent activation of the double strand RNA (dsRNA) sensor MDA5 ( IFIH1 ) and stimulation of an interferon stimulated gene (ISG) response. Multiple lines of human genetic data indicate impaired RNA editing and increased dsRNA sensing by MDA5 to be an important mechanism of coronary artery disease (CAD) risk. Here, we provide a crucial link between observations in human genetics and mechanistic cell biology leading to progression of CAD. Through analysis of human atherosclerotic plaque, we implicate the vascular smooth muscle cell (SMC) to have a unique requirement for RNA editing, and that ISG induction occurs in SMC phenotypic modulation, implicating MDA5 activation. Through culture of human coronary artery SMCs, generation of a conditional SMC specific Adar1 deletion mouse model on a pro-atherosclerosis background with additional constitutive deletion of MDA5 ( Ifih1 ), and with incorporation of single cell RNA sequencing cellular profiling, we further show that Adar1 controls SMC phenotypic state by regulating Mda5 activation, is required to maintain vascular integrity, and controls progression of atherosclerosis and vascular calcification. Through this work, we describe a fundamental mechanism of CAD, where cell type and context specific RNA editing and sensing of dsRNA mediates disease progression, bridging our understanding of human genetics and disease causality.

One Sentence Summary

Smooth muscle expression of RNA editing enzyme ADAR1 regulates activation of double strand RNA sensor MDA5 in novel mechanism of atherosclerosis.

Drug-target Mendelian randomisation applied to metabolic dysfunction-associated steatotic liver disease: opportunities and challenges

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most prevalent cause of chronic liver disease worldwide affecting over one-third of the adult population. Despite the recent evolution of new nomenclature and diagnostic criteria for MASLD, progress in drug development for this condition remains limited. This review highlights the potential of drug-target Mendelian randomisation (MR), a study design that leverages human genetics and genomics, for the discovery, repositioning and safety assessment of drug targets in MASLD. We summarised key aspects of designing and appraising a drug-target MR study, discussing its inherent assumptions and considerations for instrument selection. Furthermore, we presented real-world examples from studies in MASLD which focused on opportunities and challenges in identifying novel drug targets, repositing existing drug targets, informing adjunctive treatments and addressing issues in paediatric MASLD.

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.

Multifaceted roles of RNA editing enzyme ADAR1 in innate immunity

Innate immunity must be tightly regulated to enable sensitive pathogen detection while averting autoimmunity triggered by pathogen-like host molecules. A hallmark of viral infection, double-stranded RNAs (dsRNAs) are also abundantly encoded in mammalian genomes, necessitating surveillance mechanisms to distinguish "self" from "nonself." ADAR1, an RNA editing enzyme, has emerged as an essential safeguard against dsRNA-induced autoimmunity. By converting adenosines to inosines (A-to-I) in long dsRNAs, ADAR1 covalently marks endogenous dsRNAs, thereby blocking the activation of the cytoplasmic dsRNA sensor MDA5. Moreover, beyond its editing function, ADAR1 binding to dsRNA impedes the activation of innate immune sensors PKR and ZBP1. Recent landmark studies underscore the utility of silencing ADAR1 for cancer immunotherapy, by exploiting the ADAR1-dependence developed by certain tumors to unleash an antitumor immune response. In this perspective, we summarize the genetic and mechanistic evidence for ADAR1's multipronged role in suppressing dsRNA-mediated autoimmunity and explore the evolving roles of ADAR1 as an immuno-oncology target.

Drug development advances in human genetics-based targets

Drug development is a long and costly process, with a high degree of uncertainty from the identification of a drug target to its market launch. Targeted drugs supported by human genetic evidence are expected to enter phase II/III clinical trials or be approved for marketing more quickly, speeding up the drug development process. Currently, genetic data and technologies such as genome-wide association studies (GWAS), whole-exome sequencing (WES), and whole-genome sequencing (WGS) have identified and validated many potential molecular targets associated with diseases. This review describes the structure, molecular biology, and drug development of human genetics-based validated beneficial loss-of-function (LOF) mutation targets (target mutations that reduce disease incidence) over the past decade. The feasibility of eight beneficial LOF mutation targets (PCSK9, ANGPTL3, ASGR1, HSD17B13, KHK, CIDEB, GPR75, and INHBE) as targets for drug discovery is mainly emphasized, and their research prospects and challenges are discussed. In conclusion, we expect that this review will inspire more researchers to use human genetics and genomics to support the discovery of novel therapeutic drugs and the direction of clinical development, which will contribute to the development of new drug discovery and drug repurposing.

Beyond apples and pears: sex-specific genetics of body fat percentage

Introduction

Biological sex influences both overall adiposity and fat distribution. Further, testosterone and sex hormone binding globulin (SHBG) influence adiposity and metabolic function, with differential effects of testosterone in men and women. Here, we aimed to perform sex-stratified genome-wide association studies (GWAS) of body fat percentage (BFPAdj) (adjusting for testosterone and sex hormone binding globulin (SHBG)) to increase statistical power.

Methods

GWAS were performed in white British individuals from the UK Biobank (157,937 males and 154,337 females). To avoid collider bias, loci associated with SHBG or testosterone were excluded. We investigated association of BFPAdj loci with high density cholesterol (HDL), triglyceride (TG), type 2 diabetes (T2D), coronary artery disease (CAD), and MRI-derived abdominal subcutaneous adipose tissue (ASAT), visceral adipose tissue (VAT) and gluteofemoral adipose tissue (GFAT) using publicly available data from large GWAS. We also performed 2-sample Mendelian Randomization (MR) using identified BFPAdj variants as instruments to investigate causal effect of BFPAdj on HDL, TG, T2D and CAD in males and females separately.

Results

We identified 195 and 174 loci explaining 3.35% and 2.60% of the variation in BFPAdj in males and females, respectively at genome-wide significance (GWS, p<5x10-8). Although the direction of effect at these loci was generally concordant in males and females, only 38 loci were common to both sexes at GWS. Seven loci in males and ten loci in females have not been associated with any adiposity/cardiometabolic traits previously. BFPAdj loci generally did not associate with cardiometabolic traits; several had paradoxically beneficial cardiometabolic effects with favourable fat distribution. MR analyses did not find convincing supportive evidence that increased BFPAdj has deleterious cardiometabolic effects in either sex with highly significant heterogeneity.

Conclusions

There was limited genetic overlap between BFPAdj in males and females at GWS. BFPAdj loci generally did not have adverse cardiometabolic effects which may reflect the effects of favourable fat distribution and cardiometabolic risk modulation by testosterone and SHBG.

Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts

Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity-related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In the investigated regions with genome-wide significant associations for obesity-related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine-mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggests generalizability of genetic mechanisms underpinning obesity-related traits across populations.

Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease

Importance

Protein-truncating variants (PTVs) in apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are associated with significantly lower low-density lipoprotein (LDL) cholesterol concentrations. The association of these PTVs with coronary heart disease (CHD) warrants further characterization in large, multiracial prospective cohort studies.

Objective

To evaluate the association of PTVs in APOB and PCSK9 with LDL cholesterol concentrations and CHD risk.

Design, Setting, and Participants

This studied included participants from 5 National Heart, Lung, and Blood Institute (NHLBI) studies and the UK Biobank. NHLBI study participants aged 5 to 84 years were recruited between 1971 and 2002 across the US and underwent whole-genome sequencing. UK Biobank participants aged 40 to 69 years were recruited between 2006 and 2010 in the UK and underwent whole-exome sequencing. Data were analyzed from June 2021 to October 2022.

Exposures

PTVs in APOB and PCSK9.

Main Outcomes and Measures

Estimated untreated LDL cholesterol levels and CHD.

Results

Among 19 073 NHLBI participants (10 598 [55.6%] female; mean [SD] age, 52 [17] years), 139 (0.7%) carried an APOB or PCSK9 PTV, which was associated with 49 mg/dL (95% CI, 43-56) lower estimated untreated LDL cholesterol level. Over a median (IQR) follow-up of 21.5 (13.9-29.4) years, incident CHD was observed in 12 of 139 carriers (8.6%) vs 3029 of 18 934 noncarriers (16.0%), corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.28-0.89; P = .02). Among 190 464 UK Biobank participants (104 831 [55.0%] female; mean [SD] age, 57 [8] years), 662 (0.4%) carried a PTV, which was associated with 45 mg/dL (95% CI, 42-47) lower estimated untreated LDL cholesterol level. Estimated CHD risk by age 75 years was 3.7% (95% CI, 2.0-5.3) in carriers vs 7.0% (95% CI, 6.9-7.2) in noncarriers, corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.32-0.81; P = .004).

Conclusions and Relevance

Among 209 537 individuals in this study, 0.4% carried an APOB or PCSK9 PTV that was associated with less exposure to LDL cholesterol and a 49% lower risk of CHD.

Mendelian randomization as a tool to inform drug development using human genetics

Drug development is essential to the advancement of human health, however, the process is slow, costly, and at high risk of failure at all stages. A promising strategy for expediting and improving the probability of success in the drug development process is the use of naturally randomized human genetic variation for drug target identification and validation. These data can be harnessed using the Mendelian randomization (MR) analytic paradigm to proxy the lifelong consequences of genetic perturbations of drug targets. In this review, we discuss the myriad applications of the MR paradigm for human drug target identification and validation. We review the methodology and applications of MR, key limitations of MR, and potential future opportunities for research. Throughout the review, we refer to illustrative examples of MR analyses investigating the consequences of genetic inhibition of interleukin 6 signaling which, in some cases, have anticipated results from randomized controlled trials. As human genetic data become more widely available, we predict that MR will serve as a key pillar of support for drug development efforts.

G protein-coupled receptor 151 regulates glucose metabolism and hepatic gluconeogenesis

Human genetics has been instrumental in identification of genetic variants linked to type 2 diabetes. Recently a rare, putative loss-of-function mutation in the orphan G-protein coupled receptor 151 (GPR151) was found to be associated with lower odds ratio for type 2 diabetes, but the mechanism behind this association has remained elusive. Here we show that Gpr151 is a fasting- and glucagon-responsive hepatic gene which regulates hepatic gluconeogenesis. Gpr151 ablation in mice leads to suppression of hepatic gluconeogenesis genes and reduced hepatic glucose production in response to pyruvate. Importantly, the restoration of hepatic Gpr151 levels in the Gpr151 knockout mice reverses the reduced hepatic glucose production. In this work, we establish a previously unknown role of Gpr151 in the liver that provides an explanation to the lowered type 2 diabetes risk in individuals with nonsynonymous mutations in GPR151.

The contribution of common and rare genetic variants to variation in metabolic traits in 288,137 East Asians

Metabolic traits are heritable phenotypes widely-used in assessing the risk of various diseases. We conduct a genome-wide association analysis (GWAS) of nine metabolic traits (including glycemic, lipid, liver enzyme levels) in 125,872 Korean subjects genotyped with the Korea Biobank Array. Following meta-analysis with GWAS from Biobank Japan identify 144 novel signals (MAF ≥ 1%), of which 57.0% are replicated in UK Biobank. Additionally, we discover 66 rare (MAF < 1%) variants, 94.4% of them co-incident to common loci, adding to allelic series. Although rare variants have limited contribution to overall trait variance, these lead, in carriers, substantial loss of predictive accuracy from polygenic predictions of disease risk from common variant alone. We capture groups with up to 16-fold variation in type 2 diabetes (T2D) prevalence by integration of genetic risk scores of fasting plasma glucose and T2D and the I349F rare protective variant. This study highlights the need to consider the joint contribution of both common and rare variants on inherited risk of metabolic traits and related diseases.

RNA editing underlies genetic risk of common inflammatory diseases

A major challenge in human genetics is to identify the molecular mechanisms of trait-associated and disease-associated variants. To achieve this, quantitative trait locus (QTL) mapping of genetic variants with intermediate molecular phenotypes such as gene expression and splicing have been widely adopted1,2. However, despite successes, the molecular basis for a considerable fraction of trait-associated and disease-associated variants remains unclear3,4. Here we show that ADAR-mediated adenosine-to-inosine RNA editing, a post-transcriptional event vital for suppressing cellular double-stranded RNA (dsRNA)-mediated innate immune interferon responses5-11, is an important potential mechanism underlying genetic variants associated with common inflammatory diseases. We identified and characterized 30,319 cis-RNA editing QTLs (edQTLs) across 49 human tissues. These edQTLs were significantly enriched in genome-wide association study signals for autoimmune and immune-mediated diseases. Colocalization analysis of edQTLs with disease risk loci further pinpointed key, putatively immunogenic dsRNAs formed by expected inverted repeat Alu elements as well as unexpected, highly over-represented cis-natural antisense transcripts. Furthermore, inflammatory disease risk variants, in aggregate, were associated with reduced editing of nearby dsRNAs and induced interferon responses in inflammatory diseases. This unique directional effect agrees with the established mechanism that lack of RNA editing by ADAR1 leads to the specific activation of the dsRNA sensor MDA5 and subsequent interferon responses and inflammation7-9. Our findings implicate cellular dsRNA editing and sensing as a previously underappreciated mechanism of common inflammatory diseases.

Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots

For any given level of overall adiposity, individuals vary considerably in fat distribution. The inherited basis of fat distribution in the general population is not fully understood. Here, we study up to 38,965 UK Biobank participants with MRI-derived visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) adipose tissue volumes. Because these fat depot volumes are highly correlated with BMI, we additionally study six local adiposity traits: VAT adjusted for BMI and height (VATadj), ASATadj, GFATadj, VAT/ASAT, VAT/GFAT, and ASAT/GFAT. We identify 250 independent common variants (39 newly-identified) associated with at least one trait, with many associations more pronounced in female participants. Rare variant association studies extend prior evidence for PDE3B as an important modulator of fat distribution. Local adiposity traits (1) highlight depot-specific genetic architecture and (2) enable construction of depot-specific polygenic scores that have divergent associations with type 2 diabetes and coronary artery disease. These results - using MRI-derived, BMI-independent measures of local adiposity - confirm fat distribution as a highly heritable trait with important implications for cardiometabolic health outcomes.

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.

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.

Significant sparse polygenic risk scores across 813 traits in UK Biobank

We present a systematic assessment of polygenic risk score (PRS) prediction across more than 1,500 traits using genetic and phenotype data in the UK Biobank. We report 813 sparse PRS models with significant (p < 2.5 x 10-5) incremental predictive performance when compared against the covariate-only model that considers age, sex, types of genotyping arrays, and the principal component loadings of genotypes. We report a significant correlation between the number of genetic variants selected in the sparse PRS model and the incremental predictive performance (Spearman's ⍴ = 0.61, p = 2.2 x 10-59 for quantitative traits, ⍴ = 0.21, p = 9.6 x 10-4 for binary traits). The sparse PRS model trained on European individuals showed limited transferability when evaluated on non-European individuals in the UK Biobank. We provide the PRS model weights on the Global Biobank Engine (https://biobankengine.stanford.edu/prs).

Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank

Cardiometabolic diseases are the leading cause of death worldwide. Despite a known genetic component, our understanding of these diseases remains incomplete. Here, we analyzed the contribution of rare variants to 57 diseases and 26 cardiometabolic traits, using data from 200,337 UK Biobank participants with whole-exome sequencing. We identified 57 gene-based associations, with broad replication of novel signals in Geisinger MyCode. There was a striking risk associated with mutations in known Mendelian disease genes, including MYBPC3, LDLR, GCK, PKD1 and TTN. Many genes showed independent convergence of rare and common variant evidence, including an association between GIGYF1 and type 2 diabetes. We identified several large effect associations for height and 18 unique genes associated with blood lipid or glucose levels. Finally, we found that between 1.0% and 2.4% of participants carried rare potentially pathogenic variants for cardiometabolic disorders. These findings may facilitate studies aimed at therapeutics and screening of these common disorders.

Avasimibe Alleviates Disruption of the Airway Epithelial Barrier by Suppressing the Wnt/β-Catenin Signaling Pathway

Avasimibe (Ava) is an acetyl-CoA acetyltransferase 1 (ACAT1) specific inhibitor and an established medicine for atherosclerosis, owing to its excellent and safe anti-inflammation effects in humans. However, its efficacy in asthma has not yet been reported. We first administered varying concentrations of avasimibe to house dust mite (HDM)-induced asthmatic mice; results showed that 20 mg/kg avasimibe most significantly reduced IL-4 and IL-5 production in bronchoalveolar lavage fluid (BALF) and total IgE in serum, and the avasimibe treatment also exhibited lower mucus secretion, decreased goblet and basal cells but increased ciliated cells compared to the HDM group. And the redistribution of adherens junction (AJ) proteins induced by HDM was far more less upon avasimibe administration. However, avasimibe did not reduce the cholesterol ester ratio in lung tissues or intracellular cholesterol ester, which is avasimibe’s main effect. Further analysis confirmed that avasimibe impaired epithelial basal cell proliferation independent of regulating cholesterol metabolism and we analyzed datasets using the Gene Expression Omnibus (GEO) database and then found that the KRT5 gene (basal cell marker) expression is correlated with the β-catenin gene. Moreover, we found that β-catenin localized in cytomembrane upon avasimibe treatment. Avasimibe also reduced β-catenin phosphorylation in the cytoplasm and inactivated the Wnt/β-catenin signaling pathway induced by HDMs, thereby alleviating the airway epithelial barrier disruption. Taken together, these findings indicated that avasimibe has potential as a new therapeutic option for allergic asthma.

The genetics of obesity: from discovery to biology

The prevalence of obesity has tripled over the past four decades, imposing an enormous burden on people's health. Polygenic (or common) obesity and rare, severe, early-onset monogenic obesity are often polarized as distinct diseases. However, gene discovery studies for both forms of obesity show that they have shared genetic and biological underpinnings, pointing to a key role for the brain in the control of body weight. Genome-wide association studies (GWAS) with increasing sample sizes and advances in sequencing technology are the main drivers behind a recent flurry of new discoveries. However, it is the post-GWAS, cross-disciplinary collaborations, which combine new omics technologies and analytical approaches, that have started to facilitate translation of genetic loci into meaningful biology and new avenues for treatment.

Joint Analysis of Genetic Correlation, Mendelian Randomization and Colocalization Highlights the Bi-Directional Causal Association Between Hypothyroidism and Primary Biliary Cirrhosis

Background: Hypothyroidism and primary biliary cirrhosis (PBC) are often co-existed in observational epidemiological studies. However, the causal relationship between them remains unclear.

Methods: Genetic correlation, Mendelian randomization (MR) and colocalization analysis were combined to assess the potential causal association between hypothyroidism and PBC by using summary statistics from large-scale genome-wide association studies. Various sensitivity analyses had been conducted to assess the robustness and the consistency of the findings.

Results: The linkage disequilibrium score regression demonstrated significant evidence of shared genetic architecture between hypothyroidism and PBC, with the genetic correlation estimated to be 0.117 (p = 0.006). The OR of hypothyroidism on PBC was 1.223 (95% CI, 1.072–1.396; p = 2.76 × 10⁻³) in MR analysis with inverse variance weighted (IVW) method. More importantly, the results from other 7MR methods with different model assumptions, were almost identical with that of IVW, suggesting the findings were robust and convincing. On the other hand, PBC was also causally associated with hypothyroidism (OR, 1.049; 95% CI, 1.010–1.089; p = 0.012), and, again, similar results can also be obtained from other MR methods. Various sensitivity analyses regarding the outlier detection and leave-one-out analysis were also performed. Besides, colocalization analysis suggested that there existed shared causal variants between hypothyroidism and PBC, further highlighting the robustness of the results.

Conclusion: Our results suggest evidence for the bi-directional causal association between hypothyroidism and PBC, which may provide insights into the etiology of hypothyroidism and PBC as well as inform prevention and intervention strategies directed toward both diseases.

Whole-exome sequencing reveals a role of HTRA1 and EGFL8 in brain white matter hyperintensities

White matter hyperintensities (WMH) are among the most common radiological abnormalities in the ageing population and an established risk factor for stroke and dementia. While common variant association studies have revealed multiple genetic loci with an influence on their volume, the contribution of rare variants to the WMH burden in the general population remains largely unexplored. We conducted a comprehensive analysis of this burden in the UK Biobank using publicly available whole-exome sequencing data (n up to 17 830) and found a splice-site variant in GBE1, encoding 1,4-alpha-glucan branching enzyme 1, to be associated with lower white matter burden on an exome-wide level [c.691+2T>C, β = -0.74, standard error (SE) = 0.13, P = 9.7 × 10-9]. Applying whole-exome gene-based burden tests, we found damaging missense and loss-of-function variants in HTRA1 (frequency of 1 in 275 in the UK Biobank population) to associate with an increased WMH volume (P = 5.5 × 10-6, false discovery rate = 0.04). HTRA1 encodes a secreted serine protease implicated in familial forms of small vessel disease. Domain-specific burden tests revealed that the association with WMH volume was restricted to rare variants in the protease domain (amino acids 204-364; β = 0.79, SE = 0.14, P = 9.4 × 10-8). The frequency of such variants in the UK Biobank population was 1 in 450. The WMH volume was brought forward by ∼11 years in carriers of a rare protease domain variant. A comparison with the effect size of established risk factors for WMH burden revealed that the presence of a rare variant in the HTRA1 protease domain corresponded to a larger effect than meeting the criteria for hypertension (β = 0.26, SE = 0.02, P = 2.9 × 10-59) or being in the upper 99.8% percentile of the distribution of a polygenic risk score based on common genetic variants (β = 0.44, SE = 0.14, P = 0.002). In biochemical experiments, most (6/9) of the identified protease domain variants resulted in markedly reduced protease activity. We further found EGFL8, which showed suggestive evidence for association with WMH volume (P = 1.5 × 10-4, false discovery rate = 0.22) in gene burden tests, to be a direct substrate of HTRA1 and to be preferentially expressed in cerebral arterioles and arteries. In a phenome-wide association study mapping ICD-10 diagnoses to 741 standardized Phecodes, rare variants in the HTRA1 protease domain were associated with multiple neurological and non-neurological conditions including migraine with aura (odds ratio = 12.24, 95%CI: 2.54-35.25; P = 8.3 × 10-5]. Collectively, these findings highlight an important role of rare genetic variation and the HTRA1 protease in determining WMH burden in the general population.

Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease

Huntington disease (HD) is a neurodegenerative disorder that is caused by a CAG repeat expansion in HTT. The length of this repeat, however, only explains a proportion of the variability in age of onset in patients. Genome-wide association studies have identified modifiers that contribute toward a proportion of the observed variance. By incorporating tissue-specific transcriptomic information with these results, additional modifiers can be identified. We performed a transcriptome-wide association study assessing heritable differences in genetically determined expression in diverse tissues, with genome-wide data from over 4000 patients. Functional validation of prioritized genes was undertaken in isogenic HD stem cells and patient brains. Enrichment analyses were performed with biologically relevant gene sets to identify the core pathways. HD-associated gene coexpression modules were assessed for associations with neurological phenotypes in an independent cohort and to guide drug repurposing analyses. Transcriptomic analyses identified genes that were associated with age of HD onset and displayed colocalization with gene expression signals in brain tissue (FAN1, GPR161, PMS2, SUMF2), with supporting evidence from functional experiments. This included genes involved in DNA repair, as well as novel-candidate modifier genes that have been associated with other neurological conditions. Further, cortical coexpression modules were also associated with cognitive decline and HD-related traits in a longitudinal cohort. In summary, the combination of population-scale gene expression information with HD patient genomic data identified novel modifier genes for the disorder. Further, these analyses expanded the pathways potentially involved in modifying HD onset and prioritized candidate therapeutics for future study.

Gene expression atlas of energy balance brain regions

Energy balance is controlled by interconnected brain regions in the hypothalamus, brainstem, cortex, and limbic system. Gene expression signatures of these regions can help elucidate the pathophysiology underlying obesity. RNA sequencing was conducted on P56 C57BL/6NTac male mice and E14.5 C57BL/6NTac embryo punch biopsies in 16 obesity-relevant brain regions. The expression of 190 known obesity-associated genes (monogenic, rare, and low-frequency coding variants; GWAS; syndromic) was analyzed in each anatomical region. Genes associated with these genetic categories of obesity had localized expression patterns across brain regions. Known monogenic obesity causal genes were highly enriched in the arcuate nucleus of the hypothalamus and developing hypothalamus. The obesity-associated genes clustered into distinct “modules” of similar expression profile, and these were distinct from expression modules formed by similar analysis with genes known to be associated with other disease phenotypes (type 1 and type 2 diabetes, autism, breast cancer) in the same energy balance–relevant brain regions.

Nonsense-mediated decay is highly stable across individuals and tissues

Precise interpretation of the effects of rare protein-truncating variants (PTVs) is important for accurate determination of variant impact. Current methods for assessing the ability of PTVs to induce nonsense-mediated decay (NMD) focus primarily on the position of the variant in the transcript. We used RNA sequencing of the Genotype Tissue Expression v.8 cohort to compute the efficiency of NMD using allelic imbalance for 2,320 rare (genome aggregation database minor allele frequency ≤ 1%) PTVs across 809 individuals in 49 tissues. We created an interpretable predictive model using penalized logistic regression in order to evaluate the comprehensive influence of variant annotation, tissue, and inter-individual variation on NMD. We found that variant position, allele frequency, the inclusion of ultra-rare and singleton variants, and conservation were predictive of allelic imbalance. Furthermore, we found that NMD effects were highly concordant across tissues and individuals. Due to this high consistency, we demonstrate in silico that utilizing peripheral tissues or cell lines provides accurate prediction of NMD for PTVs.

Using Phecodes for Research with the Electronic Health Record: From PheWAS to PheRS

Electronic health records (EHRs) are a rich source of data for researchers, but extracting meaningful information out of this highly complex data source is challenging. Phecodes represent one strategy for defining phenotypes for research using EHR data. They are a high-throughput phenotyping tool based on ICD (International Classification of Diseases) codes that can be used to rapidly define the case/control status of thousands of clinically meaningful diseases and conditions. Phecodes were originally developed to conduct phenome-wide association studies to scan for phenotypic associations with common genetic variants. Since then, phecodes have been used to support a wide range of EHR-based phenotyping methods, including the phenotype risk score. This review aims to comprehensively describe the development, validation, and applications of phecodes and suggest some future directions for phecodes and high-throughput phenotyping.

Sequencing of 640,000 exomes identifies GPR75 variants associated with protection from obesity

Large-scale human exome sequencing can identify rare protein-coding variants with a large impact on complex traits such as body adiposity. We sequenced the exomes of 645,626 individuals from the United Kingdom, the United States, and Mexico and estimated associations of rare coding variants with body mass index (BMI). We identified 16 genes with an exome-wide significant association with BMI, including those encoding five brain-expressed G protein-coupled receptors (CALCR, MC4R, GIPR, GPR151, and GPR75). Protein-truncating variants in GPR75 were observed in ~4/10,000 sequenced individuals and were associated with 1.8 kilograms per square meter lower BMI and 54% lower odds of obesity in the heterozygous state. Knock out of Gpr75 in mice resulted in resistance to weight gain and improved glycemic control in a high-fat diet model. Inhibition of GPR75 may provide a therapeutic strategy for obesity.

Whole-exome imputation within UK Biobank powers rare coding variant association and fine-mapping analyses

Exome association studies to date have generally been underpowered to systematically evaluate the phenotypic impact of very rare coding variants. We leveraged extensive haplotype sharing between 49,960 exome-sequenced UK Biobank participants and the remainder of the cohort (total N~500K) to impute exome-wide variants with accuracy (R²>0.5) down to minor allele frequency (MAF) ~0.00005. Association and fine-mapping analyses of 54 quantitative traits identified 1,189 significant associations (P<5 x 10⁻⁸) involving 675 distinct rare protein-altering variants (MAF<0.01) that passed stringent filters for likely causality. Across all traits, 49% of associations (578/1,189) occurred in genes with two or more hits; follow-up analyses of these genes identified allelic series containing up to 45 distinct likely-causal variants. Our results demonstrate the utility of within-cohort imputation in population-scale GWAS cohorts, provide a catalog of likely-causal, large-effect coding variant associations, and foreshadow the insights that will be revealed as genetic biobank studies continue to grow.

Deep sequencing of 1320 genes reveals the landscape of protein-truncating variants and their contribution to psoriasis in 19,973 Chinese individuals

Protein-truncating variants (PTVs) have important impacts on phenotype diversity and disease. However, their population genetics characteristics in more globally diverse populations are not well defined. Here, we describe patterns of PTVs in 1320 genes sequenced in 10,539 healthy controls and 9434 patients with psoriasis, all of Han Chinese ancestry. We identify 8720 PTVs, of which 77% are novel, and estimate 88% of all PTVs are deleterious and subject to purifying selection. Furthermore, we show that individuals with psoriasis have a significantly higher burden of PTVs compared to controls (P = 0.02). Finally, we identified 18 PTVs in 14 genes with unusually high levels of population differentiation, consistent with the action of local adaptation. Our study provides insights into patterns and consequences of PTVs.

Multi-Omics Approaches in Immunological Research

The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.

Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10-72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10-4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10-5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.

Association of Genetic Variation With Cirrhosis: A Multi-Trait Genome-Wide Association and Gene-Environment Interaction Study

BACKGROUND & AIMS

In contrast to most other common diseases, few genetic variants have been identified that impact risk of cirrhosis. We aimed to identify new genetic variants that predispose to cirrhosis, to test whether such variants, aggregated into a polygenic score, enable genomic risk stratification, and to test whether alcohol intake or body mass index interacts with polygenic predisposition.

METHODS

We conducted a multi-trait genome-wide association study combining cirrhosis and alanine aminotransferase levels performed in 5 discovery studies (UK Biobank, Vanderbilt BioVU, Atherosclerosis Risk in Communities study, and 2 case-control studies including 4829 individuals with cirrhosis and 72,705 controls and 362,539 individuals with alanine aminotransferase levels). Identified variants were replicated in 3 studies (Partners HealthCare Biobank, FinnGen, and Biobank Japan including 3554 individuals with cirrhosis and 343,826 controls). A polygenic score was tested in Partners HealthCare Biobank.

RESULTS

Five previously reported and 7 newly identified genetic variants were associated with cirrhosis in both the discovery studies multi-trait genome-wide association study (P < 5 × 10-8) and the replication studies (P < .05), including a missense variant in the APOE gene and a noncoding variant near EFN1A. These 12 variants were used to generate a polygenic score. Among Partners HealthCare Biobank individuals, high polygenic score-defined as the top quintile of the distribution-was associated with significantly increased risk of cirrhosis (odds ratio, 2.26; P < .001) and related comorbidities compared with the lowest quintile. Risk was even more pronounced among those with extreme polygenic risk (top 1% of the distribution, odds ratio, 3.16; P < .001). The impact of extreme polygenic risk was substantially more pronounced in those with elevated alcohol consumption or body mass index. Modeled as risk by age 75 years, probability of cirrhosis with extreme polygenic risk was 13.7%, 20.1%, and 48.2% among individuals with no or modest, moderate, and increased alcohol consumption, respectively (Pinteraction < .001). Similarly, probability among those with extreme polygenic risk was 6.5%, 10.3%, and 19.5% among individuals with normal weight, overweight, and obesity, respectively (Pinteraction < .001).

CONCLUSIONS

Twelve independent genetic variants, 7 of which are newly identified in this study, conferred risk for cirrhosis. Aggregated into a polygenic score, these variants identified a subset of the population at substantially increased risk who are most susceptible to the hepatotoxic effects of excess alcohol consumption or obesity.

Germline Genetic Variants of Viral Entry and Innate Immunity May Influence Susceptibility to SARS-CoV-2 Infection: Toward a Polygenic Risk Score for Risk Stratification

The ongoing COVID-19 pandemic caused by the novel coronavirus, SARS-CoV-2 has affected all aspects of human society with a special focus on healthcare. Although older patients with preexisting chronic illnesses are more prone to develop severe complications, younger, healthy individuals might also exhibit serious manifestations. Previous studies directed to detect genetic susceptibility factors for earlier epidemics have provided evidence of certain protective variations. Following SARS-CoV-2 exposure, viral entry into cells followed by recognition and response by the innate immunity are key determinants of COVID-19 development. In the present review our aim was to conduct a thorough review of the literature on the role of single nucleotide polymorphisms (SNPs) as key agents affecting the viral entry of SARS-CoV-2 and innate immunity. Several SNPs within the scope of our approach were found to alter susceptibility to various bacterial and viral infections. Additionally, a multitude of studies confirmed genetic associations between the analyzed genes and autoimmune diseases, underlining the versatile immune consequences of these variants. Based on confirmed associations it is highly plausible that the SNPs affecting viral entry and innate immunity might confer altered susceptibility to SARS-CoV-2 infection and its complex clinical consequences. Anticipating several COVID-19 genomic susceptibility loci based on the ongoing genome wide association studies, our review also proposes that a well-established polygenic risk score would be able to clinically leverage the acquired knowledge.

Loss of Znt8 function in diabetes mellitus: risk or benefit?

The zinc transporter 8 (ZnT8) plays an essential role in zinc homeostasis inside pancreatic β cells, its function is related to the stabilization of insulin hexameric form. Genome-wide association studies (GWAS) have established a positive and negative relationship of ZnT8 variants with type 2 diabetes mellitus (T2DM), exposing a dual and controversial role. The first hypotheses about its role in T2DM indicated a higher risk of developing T2DM for loss of function; nevertheless, recent GWAS of ZnT8 loss-of-function mutations in humans have shown protection against T2DM. With regard to the ZnT8 role in T2DM, most studies have focused on rodent models and common high-risk variants; however, considerable differences between human and rodent models have been found and the new approaches have included lower-frequency variants as a tool to clarify gene functions, allowing a better understanding of the disease and offering possible therapeutic targets. Therefore, this review will discuss the physiological effects of the ZnT8 variants associated with a major and lower risk of T2DM, emphasizing the low- and rare-frequency variants.

Rare versus common diseases: a false dichotomy in precision medicine

Precision medicine initiatives are being launched worldwide, each with the capacity to sequence many thousands to millions of human genomes. At the strategic planning level, all are debating the extent to which these resources will be directed towards rare diseases (and cancers) versus common diseases. However, these are not mutually exclusive choices. The organizational and governmental infrastructure created for rare diseases is extensible to common diseases. As we will explain, the underlying technology can also be used to identify drug targets for common diseases with a strategy focused on naturally occurring human knockouts. This flips on its head the prevailing modus operandi of studying people with diseases of interest, shifting the onus to defining traits worth emulating by pharmaceuticals, and searching phenotypically for people with these traits. This also shifts the question of what is rare or common from the many underlying causes to the possibility of a common final pathway.

Whole exome sequencing analyses reveal gene-microbiota interactions in the context of IBD

OBJECTIVE

Both the gut microbiome and host genetics are known to play significant roles in the pathogenesis of IBD. However, the interaction between these two factors and its implications in the aetiology of IBD remain underexplored. Here, we report on the influence of host genetics on the gut microbiome in IBD.

DESIGN

To evaluate the impact of host genetics on the gut microbiota of patients with IBD, we combined whole exome sequencing of the host genome and whole genome shotgun sequencing of 1464 faecal samples from 525 patients with IBD and 939 population-based controls. We followed a four-step analysis: (1) exome-wide microbial quantitative trait loci (mbQTL) analyses, (2) a targeted approach focusing on IBD-associated genomic regions and protein truncating variants (PTVs, minor allele frequency (MAF) >5%), (3) gene-based burden tests on PTVs with MAF <5% and exome copy number variations (CNVs) with site frequency <1%, (4) joint analysis of both cohorts to identify the interactions between disease and host genetics.

RESULTS

We identified 12 mbQTLs, including variants in the IBD-associated genes IL17REL, MYRF, SEC16A and WDR78. For example, the decrease of the pathway acetyl-coenzyme A biosynthesis, which is involved in short chain fatty acids production, was associated with variants in the gene MYRF (false discovery rate <0.05). Changes in functional pathways involved in the metabolic potential were also observed in participants carrying rare PTVs or CNVs in CYP2D6, GPR151 and CD160 genes. These genes are known for their function in the immune system. Moreover, interaction analyses confirmed previously known IBD disease-specific mbQTLs in TNFSF15.

CONCLUSION

This study highlights that both common and rare genetic variants affecting the immune system are key factors in shaping the gut microbiota in the context of IBD and pinpoints towards potential mechanisms for disease treatment.

Rare variant contribution to human disease in 281,104 UK Biobank exomes

Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits^1,2. Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal ( http://azphewas.com/ ).

Mutations in G Protein-Coupled Receptors: Mechanisms, Pathophysiology and Potential Therapeutic Approaches

There are approximately 800 annotated G protein-coupled receptor (GPCR) genes, making these membrane receptors members of the most abundant gene family in the human genome. Besides being involved in manifold physiologic functions and serving as important pharmacotherapeutic targets, mutations in 55 GPCR genes cause about 66 inherited monogenic diseases in humans. Alterations of nine GPCR genes are causatively involved in inherited digenic diseases. In addition to classic gain- and loss-of-function variants, other aspects, such as biased signaling, trans-signaling, ectopic expression, allele variants of GPCRs, pseudogenes, gene fusion, and gene dosage, contribute to the repertoire of GPCR dysfunctions. However, the spectrum of alterations and GPCR involvement is probably much larger because an additional 91 GPCR genes contain homozygous or hemizygous loss-of-function mutations in human individuals with currently unidentified phenotypes. This review highlights the complexity of genomic alteration of GPCR genes as well as their functional consequences and discusses derived therapeutic approaches. SIGNIFICANCE STATEMENT: With the advent of new transgenic and sequencing technologies, the number of monogenic diseases related to G protein-coupled receptor (GPCR) mutants has significantly increased, and our understanding of the functional impact of certain kinds of mutations has substantially improved. Besides the classical gain- and loss-of-function alterations, additional aspects, such as biased signaling, trans-signaling, ectopic expression, allele variants of GPCRs, uniparental disomy, pseudogenes, gene fusion, and gene dosage, need to be elaborated in light of GPCR dysfunctions and possible therapeutic strategies.

Exome sequencing and characterization of 49,960 individuals in the UK Biobank

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

Precision medicine and therapies of the future

Precision medicine in the epilepsies has gathered much attention, especially with gene discovery pushing forward new understanding of disease biology. Several targeted treatments are emerging, some with considerable sophistication and individual‐level tailoring. There have been rare achievements in improving short‐term outcomes in a few very select patients with epilepsy. The prospects for further targeted, repurposed, or novel treatments seem promising. Along with much‐needed success, difficulties are also arising. Precision treatments do not always work, and sometimes are inaccessible or do not yet exist. Failures of precision medicine may not find their way to broader scrutiny. Precision medicine is not a new concept: It has been boosted by genetics and is often focused on genetically determined epilepsies, typically considered to be driven in an individual by a single genetic variant. Often the mechanisms generating the full clinical phenotype from such a perceived single cause are incompletely understood. The impact of additional genetic variation and other factors that might influence the clinical presentation represent complexities that are not usually considered. Precision success and precision failure are usually equally incompletely explained. There is a need for more comprehensive evaluation and a more rigorous framework, bringing together information that is both necessary and sufficient to explain clinical presentation and clinical responses to precision treatment in a precision approach that considers the full picture not only of the effects of a single variant, but also of its genomic and other measurable environment, within the context of the whole person. As we may be on the brink of a treatment revolution, progress must be considered and reasoned: One possible framework is proposed for the evaluation of precision treatments.

Translating genomic insights into cardiovascular medicine: Opportunities and challenges of CRISPR-Cas9

The growing appreciation of human genetics and genomics in cardiovascular disease (CVD) accompanied by the technological breakthroughs in genome editing, particularly the CRISPR-Cas9 technologies, has presented an unprecedented opportunity to explore the application of genome editing in cardiovascular medicine. The ever-growing genome editing toolbox includes an assortment of CRISPR-Cas systems with increasing efficiency, precision, flexibility, and targeting capacity. Over the past decade, the advent of large-scale genotyping technologies and genome-wide association studies (GWAS) has provided numerous genotype-phenotype associations for diseases with complex traits. Notably, a growing number of loss-of-function mutations have been associated with favorable CVD risk-factor profiles that may confer protection. Combining the newly gained insights of human genetics with recent breakthrough technologies, such as the CRISPR-Cas9 technologies, holds great promise in elucidating novel disease mechanisms and transforming genes into medicines. Nonetheless, translating genetic insights into novel therapeuties remains challenging. Applications of "in body" genome editing for CVD treatment and engineering cardioprotection remain mostly theoretical. Here we highlight the recent advances of the CRISPR-based genome editing toolbox and discuss the potential and challenges of CRISPR-based technologies for translating GWAS findings into genomic medicines.

Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases

Population-scale biobanks that combine genetic data and high-dimensional phenotyping for a large number of participants provide an exciting opportunity to perform genome-wide association studies (GWAS) to identify genetic variants associated with diverse quantitative traits and diseases. A major challenge for GWAS in population biobanks is ascertaining disease cases from heterogeneous data sources such as hospital records, digital questionnaire responses, or interviews. In this study, we use genetic parameters, including genetic correlation, to evaluate whether GWAS performed using cases in the UK Biobank ascertained from hospital records, questionnaire responses, and family history of disease implicate similar disease genetics across a range of effect sizes. We find that hospital record and questionnaire GWAS largely identify similar genetic effects for many complex phenotypes and that combining together both phenotyping methods improves power to detect genetic associations. We also show that family history GWAS using cases ascertained on family history of disease agrees with combined hospital record and questionnaire GWAS and that family history GWAS has better power to detect genetic associations for some phenotypes. Overall, this work demonstrates that digital phenotyping and unstructured phenotype data can be combined with structured data such as hospital records to identify cases for GWAS in biobanks and improve the ability of such studies to identify genetic associations.

The mutational constraint spectrum quantified from variation in 141,456 humans

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease

Analyzing 12,361 all-cause cirrhosis cases and 790,095 controls from eight cohorts, we identify a common missense variant in the Mitochondrial Amidoxime Reducing Component 1 gene (MARC1 p.A165T) that associates with protection from all-cause cirrhosis (OR 0.91, p = 2.3*10⁻¹¹). This same variant also associates with lower levels of hepatic fat on computed tomographic imaging and lower odds of physician-diagnosed fatty liver as well as lower blood levels of alanine transaminase (-0.025 SD, 3.7*10⁻⁴³), alkaline phosphatase (-0.025 SD, 1.2*10⁻³⁷), total cholesterol (-0.030 SD, p = 1.9*10⁻³⁶) and LDL cholesterol (-0.027 SD, p = 5.1*10⁻³⁰) levels. We identified a series of additional MARC1 alleles (low-frequency missense p.M187K and rare protein-truncating p.R200Ter) that also associated with lower cholesterol levels, liver enzyme levels and reduced risk of cirrhosis (0 cirrhosis cases for 238 R200Ter carriers versus 17,046 cases of cirrhosis among 759,027 non-carriers, p = 0.04) suggesting that deficiency of the MARC1 enzyme may lower blood cholesterol levels and protect against cirrhosis.

Cirrhosis is a leading cause of death worldwide. However, the genetic underpinnings of cirrhosis remain poorly understood. In this study, we analyze twelve thousand individuals with cirrhosis and identify a common missense variant in a gene called MARC1 that protects against cirrhosis. Carriers of this missense variant also have lower blood cholesterol levels, lower liver enzyme levels and reduced liver fat. We identify an additional two low-frequency coding variants in MARC1 that are also associated with lower cholesterol levels, lower liver enzyme levels and protection from cirrhosis. Finally, we identify an individual homozygous for a predicted loss-of-function variant in MARC1 who exhibits very low blood LDL cholesterol levels. These genetic findings suggest that MARC1 deficiency may lower blood cholesterol levels and protect against cirrhosis, pointing to MARC1 as a potential therapeutic target for liver disease.

The habenular G-protein-coupled receptor 151 regulates synaptic plasticity and nicotine intake

The habenula, an ancient small brain area in the epithalamus, densely expresses nicotinic acetylcholine receptors and is critical for nicotine intake and aversion. As such, identification of strategies to manipulate habenular activity may yield approaches to treat nicotine addiction. Here we show that GPR151, an orphan G-protein-coupled receptor (GPCR) highly enriched in the habenula of humans and rodents, is expressed at presynaptic membranes and synaptic vesicles and associates with synaptic components controlling vesicle release and ion transport. Deletion of Gpr151 inhibits evoked neurotransmission but enhances spontaneous miniature synaptic currents and eliminates short-term plasticity induced by nicotine. We find that GPR151 couples to the G-alpha inhibitory protein Gα_o1 to reduce cyclic adenosine monophosphate (cAMP) levels in mice and in GPR151-expressing cell lines that are amenable to ligand screens. Gpr151- knockout (KO) mice show diminished behavioral responses to nicotine and self-administer greater quantities of the drug, phenotypes rescued by viral reexpression of Gpr151 in the habenula. These data identify GPR151 as a critical modulator of habenular function that controls nicotine addiction vulnerability.