Genomics of disease risk in globally diverse populations

Single nucleotide variants in microRNA biosynthesis genes in Mexican individuals

Background: MicroRNAs (miRNAs) are important regulators in a variety of biological processes, and their dysregulation is associated with multiple human diseases. Single nucleotide variants (SNVs) in genes involved in the processing of microRNAs may alter miRNA regulation and could present high allele heterogeneity in populations from different ethnic groups. Thus, the aim of this study was to genotype 15 SNVs in eight genes involved in the miRNA processing pathway in Mexican individuals and compare their frequencies across 21 populations from five continental groups.

Methods: Genomic DNA was obtained from 399 healthy Mexican individuals. SNVs in AGO2 (rs2293939 and rs4961280), DGCR8 (rs720012), DICER (rs3742330 and rs13078), DROSHA (rs10719 and rs6877842), GEMIN3 (rs197388 and rs197414), GEMIN4 (rs7813, rs2740349, and rs4968104), TNRC6B (rs9611280), and XP05 (rs11077 and rs34324334) were genotyped using TaqMan probes. The minor allele frequency of each SNV was compared to those reported in the 1,000 Genomes database using chi-squared. Sankey plot was created in the SankeyMATIC package to visualize the frequency range of each variant in the different countries analyzed.

Results: In Mexican individuals, all 15 SNVs were found in Hardy-Weinberg equilibrium, with frequencies ranging from 0.04 to 0.45. The SNVs rs4961280, rs2740349, rs34324334, and rs720012 in Mexican individuals had the highest minor allele frequencies worldwide, whereas the minor allele frequencies of rs197388, rs10719, rs197414, and rs1107 were among the lowest in Mexican individuals. The variants had high allele heterogeneity among the sub-continental populations, ranging from monomorphic, as was the case for rs9611280 and rs34324334 in African groups, to >0.50, which was the case for variants rs11077 and rs10719 in most of the populations. Importantly, the variants rs197388, rs720012, and rs197414 had FST values > 0.18, indicating a directional selective process. Finally, the SNVs rs13078 and rs10719 significantly correlated with both latitude and longitude.

Conclusion: These data indicate the presence of high allelic heterogeneity in the worldwide distribution of the frequency of SNVs located in components of the miRNA processing pathway, which could modify the genetic susceptibility associated with human diseases in populations with different ancestry.

Socioeconomic changes predict genome-wide DNA methylation in childhood

Childhood socioeconomic position (SEP) is a major determinant of health and well-being across the entire life course. To effectively prevent and reduce health risks related to SEP, it is critical to better understand when and under what circumstances socioeconomic adversity shapes biological processes. DNA methylation (DNAm) is one such mechanism for how early life adversity 'gets under the skin'. In this study, we evaluated the dynamic relationship between SEP and DNAm across childhood using data from 946 mother-child pairs in the Avon Longitudinal Study of Parents and Children. We assessed six SEP indicators spanning financial, occupational and residential domains during very early childhood (ages 0-2), early childhood (ages 3-5) and middle childhood (ages 6-7). Epigenome-wide DNAm was measured at 412 956 cytosine-guanines (CpGs) from peripheral blood at age 7. Using an innovative two-stage structured life-course modeling approach, we tested three life-course hypotheses for how SEP shapes DNAm profiles-accumulation, sensitive period and mobility. We showed that changes in the socioeconomic environment were associated with the greatest differences in DNAm, and that middle childhood may be a potential sensitive period when socioeconomic instability is especially important in shaping DNAm. Top SEP-related DNAm CpGs were overrepresented in genes involved in pathways important for neural development, immune function and metabolic processes. Our findings highlight the importance of socioeconomic stability during childhood and if replicated, may emphasize the need for public programs to help children and families experiencing socioeconomic instability and other forms of socioeconomic adversity.

Impact of cardiovascular health and genetic risk on coronary artery disease in Chinese adults

OBJECTIVE

To examine whether adherence to ideal cardiovascular health (CVH) can mitigate the genetic risk of coronary artery disease (CAD) in non-European populations.

METHODS

Fine and Grey's models were used to calculate HRs and their corresponding 95% CIs, as well as the lifetime risk of CVH metrics across Polygenic Risk Score (PRS) categories.

RESULTS

We included 39 755 individuals aged 30-75 years in Chinese prospective cohorts. 1275 CAD cases were recorded over a mean follow-up of 12.9 years. Compared with unfavourable CVH profile (zero to three ideal CVH metrics), favourable CVH profile (six to seven ideal CVH metrics) demonstrated similar relative effects across PRS categories, with the HRs of 0.40 (95% CI 0.24 to 0.67), 0.41 (95% CI 0.32 to 0.52) and 0.36 (95% CI 0.26 to 0.52) in low (bottom quintile of PRS), intermediate (two to four quintiles of PRS) and high (top quintile of PRS) PRS categories, respectively. For the absolute risk reduction (ARR), individuals with high PRS achieved the greatest benefit from favourable CVH, mitigating the risk to the average level of population (from 21.1% to 8.7%), and the gradient was strengthened in individuals at the top 5% of PRS. Moreover, compared with individuals at low PRS, those at high PRS obtained longer CAD-free years (2.6 vs 1.1) from favourable CVH at the index age of 35 years.

CONCLUSION

Favourable CVH profile reduced the CAD relative risk by similar magnitude across PRS categories, while the ARR from favourable CVH was most pronounced in high PRS category. Attaining favourable CVH should be encouraged for all individuals, especially in individuals with high genetic susceptibility.

The future of sickle cell disease therapeutics rests in genomics

Sickle cell disease (SCD) is the most-common monogenic recessive disease in humans, annually affecting almost 300,000 newborns worldwide, 75% of whom live in Africa. Genomics research can accelerate the development of curative therapies for SCD in three ways. First, research should explore the missing heritability of foetal haemoglobin (HbF) - the strongest known modifier of SCD clinical expression - among highly genetically heterogenous and understudied African populations, to provide novel therapeutics targets for HbF induction. Second, SCD research should invest in RNA therapies, either by using microRNA to target the production of HbF proteins by binding to the transcription machinery in a cell, or by directly mediating production of HbF or adult haemoglobin through injection of messenger RNA. Third, investigators should aim to identify currently unknown genetic risk factors for SCD cardiovascular complications, which will address mortality, particularly in adults. Now is the time for global research programs to uncover genomic keys to unlock SCD therapeutics.

New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.

Disparities in Inherited Retinal Degenerations

To review disparities in the field of inherited retinal degenerations to establish foundations for future discussions oriented toward finding possible solutions. A narrative overview of the literature. Despite collective efforts towards democratization of genetic testing and investigation, genetic databases containing primarily European populations are heavily relied upon. Access to specialized care and other resources is also still not available to all. Recognizing and addressing disparities and inequities within the field of inherited retinal degenerations will improve our care of these patients and our knowledge of their conditions.

Current advances in primate genomics: novel approaches for understanding evolution and disease

Primate genomics holds the key to understanding fundamental aspects of human evolution and disease. However, genetic diversity and functional genomics data sets are currently available for only a few of the more than 500 extant primate species. Concerted efforts are under way to characterize primate genomes, genetic polymorphism and divergence, and functional landscapes across the primate phylogeny. The resulting data sets will enable the connection of genotypes to phenotypes and provide new insight into aspects of the genetics of primate traits, including human diseases. In this Review, we describe the existing genome assemblies as well as genetic variation and functional genomic data sets. We highlight some of the challenges with sample acquisition. Finally, we explore how technological advances in single-cell functional genomics and induced pluripotent stem cell-derived organoids will facilitate our understanding of the molecular foundations of primate biology.

Consent Codes: Maintaining Consent in an Ever-expanding Open Science Ecosystem

We previously proposed a structure for recording consent-based data use 'categories' and 'requirements' - Consent Codes - with a view to supporting maximum use and integration of genomic research datasets, and reducing uncertainty about permissible re-use of shared data. Here we discuss clarifications and subsequent updates to the Consent Codes (v4) based on new areas of application (e.g., the neurosciences, biobanking, H3Africa), policy developments (e.g., return of research results), and further practical considerations, including developments in automated approaches to consent management.

Microvascular and macrovascular complications of type 2 diabetes mellitus: Exome wide association analyses

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a chronic, metabolic disorder in which concomitant insulin resistance and β-cell impairment lead to hyperglycemia, influenced by genetic and environmental factors. T2DM is associated with long-term complications that have contributed to the burden of morbidity and mortality worldwide. The objective of this manuscript is to conduct an Exome-Wide Association Study (EWAS) on T2DM Emirati individuals to improve our understanding on diabetes-related complications to improve early diagnostic methods and treatment strategies.

METHODS

This cross-sectional study recruited 310 Emirati participants that were stratified according to their medically diagnosed diabetes-related complications: diabetic retinopathy, diabetic neuropathy, diabetic nephropathy, and cardiovascular complications. The Illumina's Infinium Exome-24 array was used and 39,840 SNPs remained for analysis after quality control.

FINDINGS

The analysis revealed the associations of various genes with each complication category: 1) diabetic retinopathy was associated to SHANK3 gene in locus 22q13.33 (SNP rs9616915; p=5.18 x10^-4), ZSCAN5A gene in locus 19q13.43 (SNP rs7252603; p=7.55 x10^-4), and DCP1B gene in locus 12p13.33 (SNPs rs715146, rs1044950, rs113147414, rs34730825; p=7.62 x10^-4); 2) diabetic neuropathy was associated to ADH4 gene in locus 4q23 (SNP rs4148883; p=1.23 x10^-4), SLC11A1 gene in locus 2q35 (SNP rs17235409; p=1.85 x10^-4), and MATN4 gene in locus 20q13.12 (SNP rs2072788; p=2.68 x10^-4); 3) diabetic nephropathy was associated to PPP1R3A gene in locus 7q31.1 (SNP rs1799999; p=1.91 x10^-4), ZNF136 gene in locus 19p13.2 (SNP rs140861589; p=2.80 x10^-4), and HSPA12B gene in locus 20p13 (SNP rs6076550; p=2.86 x10^-4); and 4) cardiovascular complications was associated to PCNT gene in locus 21q22.3 (SNPs rs7279204, rs6518289, rs2839227, rs2839223; p=2.18 x10^-4,3.04 x10^-4,4.51 x10^-4,5.22 x10^-4 respectively), SEPT14 gene in locus 7p11.2 (SNP rs146350220; p=2.77 x10^-4), and WDR73 gene in locus 15q25.2 (SNP rs72750868; p=4.47 x10^-4).

INTERPRETATION

We have identified susceptibility loci associated with each category of T2DM-related complications in the Emirati population. Given that only 16% of the markers from the Illumina's Infinium Exome chip passed quality control assessment, this demonstrates that multiple variants were, either, monomorphic in the Arab population or were not genotyped due to the use of a Euro-centric EWAS array that limits the possibility of including targeted ethnic-specific SNPs. Our results suggest the alarming possibility that lack of representation in reference panels could inhibit discovery of functionally important loci associated to T2DM complications. Further effort must be conducted to improve the representation of diverse populations in genotyping and sequencing studies.

Monogenic Causes in Familial Stroke Across Intracerebral Hemorrhage and Ischemic Stroke Subtypes Identified by Whole-Exome Sequencing

Whole exome sequencing (WES) has been used to detect rare causative variants in neurological diseases. However, the efficacy of WES in genetic diagnosis of clinically heterogeneous familial stroke remains inconclusive. We prospectively searched for disease-causing variants in unrelated probands with defined familial stroke by candidate gene/hotspot screening and/or WES, depending on stroke subtypes and neuroimaging features at a referral center. The clinical significance of each variant was determined according to the American College of Medical Genetics guidelines. Among 161 probands (mean age at onset 53.2 ± 13.7 years; male 63.4%), 33 participants (20.5%) had been identified with 19 pathogenic/likely pathogenic variants (PVs; WES applied 152/161 = 94.4%). Across subtypes, the highest hit rate (HR) was intracerebral hemorrhage (ICH, 7/18 = 38.9%), particularly with the etiological subtype of structural vasculopathy (4/4 = 100%, PVs in ENG, KRIT1, PKD1, RNF213); followed by ischemic small vessel disease (SVD, 15/48 = 31.3%; PVs in NOTCH3, HTRA1, HBB). In contrast, large artery atherosclerosis (LAA, 4/44 = 9.1%) and cardioembolism (0/11 = 0%) had the lowest HR. NOTCH3 was the most common causative gene (16/161 = 9.9%), presenting with multiple subtypes of SVD (n = 13), ICH (n = 2), or LAA (n = 1). Importantly, we disclosed two previously unreported PVs, KRIT1 p.E379* in a familial cerebral cavernous malformation, and F2 p.F382L in a familial cerebral venous sinus thrombosis. The contribution of monogenic etiologies was particularly high in familial ICH and SVD subtypes in our Taiwanese cohort. Utilizing subtype-guided hotspot screening and/or subsequent WES, we unraveled monogenic causes in 20.5% familial stroke probands, including 1.2% novel PVs. Genetic diagnosis may enable early diagnosis, management and lifestyle modification. Among 161 familial stroke probands, 33 (20.5%) had been identified pathogenic or likely pathogenic monogenic variants related to stroke. The positive hit rate among all subtypes was high in intracerebral hemorrhage (ICH) and ischemic small vessel disease (SVD). Notably, two previously unreported variants, KRIT1 p.E379* in a familial cerebral cavernous malformation and F2 p.F382L in familial cerebral venous sinus thrombosis, were disclosed. CVT cerebral venous thrombosis; HTN Hypertensive subtype; LAA large artery atherosclerosis; SV structural vasculopathy; U Undetermined.

Analysis of clinically relevant variants from ancestrally diverse Asian genomes

Asian populations are under-represented in human genomics research. Here, we characterize clinically significant genetic variation in 9051 genomes representing East Asian, South Asian, and severely under-represented Austronesian-speaking Southeast Asian ancestries. We observe disparate genetic risk burden attributable to ancestry-specific recurrent variants and identify individuals with variants specific to ancestries discordant to their self-reported ethnicity, mostly due to cryptic admixture. About 27% of severe recessive disorder genes with appreciable carrier frequencies in Asians are missed by carrier screening panels, and we estimate 0.5% Asian couples at-risk of having an affected child. Prevalence of medically-actionable variant carriers is 3.4% and a further 1.6% harbour variants with potential for pathogenic classification upon additional clinical/experimental evidence. We profile 23 pharmacogenes with high-confidence gene-drug associations and find 22.4% of Asians at-risk of Centers for Disease Control and Prevention Tier 1 genetic conditions concurrently harbour pharmacogenetic variants with actionable phenotypes, highlighting the benefits of pre-emptive pharmacogenomics. Our findings illuminate the diversity in genetic disease epidemiology and opportunities for precision medicine for a large, diverse Asian population.

Can genomic research make a useful contribution to social policy?

As genetic research into outcomes beyond health gathers pace, largely through the use of genome-wide association studies, interest from policy-makers has grown. In the last year, two UK reports have explored the policy implications of genomic research, one from the UK Government Office for Science and one from the Early Intervention Foundation. In this article, we explore areas of consensus between these two reports and use them to propose priorities for policy-makers as we prepare for what some have termed a 'genetic revolution'. Both reports agree on two clear recommendations for science and policy communities. One of these relates to public education and engagement, and the other to ensuring that genomic databases are ancestrally diverse. Both reports agree that-even if it is found to be a viable and ethical idea in the medium-term future-DNA data should not be incorporated into social policy before these two issues have been comprehensively addressed. In the article, we argue that scientists are taking the lead on tackling the diversity deficit but that there is a clear role for policy-makers to play in addressing low genetic literacy in society, and that this is a matter of urgency.

Advancing mRNA technologies for therapies and vaccines: An African context

Synthetic mRNA technologies represent a versatile platform that can be used to develop advanced drug products. The remarkable speed with which vaccine development programs designed and manufactured safe and effective COVID-19 vaccines has rekindled interest in mRNA technology, particularly for future pandemic preparedness. Although recent R&D has focused largely on advancing mRNA vaccines and large-scale manufacturing capabilities, the technology has been used to develop various immunotherapies, gene editing strategies, and protein replacement therapies. Within the mRNA technologies toolbox lie several platforms, design principles, and components that can be adapted to modulate immunogenicity, stability, in situ expression, and delivery. For example, incorporating modified nucleotides into conventional mRNA transcripts can reduce innate immune responses and improve in situ translation. Alternatively, self-amplifying RNA may enhance vaccine-mediated immunity by increasing antigen expression. This review will highlight recent advances in the field of synthetic mRNA therapies and vaccines, and discuss the ongoing global efforts aimed at reducing vaccine inequity by establishing mRNA manufacturing capacity within Africa and other low- and middle-income countries.

Pharmacogenetic Variation and Its Clinical Relevance in a Latin American Rural Population

Latin-American populations have been largely underrepresented in genomic studies of drug response and disease susceptibility. In this paper, we present a genome-wide Chilean dataset from Talca based on the Illumina Global Screening Array. This let us to compare the frequency of gene variants involved in response to drugs among our population and others, taking data from the 1000 Genomes Project. We found four single-nucleotide polymorphisms with low prevalence in Chileans when compared with African, Amerindian, East and South Asian, and European populations: rs2819742 (RYR2), rs2631367 (SLC22A5), rs1063320 (HLA-G), and rs1042522 (TP53). Moreover, two markers showed significant differences between lower and higher proportion of Mapuche ancestry groups: rs1719247 (located in an intergenic region in chromosome 15; p-value = 6.17 × 10⁻⁵, Bonferroni corrected p-value = 0.02) and rs738409 (A nonsynonymous gene variant in the PNPLA3 gene; p-value = 9.02 × 10⁻⁵, Bonferroni corrected p-value = 0.04). All of these polymorphisms have been shown to be associated with diverse pathologies, such as asthma, cancer, or chronic hepatitis B, or to be involved in a different response to drugs, such as metformin, HMG-CoA reductase inhibitors, or simvastatin. The present work provides a pharmacogenetic landscape of an understudied Latin American rural population and supports the notion that pharmacogenetic studies in admixed populations should consider ancestry for a higher accuracy of the results. Our study stresses the relevance of the pharmacogenomic research to provide guidance for a better choice of the best treatment for each individual in a population with admixed ancestry.

Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

African-specific alleles modify risk for asthma at the 17q12-q21 locus in African Americans

BACKGROUND

Asthma is the most common chronic disease in children, occurring at higher frequencies and with more severe disease in children with African ancestry.

METHODS

We tested for association with haplotypes at the most replicated and significant childhood-onset asthma locus at 17q12-q21 and asthma in European American and African American children. Following this, we used whole-genome sequencing data from 1060 African American and 100 European American individuals to identify novel variants on a high-risk African American-specific haplotype. We characterized these variants in silico using gene expression and ATAC-seq data from airway epithelial cells, functional annotations from ENCODE, and promoter capture (pc)Hi-C maps in airway epithelial cells. Candidate causal variants were then assessed for correlation with asthma-associated phenotypes in African American children and adults.

RESULTS

Our studies revealed nine novel African-specific common variants, enriched on a high-risk asthma haplotype, which regulated the expression of GSDMA in airway epithelial cells and were associated with features of severe asthma. Using ENCODE annotations, ATAC-seq, and pcHi-C, we narrowed the associations to two candidate causal variants that are associated with features of T2 low severe asthma.

CONCLUSIONS

Previously unknown genetic variation at the 17q12-21 childhood-onset asthma locus contributes to asthma severity in individuals with African ancestries. We suggest that many other population-specific variants that have not been discovered in GWAS contribute to the genetic risk for asthma and other common diseases.

Detecting associated genes for complex traits shared across East Asian and European populations under the framework of composite null hypothesis testing

Background

Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking.

Methods

By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement.

Results

Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones.

Conclusion

Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03637-8.

Pharmacogenetics of Cardiovascular Prevention in Diabetes: From Precision Medicine to Identification of Novel Targets

Pharmacogenetics—a branch of precision medicine—holds the promise of becoming a novel tool to reduce the social and healthcare burdens of cardiovascular disease (CVD) and coronary artery disease (CAD) in diabetes. The improvement in cardiovascular risk stratification resulting from adding genetic characteristics to clinical data has moved from the modest results obtained with genetic risk scores based on few genetic variants, to the progressively better performances of polygenic risk scores based on hundreds to millions of variants (CAD-PGRS). Similarly, over the past few years, the number of studies investigating the use of CAD-PGRS to identify different responses to cardio-preventive treatment has progressively increased, yielding striking results for lipid-lowering drugs such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and statins. The use of CAD-PGRS to stratify patients based on their likely response to diabetes-specific interventions has been less successful, but promising results have been obtained with regard to specific genetic variants modulating the effects of interventions such as intensive glycemic control and fenofibrate. The finding of diabetes-specific CAD-loci, such as GLUL, has also led to the identification of promising new targets that might hopefully result in the development of specific therapies to reduce CVD burden in patients with diabetes. As reported in consensus statements from international diabetes societies, some of these pharmacogenetic approaches are expected to be introduced in clinical practice over the next decade. For this to happen, in addition to continuing to improve and validate these tools, it will be necessary to educate physicians and patients about the opportunities and limits of pharmacogenetics, as summarized in this review.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Sodium-calcium exchanger-3 regulates pain "wind-up": From human psychophysics to spinal mechanisms

Repeated application of noxious stimuli leads to a progressively increased pain perception; this temporal summation is enhanced in and predictive of clinical pain disorders. Its electrophysiological correlate is "wind-up," in which dorsal horn spinal neurons increase their response to repeated nociceptor stimulation. To understand the genetic basis of temporal summation, we undertook a GWAS of wind-up in healthy human volunteers and found significant association with SLC8A3 encoding sodium-calcium exchanger type 3 (NCX3). NCX3 was expressed in mouse dorsal horn neurons, and mice lacking NCX3 showed normal, acute pain but hypersensitivity to the second phase of the formalin test and chronic constriction injury. Dorsal horn neurons lacking NCX3 showed increased intracellular calcium following repetitive stimulation, slowed calcium clearance, and increased wind-up. Moreover, virally mediated enhanced spinal expression of NCX3 reduced central sensitization. Our study highlights Ca2+ efflux as a pathway underlying temporal summation and persistent pain, which may be amenable to therapeutic targeting.

Transferability of genetic loci and polygenic scores for cardiometabolic traits in British Pakistani and Bangladeshi individuals

Individuals with South Asian ancestry have a higher risk of heart disease than other groups but have been largely excluded from genetic research. Using data from 22,000 British Pakistani and Bangladeshi individuals with linked electronic health records from the Genes & Health cohort, we conducted genome-wide association studies of coronary artery disease and its key risk factors. Using power-adjusted transferability ratios, we found evidence for transferability for the majority of cardiometabolic loci powered to replicate. The performance of polygenic scores was high for lipids and blood pressure, but lower for BMI and coronary artery disease. Adding a polygenic score for coronary artery disease to clinical risk factors showed significant improvement in reclassification. In Mendelian randomisation using transferable loci as instruments, our findings were consistent with results in European-ancestry individuals. Taken together, trait-specific transferability of trait loci between populations is an important consideration with implications for risk prediction and causal inference.

Early Diagnosis, Early Stratification, and Early Intervention to Deliver Precision Medicine in IBD

Despite huge advances in understanding the molecular basis of IBD, clinical management has continued to rely on a "trial and error" approach. In addition, a therapeutic ceiling has emerged whereby even the most effective interventions are only beneficial for approximately 30% of patients. Consequently, several tools have been developed to aid stratification and guide treatment-decisions. We review the potential application for many of these precision medicine approaches, which are now almost within reach. We highlight the importance of early action (and avoiding inaction) to ensure the best outcomes for patients and how combining early action with precision tools will likely ensure the right treatment is delivered at the right time and place for each individual person living with IBD. The lack of clinical impact to date from precision medicine, despite much hype and investment, should be tempered with the knowledge that clinical translation can take a long time, and many promising breakthroughs might be ready for clinical implementation in the near future. We discuss some of the remaining challenges and barriers to overcome for clinical adoption. We also highlight that early recognition, early diagnosis, early stratification, and early intervention go hand in hand with precision medicine tools. It is the combination of these approaches that offer the greatest opportunity to finally deliver on the promise of precision medicine in IBD.

Leveraging the local genetic structure for trans-ancestry association mapping

Over the past two decades, genome-wide association studies (GWASs) have successfully advanced our understanding of the genetic basis of complex traits. Despite the fruitful discovery of GWASs, most GWAS samples are collected from European populations, and these GWASs are often criticized for their lack of ancestry diversity. Trans-ancestry association mapping (TRAM) offers an exciting opportunity to fill the gap of disparities in genetic studies between non-Europeans and Europeans. Here, we propose a statistical method, LOG-TRAM, to leverage the local genetic architecture for TRAM. By using biobank-scale datasets, we showed that LOG-TRAM can greatly improve the statistical power of identifying risk variants in under-represented populations while producing well-calibrated p values. We applied LOG-TRAM to the GWAS summary statistics of various complex traits/diseases from BioBank Japan, UK Biobank, and African populations. We obtained substantial gains in power and achieved effective correction of confounding biases in TRAM. Finally, we showed that LOG-TRAM can be successfully applied to identify ancestry-specific loci and the LOG-TRAM output can be further used for construction of more accurate polygenic risk scores in under-represented populations.

Ethical, legal and social/societal implications (ELSI) of recall-by-genotype (RbG) and genotype-driven-research (GDR) approaches: a scoping review

Recall by Genotype (RbG), Genotype-driven-recall (GDR), and Genotype-based-recall (GBR) strategies are increasingly used to conduct genomic or biobanking sub-studies that single out participants as eligible because of their specific individual genotypic information. However, existing regulatory and governance frameworks do not apply to all aspects of genotype-driven research approaches. The recall strategies disclose or withhold personal genotypic information with uncertain clinical utility. Accordingly, this scoping review aims to identify peculiar, explicit and implicit ethical, legal, and societal/social implications (ELSI) of RbG study designs. We conducted a systematic literature search of three electronic databases from November 2020 to February 2021. We investigated qualitative and quantitative research methods used to report ELSI aspects in RbG research. Congruent with other research findings, we identified a lack of qualitative research investigating the particular ELSI challenges with RbG. We included and analysed the content of twenty-five publications. We found a consensus on RbG posing significant ethical issues, dilemmas, barriers, concerns and societal challenges. However, we found that the approaches to disclosure and study-specific recall and communication strategies employed consent models and Return of Research Results (RoRR) policies varied considerably. Furthermore, we identified a high heterogeneity in perspectives of participants and experts about ELSI of study-specific RbG policies. Therefore, further fine-mapping through qualitative and empirical research is needed to draw conclusions and re-fine ELSI frameworks.

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

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

Five Priorities of African Genomics Research: The Next Frontier

To embrace the prospects of accurately diagnosing thousands of monogenic conditions, predicting disease risks for complex traits or diseases, tailoring treatment to individuals' pharmacogenetic profiles, and potentially curing some diseases, research into African genomic variation is a scientific imperative. African genomes harbor millions of uncaptured variants accumulated over 300,000 years of modern humans' evolutionary history, with successive waves of admixture, migration, and natural selection combining with extensive ecological diversity to create a broad and exceptional genomic complexity. Harnessing African genomic complexity, therefore, will require sustained commitment and equitable collaboration from the scientific community and funding agencies. African governments must support academic public research and industrial partnerships that build the necessary genetic medicine workforce, utilize the emerging genomic big data to develop expertise in computer science and bioinformatics, and evolve national and global governance frameworks that recognize the ethical implications of data-driven genomic research and empower its application in African social, cultural, economic, and religious contexts. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Stability of polygenic scores across discovery genome-wide association studies

Polygenic scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual level when phenotypes are not necessarily already known. We investigated the stability of PGS in European American (EUR) and African American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort and the Adolescent Brain Cognitive Development study using different discovery genome-wide association study (GWAS) results for post-traumatic stress disorder (PTSD), type 2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations >0.92. However, PGS calculated from pairs of same-ancestry and different-ancestry GWAS had correlations that ranged from <0.01 to 0.74. PGS stability was greater for height than for PTSD or T2D. A series of height GWAS in the UK Biobank suggested that correlation between PGS is strongly dependent on the extent of sample overlap between the discovery GWAS. Focusing on the upper end of the PGS distribution, different discovery GWAS do not consistently identify the same individuals in the upper quantiles, with the best case being 60% of individuals above the 80th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the individual level, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications.

Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores

Polygenic risk scores suffer reduced accuracy in non-European populations, exacerbating health disparities. We propose PolyPred, a method that improves cross-population polygenic risk scores by combining two predictors: a new predictor that leverages functionally informed fine-mapping to estimate causal effects (instead of tagging effects), addressing linkage disequilibrium differences, and BOLT-LMM, a published predictor. When a large training sample is available in the non-European target population, we propose PolyPred+, which further incorporates the non-European training data. We applied PolyPred to 49 diseases/traits in four UK Biobank populations using UK Biobank British training data, and observed relative improvements versus BOLT-LMM ranging from +7% in south Asians to +32% in Africans, consistent with simulations. We applied PolyPred+ to 23 diseases/traits in UK Biobank east Asians using both UK Biobank British and Biobank Japan training data, and observed improvements of +24% versus BOLT-LMM and +12% versus PolyPred. Summary statistics-based analogs of PolyPred and PolyPred+ attained similar improvements.

Comethyl: a network-based methylome approach to investigate the multivariate nature of health and disease

Health outcomes are frequently shaped by difficult to dissect inter-relationships between biological, behavioral, social and environmental factors. DNA methylation patterns reflect such multivariate intersections, providing a rich source of novel biomarkers and insight into disease etiologies. Recent advances in whole-genome bisulfite sequencing enable investigation of DNA methylation over all genomic CpGs, but existing bioinformatic approaches lack accessible system-level tools. Here, we develop the R package Comethyl, for weighted gene correlation network analysis of user-defined genomic regions that generates modules of comethylated regions, which are then tested for correlations with multivariate sample traits. First, regions are defined by CpG genomic location or regulatory annotation and filtered based on CpG count, sequencing depth and variability. Next, correlation networks are used to find modules of interconnected nodes using methylation values within the selected regions. Each module containing multiple comethylated regions is reduced in complexity to a single eigennode value, which is then tested for correlations with experimental metadata. Comethyl has the ability to cover the noncoding regulatory regions of the genome with high relevance to interpretation of genome-wide association studies and integration with other types of epigenomic data. We demonstrate the utility of Comethyl on a dataset of male cord blood samples from newborns later diagnosed with autism spectrum disorder (ASD) versus typical development. Comethyl successfully identified an ASD-associated module containing regions mapped to genes enriched for brain glial functions. Comethyl is expected to be useful in uncovering the multivariate nature of health disparities for a variety of common disorders. Comethyl is available at github.com/cemordaunt/comethyl with complete documentation and example analyses.

A polygenic risk score improves risk stratification of coronary artery disease: a large-scale prospective Chinese cohort study

Aims

To construct a polygenic risk score (PRS) for coronary artery disease (CAD) and comprehensively evaluate its potential in clinical utility for primary prevention in Chinese populations.

Methods and results

Using meta-analytic approach and large genome-wide association results for CAD and CAD-related traits in East Asians, a PRS comprising 540 genetic variants was developed in a training set of 2800 patients with CAD and 2055 controls, and was further assessed for risk stratification for CAD integrating with the guideline-recommended clinical risk score in large prospective cohorts comprising 41 271 individuals. During a mean follow-up of 13.0 years, 1303 incident CAD cases were identified. Individuals with high PRS (the highest 20%) had about three-fold higher risk of CAD than the lowest 20% (hazard ratio 2.91, 95% confidence interval 2.43–3.49), with the lifetime risk of 15.9 and 5.8%, respectively. The addition of PRS to the clinical risk score yielded a modest yet significant improvement in C-statistic (1%) and net reclassification improvement (3.5%). We observed significant gradients in both 10-year and lifetime risk of CAD according to the PRS within each clinical risk strata. Particularly, when integrating high PRS, intermediate clinical risk individuals with uncertain clinical decision for intervention would reach the risk levels (10-year of 4.6 vs. 4.8%, lifetime of 17.9 vs. 16.6%) of high clinical risk individuals with intermediate (20–80%) PRS.

Conclusion

The PRS could stratify individuals into different trajectories of CAD risk, and further refine risk stratification for CAD within each clinical risk strata, demonstrating a great potential to identify high-risk individuals for targeted intervention in clinical utility.

Public human microbiome data are dominated by highly developed countries

The importance of sampling from globally representative populations has been well established in human genomics. In human microbiome research, however, we lack a full understanding of the global distribution of sampling in research studies. This information is crucial to better understand global patterns of microbiome-associated diseases and to extend the health benefits of this research to all populations. Here, we analyze the country of origin of all 444,829 human microbiome samples that are available from the world’s 3 largest genomic data repositories, including the Sequence Read Archive (SRA). The samples are from 2,592 studies of 19 body sites, including 220,017 samples of the gut microbiome. We show that more than 71% of samples with a known origin come from Europe, the United States, and Canada, including 46.8% from the US alone, despite the country representing only 4.3% of the global population. We also find that central and southern Asia is the most underrepresented region: Countries such as India, Pakistan, and Bangladesh account for more than a quarter of the world population but make up only 1.8% of human microbiome samples. These results demonstrate a critical need to ensure more global representation of participants in microbiome studies.

The importance of sampling from globally representative populations has been well established in human genomics, but what about the microbiome? This study shows that metadata from almost half a million samples reveals worldwide human microbiome research is skewed heavily in favor of Europe and North America and excludes large but less developed nations in Asia and Africa.

GSTM1 and GSTT1 polymorphisms in healthy volunteers - a worldwide systematic review

The GSTM1 and GSTT1 genes encode homonymous enzymes, which are responsible for the detoxification of several substances potentially harmful to the human body, such as air pollution, drugs, pesticides, and tobacco. However, some individuals may present a complete deletion of these genes and, consequently, an enzyme deficiency leading to an inadequate metabolism and, therefore, a higher susceptibility to some clinical conditions. Interethnic variations have also been described for both genes, making necessary the study of the deletion frequencies of GSTM1 and GSTT1 in different populations around the world. So, the aim of this study was to enable the synthesis and discussion of the main population differences of GSTM1 and GSTT1 polymorphisms in healthy volunteers. Searches were performed in the PubMed database, including 533 articles and 178,566 individuals in the analyses. We found an overrepresentation of European individuals and studies, and an underrepresentation of non-European ethnicities. Moreover, there are significant frequency differences among distinct ethnic groups: East Asians present the highest frequencies worldwide for GSTM1 and GSTT1 deletions, which could suggest higher disorders risk for this population; in contrast, Sub-Saharan Africans presented the lowest frequency of GSTM1 worldwide, corroborating evolution inferences performed previously for other genes codifying metabolism enzymes. Also, admixture is a relevant component when analyzing frequency values for both genes, but further studies focusing on this subject are warranted.

Analyses of biomarker traits in diverse UK biobank participants identify associations missed by European-centric analysis strategies

Despite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, as well as variants rare in European populations, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n = 9354), East Asian (n = 2559), and South Asian (n = 9823) ancestry UK Biobank (UKBB) participants. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in a recent European ancestry-focused analysis of UKBB participants. We identify 7 novel signals in African ancestry and 2 novel signals in South Asian ancestry participants (p < 1.61E-10). Many of these signals are highly plausible, including a cis pQTL for the gene encoding gamma-glutamyl transferase and PIEZO1 and G6PD variants with impacts on HbA1c through likely erythrocytic mechanisms. This work illustrates the importance of using the genetic data we already have in diverse populations, with novel discoveries possible in even modest sample sizes.

Who's afraid of genetic tests?: An assessment of Singapore's public attitudes and changes in attitudes after taking a genetic test

BACKGROUND

As a consequence of precision medicine initiatives, genomic technologies have rapidly spread around the world, raising questions about genetic privacy and the ethics of data sharing. Previous scholarship in bioethics and science and technology studies has made clear that different nations have varying expectations about trust, transparency, and public reason in relation to emerging technologies and their governance. The key aims of this article are to assess genetic literacy, perceptions of genetic testing, privacy concerns, and governing norms amongst the Singapore population by collecting surveys.

METHODS

This study investigated genetic literacy and broad public attitudes toward genetic tests in Singapore with an online public survey (n = 560). To assess potential changes in attitudes following receipt of results from a genetic test, we also surveyed undergraduate students who underwent a genetic screen as part of a university class before and after they received their test results (n = 25).

RESULTS

Public participants showed broad support for the use of genetic tests; scored an average of 48.9% in genetic literacy; and expressed privacy concerns over data sharing and a desire for control over their genetic data. After taking a genetic test and receiving genetic test results, students reported less fear of genetic tests while other attitudes did not change significantly.

CONCLUSION

These findings highlight the potential of genetic education and active engagement with genetic testing to increase support and participation in genomic projects, PM, and biobanking initiatives; and they suggest that data privacy protections could potentially reduce discrimination by giving participants control over who can access their data. More specifically, these findings and the dataset we provide may be helpful in formulating culturally sensitive education programs and regulations concerning genomic technologies and data privacy.

Harnessing big data to characterize immune-related adverse events

Immune-checkpoint inhibitors (ICIs) have transformed patient care in oncology but are associated with a unique spectrum of organ-specific inflammatory toxicities known as immune-related adverse events (irAEs). Given the expanding use of ICIs, an increasing number of patients with cancer experience irAEs, including severe irAEs. Proper diagnosis and management of irAEs are important to optimize the quality of life and long-term outcomes of patients receiving ICIs; however, owing to the substantial heterogeneity within irAEs, and despite multicentre initiatives, performing clinical studies of these toxicities with a sufficient cohort size is challenging. Pioneering studies from the past few years have demonstrated that aggregate clinical data, real-world data (such as data on pharmacovigilance or from electronic health records) and multi-omics data are alternative tools well suited to investigating the underlying mechanisms and clinical presentations of irAEs. In this Perspective, we summarize the advantages and shortcomings of different sources of 'big data' for the study of irAEs and highlight progress made using such data to identify biomarkers of irAE risk, evaluate associations between irAEs and therapeutic efficacy, and characterize the effects of demographic and anthropometric factors on irAE risk. Harnessing big data will accelerate research on irAEs and provide key insights that will improve the clinical management of patients receiving ICIs.

Health equality, race and pharmacogenomics

Pharmacogenomics is increasingly moving into mainstream clinical practice. Careful consideration must be paid to inclusion of diverse populations in research, translation and implementation, in the historical and social context of population stratification, to ensure that this leads to improvements in healthcare for all rather than increased health disparities. This review takes a broad and critical approach to the current role of diversity in pharmacogenomics and addresses potential pitfalls in order to raise awareness for prescribers. It also emphasizes evidence gaps and suggests approaches that may minimize negative consequences and promote health equality.

Genome-Wide Admixture Mapping of Estimated Glomerular Filtration Rate and Chronic Kidney Disease Identifies European and African Ancestry-of-Origin Loci in Hispanic and Latino Individuals in the United States

BACKGROUND

Admixture mapping is a powerful approach for gene mapping of complex traits that leverages the diverse genetic ancestry in populations with recent admixture, such as Hispanic or Latino individuals in the United States. These individuals have an increased risk of CKD.

METHODS

We performed genome-wide admixture mapping for both CKD and eGFR in a sample of 12,601 participants from the Hispanic Community Health Study/Study of Latinos, with validation in a sample of 8191 Black participants from the Women's Health Initiative (WHI). We also compared the findings with those from a conventional genome-wide association study.

RESULTS

Three novel ancestry-of-origin loci were identified on chromosomes 2, 14, and 15 for CKD and eGFR. The chromosome 2 locus comprises two European ancestry regions encompassing the FSHR and NRXN1 genes, with European ancestry at this locus associated with increased CKD risk. The chromosome 14 locus, found within the DLK1-DIO3 imprinted domain, was associated with lower eGFR and driven by European ancestry. The eGFR-associated locus on chromosome 15 included intronic variants of RYR3 and was within an African-specific genomic region associated with higher eGFR. The genome-wide association study failed to identify significant associations in these regions. We validated the chromosome 14 and 15 loci associated with eGFR in the WHI Black participants.

CONCLUSIONS

This study provides evidence of shared ancestry-specific genomic regions influencing eGFR in Hispanic or Latino individuals and Black individuals and illustrates the potential for leveraging genetic ancestry in recently admixed populations for the discovery of novel candidate loci for kidney phenotypes.

Genomics and Functional Genomics of Alzheimer's Disease

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5-10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.

Clinical validation of genomic functional screen data: analysis of observed BRCA1 variants in an unselected population cohort

Functional assessment of genomic variants provides a promising approach to systematically examine the potential pathogenicity of variants independent of associated clinical data. However, making such conclusions requires validation with appropriate clinical findings. To this end, here, we use variant calls from exome data and BRCA1-related cancer diagnoses from electronic health records to demonstrate an association between published laboratory-based functional designations of BRCA1 variants and BRCA1-related cancer diagnoses in an unselected cohort of patient-participants. These findings validate and support further exploration of functional assay data to better understand the pathogenicity of rare variants. This information may be valuable in the context of healthy population genomic screening, where many rare, potentially pathogenic variants may not have sufficient associated clinical data to inform their interpretation directly.

Missing lnc(RNAs) in Alzheimer's Disease?

With the ongoing demographic shift towards increasingly elderly populations, it is estimated that approximately 150 million people will live with Alzheimer's disease (AD) by 2050. By then, AD will be one of the most burdensome diseases of this and potentially next centuries. Although its exact etiology remains elusive, both environmental and genetic factors play crucial roles in the mechanisms underlying AD neuropathology. Genome-wide association studies (GWAS) identified genetic variants associated with AD susceptibility in more than 40 different genomic loci. Most of these disease-associated variants reside in non-coding regions of the genome. In recent years, it has become clear that functionally active transcripts arise from these non-coding loci. One type of non-coding transcript, referred to as long non-coding RNAs (lncRNAs), gained significant attention due to their multiple roles in neurodevelopment, brain homeostasis, aging, and their dysregulation or dysfunction in neurological diseases including in AD. Here, we will summarize the current knowledge regarding genetic variations, expression profiles, as well as potential functions, diagnostic or therapeutic roles of lncRNAs in AD. We postulate that lncRNAs may represent the missing link in AD pathology and that unraveling their role may open avenues to better AD treatments.

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.

Polygenic risk for coronary artery disease in the Scottish and English population

Background

Epidemiological studies have repeatedly observed a markedly higher risk for coronary artery disease (CAD) in Scotland as compared to England. Up to now, it is unclear whether environmental or genetic factors might explain this phenomenon.

Methods

Using UK Biobank (UKB) data, we assessed CAD risk, based on the Framingham risk score (FRS) and common genetic variants, to explore the respective contribution to CAD prevalence in Scotland (n = 31,963) and England (n = 317,889). We calculated FRS based on sex, age, body mass index (BMI), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), antihypertensive medication, smoking status, and diabetes. We determined the allele frequency of published genome-wide significant risk CAD alleles and a weighted genetic risk score (wGRS) for quantifying genetic CAD risk.

Results

Prevalence of CAD was 16% higher in Scotland as compared to England (8.98% vs. 7.68%, P < 0.001). However, the FRS only predicted a marginally higher CAD risk (less than 1%) in Scotland (12.5 ± 10.5 vs.12.6 ± 10.6, P = 0.03). Likewise, the overall number of genome-wide significant variants affecting CAD risk (157.6 ± 7.7 and 157.5 ± 7.7; P = 0.12) and a wGRS for CAD (2.49 ± 0.25 in both populations, P = 0.14) were remarkably similar in the English and Scottish population. Interestingly, we observed substantial differences in the allele frequencies of individual risk variants. Of the previously described 163 genome-wide significant variants studied here, 35 variants had higher frequencies in Scotland, whereas 37 had higher frequencies in England (P < 0.001 each).

Conclusions

Neither the traditional risk factors included in the FRS nor a genetic risk score (GRS) based on established common risk alleles explained the higher CAD prevalence in Scotland. However, we observed marked differences in the distribution of individual risk alleles, which emphasizes that even geographically and ethnically closely related populations may display relevant differences in the genetic architecture of a common disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02398-4.

Hypertension genetics past, present and future applications

Essential hypertension is a complex trait where the underlying aetiology is not completely understood. Left untreated it increases the risk of severe health complications including cardiovascular and renal disease. It is almost 15 years since the first genome-wide association study for hypertension, and after a slow start there are now over 1000 blood pressure (BP) loci explaining ∼6% of the single nucleotide polymorphism-based heritability. Success in discovery of hypertension genes has provided new pathological insights and drug discovery opportunities and translated to the development of BP genetic risk scores (GRSs), facilitating population disease risk stratification. Comparing highest and lowest risk groups shows differences of 12.9 mm Hg in systolic-BP with significant differences in risk of hypertension, stroke, cardiovascular disease and myocardial infarction. GRSs are also being trialled in antihypertensive drug responses. Drug targets identified include NPR1, for which an agonist drug is currently in clinical trials. Identification of variants at the PHACTR1 locus provided insights into regulation of EDN1 in the endothelin pathway, which is aiding the development of endothelin receptor EDNRA antagonists. Drug re-purposing opportunities, including SLC5A1 and canagliflozin (a type-2 diabetes drug), are also being identified. In this review, we present key studies from the past, highlight current avenues of research and look to the future focusing on gene discovery, epigenetics, gene-environment interactions, GRSs and drug discovery. We evaluate limitations affecting BP genetics, including ancestry bias and discuss streamlining of drug target discovery and applications for treating and preventing hypertension, which will contribute to tailored precision medicine for patients.

An Overview of Strategies for Detecting Genotype-Phenotype Associations Across Ancestrally Diverse Populations

Genome-wide association studies (GWAS) have been very successful at identifying genetic variants influencing a large number of traits. Although the great majority of these studies have been performed in European-descent individuals, it has been recognised that including populations with differing ancestries enhances the potential for identifying causal SNPs due to their differing patterns of linkage disequilibrium. However, when individuals from distinct ethnicities are included in a GWAS, it is necessary to implement a number of control steps to ensure that the identified associations are real genotype-phenotype relationships. In this Review, we discuss the analyses that are required when performing multi-ethnic studies, including methods for determining ancestry at the global and local level for sample exclusion, controlling for ancestry in association testing, and post-GWAS interrogation methods such as genomic control and meta-analysis. We hope that this overview provides a primer for those researchers interested in including distinct populations in their studies.

The limits of personalization in precision medicine: Polygenic risk scores and racial categorization in a precision breast cancer screening trial

Population-based genomic screening is at the forefront of a new approach to disease prevention. Yet the lack of diversity in genome wide association studies and ongoing debates about the appropriate use of racial and ethnic categories in genomics raise key questions about the translation of genomic knowledge into clinical practice. This article reports on an ethnographic study of a large pragmatic clinical trial of breast cancer screening called WISDOM (Women Informed to Screen Depending On Measures of Risk). Our ethnography illuminates the challenges of using race or ethnicity as a risk factor in the implementation of precision breast cancer risk assessment. Our analysis provides critical insights into how categories of race, ethnicity and ancestry are being deployed in the production of genomic knowledge and medical practice, and key challenges in the development and implementation of novel Polygenic Risk Scores in the research and clinical applications of this emerging science. Specifically, we show how the conflation of social and biological categories of difference can influence risk prediction for individuals who exist at the boundaries of these categories, affecting the perceptions and practices of scientists, clinicians, and research participants themselves. Our research highlights the potential harms of practicing genomic medicine using under-theorized and ambiguous categories of race, ethnicity, and ancestry, particularly in an adaptive, pragmatic trial where research findings are applied in the clinic as they emerge. We contribute to the expanding literature on categories of difference in post-genomic science by closely examining the implementation of a large breast cancer screening study that aims to personalize breast cancer risk using both common and rare genomic markers.

Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets

Polygenic risk prediction is a widely investigated topic because of its promising clinical applications. Genetic variants in functional regions of the genome are enriched for complex trait heritability. Here, we introduce a method for polygenic prediction, LDpred-funct, that leverages trait-specific functional priors to increase prediction accuracy. We fit priors using the recently developed baseline-LD model, including coding, conserved, regulatory, and LD-related annotations. We analytically estimate posterior mean causal effect sizes and then use cross-validation to regularize these estimates, improving prediction accuracy for sparse architectures. We applied LDpred-funct to predict 21 highly heritable traits in the UK Biobank (avg N = 373 K as training data). LDpred-funct attained a +4.6% relative improvement in average prediction accuracy (avg prediction R2 = 0.144; highest R2 = 0.413 for height) compared to SBayesR (the best method that does not incorporate functional information). For height, meta-analyzing training data from UK Biobank and 23andMe cohorts (N = 1107 K) increased prediction R2 to 0.431. Our results show that incorporating functional priors improves polygenic prediction accuracy, consistent with the functional architecture of complex traits.