Trans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci

Genetic control of DNA methylation is largely shared across European and East Asian populations

DNA methylation is an ideal trait to study the extent of the shared genetic control across ancestries, effectively providing hundreds of thousands of model molecular traits with large QTL effect sizes. We investigate cis DNAm QTLs in three European (n = 3701) and two East Asian (n = 2099) cohorts to quantify the similarities and differences in the genetic architecture across populations. We observe 80,394 associated mQTLs (62.2% of DNAm probes with significant mQTL) to be significant in both ancestries, while 28,925 mQTLs (22.4%) are identified in only a single ancestry. mQTL effect sizes are highly conserved across populations, with differences in mQTL discovery likely due to differences in allele frequency of associated variants and differing linkage disequilibrium between causal variants and assayed SNPs. This study highlights the overall similarity of genetic control across ancestries and the value of ancestral diversity in increasing the power to detect associations and enhancing fine mapping resolution.

Protein kinase D (PKD) on the crossroad of lipid absorption, synthesis and utilization

Inappropriate lipid levels in the blood, as well as its content and composition in different organs, underlie multiple metabolic disorders including obesity, non-alcoholic fatty liver disease, type 2 diabetes, and atherosclerosis. Multiple processes contribute to the complex metabolism of triglycerides (TGs), fatty acids (FAs), and other lipid species. These consist of digestion and absorption of dietary lipids, de novo FAs synthesis (lipogenesis), uptake of TGs and FAs by peripheral tissues, TGs storage in the intracellular depots as well as lipid utilization for β-oxidation and their conversion to lipid-derivatives. A majority of the enzymatic reactions linked to lipogenesis, TGs synthesis, lipid absorption, and transport are happening at the endoplasmic reticulum, while β-oxidation takes place in mitochondria and peroxisomes. The Golgi apparatus is a central sorting, protein- and lipid-modifying organelle and hence is involved in lipid metabolism as well. However, the impact of the processes taking part in the Golgi apparatus are often overseen. The protein kinase D (PKD) family (composed of three members, PKD1, 2, and 3) is the master regulator of Golgi dynamics. PKDs are also a sensor of different lipid species in distinct cellular compartments. In this review, we discuss the roles of PKD family members in the regulation of lipid metabolism including the processes executed by PKDs at the Golgi apparatus. We also discuss the role of PKDs-dependent signaling in different cellular compartments and organs in the context of the development of metabolic disorders.

Identification of potential genetic causal variants for obesity-related traits using statistical fine mapping

BACKGROUND

Obesity is highly influenced by heritability and variant effects. While previous genome-wide association studies (GWASs) have successfully identified numerous genetic loci associated with obesity-related traits [body mass index (BMI) and waist-to-hip ratio (WHR)], most causal variants remain unidentified. The high degree of linkage disequilibrium (LD) throughout the genome makes it extremely difficult to distinguish the GWAS-associated SNPs that exert a true biological effect.

OBJECTIVE

This study was to identify the potential causal variants having a biological effect on obesity-related traits.

METHODS

We used Probabilistic Annotation INTegratOR, a Bayesian fine-mapping method, which incorporated genetic association data (GWAS summary statistics), LD structure, and functional annotations to calculate a posterior probability of causality for SNPs across all loci of interest. Moreover, we performed gene expression analysis using the available public transcriptomic data to validate the corresponding genes of the potential causal SNPs partially.

RESULTS

We identified 96 SNPs for BMI and 43 SNPs for WHR with a high posterior probability of causality (> 99%), including 49 BMI SNPs and 24 WHR SNPs which did not reach genome-wide significance in the original GWAS. Finally, we partially validated some genes corresponding to the potential causal SNPs.

CONCLUSION

Using a statistical fine-mapping approach, we identified a set of potential causal variants to be prioritized for future functional validation and also detected some novel trait-associated variants. These results provided novel insight into our understanding of the genetics of obesity and also demonstrated that fine mapping may improve upon the results identified by the original GWASs.

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.

WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10-9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

New insights from GWAS on BMI-related growth traits in a longitudinal cohort of admixed children with Native American and European ancestry

Body-mass index (BMI) is a hallmark of adiposity. In contrast with adulthood, the genetic architecture of BMI during childhood is poorly understood. The few genome-wide association studies (GWAS) on children have been performed almost exclusively in Europeans and at single ages. We performed cross-sectional and longitudinal GWAS for BMI-related traits on 904 admixed children with mostly Mapuche Native American and European ancestries. We found regulatory variants of the immune gene HLA-DQB3 strongly associated with BMI at 1.5 - 2.5 years old. A variant in the sex-determining gene DMRT1 was associated with the age at adiposity rebound (Age-AR) in girls (P = 9.8 × 10 - 9 ). BMI was significantly higher in Mapuche than in Europeans between 5.5 and 16.5 years old. Finally, Age-AR was significantly lower (P = 0.004 ) by 1.94 years and BMI at AR was significantly higher (P = 0.04 ) by 1.2 kg/ m 2 , in Mapuche children compared with Europeans.

Polymorphism of LYPLAL1 and TGFA Genes Associated With Progression of Knee Osteoarthritis in Residents Central Chernozem Region of Russia

Background. Кnee osteoarthritis (OA) is a multifactorial disease in which genetic factors play an important role. The share of the hereditary component in the development of OA, according to various literature sources, ranges from 40 to 65%. Кnee OA is a progressive disease that leads to a decrease in the quality of life and disability. The study aimed to evaluate the role of polymorphic markers of candidate genes rs2820436 and rs2820443 LYPLAL1, rs3771501 TGFA, rs11177 GNL3, rs6976 GLT8D1 in the progression of knee OA in the population of the Central Chernozem Region of Russia. Methods. The study was performed in a case-control design on a sample of 500 patients with knee OA. Case patients with III-IV stages of the disease according to KellgrenLawrence (n = 325), control (individuals who do not have the analyzed sign III-IV stages of the disease) patients with stage II (n = 175). Genotyping of five single nucleotide polymorphisms (SNPs) of candidate genes was performed using the polymerase chain reaction method for DNA synthesis. The study of the associations of the studied polymorphic loci, the calculation of haplotype frequencies and the analysis of their relationship with the progression of knee OA was carried out by the method of logistic regression in the program PLINK v 2.050. Results. Significant associations with the progression of OA of the knee were established for allelic variant A rs2820436 of LYPLAL1 gene according to allelic (OR = 1.48, p = 0.010, pperm = 0.012), additive (OR = 1.58, p = 0.009, pperm = 0.010), dominant (OR = 1.61, p = 0.024, pperm = 0.030) genetic models and A/A genotype of the same polymorphism (OR = 2.53, p = 0.041). The genotypes C/C rs2820436 LYPLAL1 (OR = 0.67, p = 0.043), A/G rs3771501 TGFA (OR = 0.67, p = 0.042) have a protective role in the progression of the disease. It was found that the frequency of the AC haplotype of haploblock rs2820436-rs2820443 in the group of patients with III-IV stages of the disease was significantly higher than in patients with stage II (OR = 1.83, p = 0.002, pperm = 0.002). The identified molecular genetic markers rs2820436 and rs2820443 of LYPLAL1 gene, rs3771501 of TGFA gene are associated both with the risk of developing OA according to previous genome-wide studies and, according to our data, are associated with the progression of knee OA. Conclusions. Genetic risk factors for the development of knee OA of III-IV radiological stages are allelic variant A and genotype A/A rs2820436 of LYPLAL1 gene, haplotype AC of haploblock rs2820436-rs2820443 in the population of the Central Chernozem Region of Russia. Genotypes C/C rs2820436 of LYPLAL1 gene and A/G rs3771501 of TGFA gene have a protective value in the progression of this disease.

Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification

Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

African Gene Flow Reduces Beta-Ionone Anosmia/Hyposmia Prevalence in Admixed Malagasy Populations

While recent advances in genetics make it possible to follow the genetic exchanges between populations and their phenotypic consequences, the impact of the genetic exchanges on the sensory perception of populations has yet to be explored. From this perspective, the present study investigated the consequences of African gene flow on odor perception in a Malagasy population with a predominantly East Asian genetic background. To this end, we combined psychophysical tests with genotype data of 235 individuals who were asked to smell the odorant molecule beta-ionone (βI). Results showed that in this population the ancestry of the OR5A1 gene significantly influences the ability to detect βI. At the individual level, African ancestry significantly protects against specific anosmia/hyposmia due to the higher frequency of the functional gene (OR ratios = 14, CI: 1.8–110, p-value = 0.012). At the population level, African introgression decreased the prevalence of specific anosmia/hyposmia to this odorous compound. Taken together, these findings validate the conjecture that in addition to cultural exchanges, genetic transfer may also influence the sensory perception of the population in contact.

The influence of evolutionary history on human health and disease

Nearly all genetic variants that influence disease risk have human-specific origins; however, the systems they influence have ancient roots that often trace back to evolutionary events long before the origin of humans. Here, we review how advances in our understanding of the genetic architectures of diseases, recent human evolution and deep evolutionary history can help explain how and why humans in modern environments become ill. Human populations exhibit differences in the prevalence of many common and rare genetic diseases. These differences are largely the result of the diverse environmental, cultural, demographic and genetic histories of modern human populations. Synthesizing our growing knowledge of evolutionary history with genetic medicine, while accounting for environmental and social factors, will help to achieve the promise of personalized genomics and realize the potential hidden in an individual's DNA sequence to guide clinical decisions. In short, precision medicine is fundamentally evolutionary medicine, and integration of evolutionary perspectives into the clinic will support the realization of its full potential.

Genetics of Obesity in East Asians

Obesity has become a public health problem worldwide. Compared with Europe, people in Asia tend to suffer from type 2 diabetes with a lower body mass index (BMI). Genome-wide association studies (GWASs) have identified over 750 loci associated with obesity. Although the majority of GWAS results were conducted in individuals of European ancestry, a recent GWAS in individuals of Asian ancestry has made a significant contribution to the identification of obesity susceptibility loci. Indeed, owing to the multifactorial character of obesity with a strong environmental component, the revealed loci may have distinct contributions in different ancestral genetic backgrounds and in different environments as presented through diet and exercise among other factors. Uncovering novel, yet unrevealed genes in non-European ancestries may further contribute to explaining the missing heritability for BMI. In this review, we aimed to summarize recent advances in obesity genetics in individuals of Asian ancestry. We therefore compared proposed mechanisms underlying susceptibility loci for obesity associated with individuals of European and Asian ancestries and discussed whether known genetic variants might explain ethnic differences in obesity risk. We further acknowledged that GWAS implemented in individuals of Asian ancestries have not only validated the potential role of previously specified obesity susceptibility loci but also exposed novel ones, which have been missed in the initial genetic studies in individuals of European ancestries. Thus, multi-ethnic studies have a great potential not only to contribute to a better understanding of the complex etiology of human obesity but also potentially of ethnic differences in the prevalence of obesity, which may ultimately pave new avenues in more targeted and personalized obesity treatments.

Obesity Genomics and Metabolomics: a Nexus of Cardiometabolic Risk

PURPOSE OF REVIEW

Obesity is a significant international public health epidemic with major downstream consequences on morbidity and mortality. While lifestyle factors contribute, there is an evolving understanding of genomic and metabolomic pathways involved with obesity and its relationship with cardiometabolic risk. This review will provide an overview of some of these important findings from both a biologic and clinical perspective.

RECENT FINDINGS

Recent studies have identified polygenic risk scores and metabolomic biomarkers of obesity and related outcomes, which have also highlighted biological pathways, such as the branched-chain amino acid (BCAA) pathway that is dysregulated in this disease. These biomarkers may help in personalizing obesity interventions and for mitigation of future cardiometabolic risk. A multifaceted approach is necessary to impact the growing epidemic of obesity and related diseases. This will likely include incorporating precision medicine approaches with genomic and metabolomic biomarkers to personalize interventions and improve risk prediction.

Importance of Genetic Studies of Cardiometabolic Disease in Diverse Populations

Genome-wide association studies have revolutionized our understanding of the genetic underpinnings of cardiometabolic disease. Yet, the inadequate representation of individuals of diverse ancestral backgrounds in these studies may undercut their ultimate potential for both public health and precision medicine. The goal of this review is to describe the imperativeness of studying the populations who are most affected by cardiometabolic disease, to the aim of better understanding the genetic underpinnings of the disease. We support this premise by describing the current variation in the global burden of cardiometabolic disease and emphasize the importance of building a globally and ancestrally representative genetics evidence base for the identification of population-specific variants, fine-mapping, and polygenic risk score estimation. We discuss the important ethical, legal, and social implications of increasing ancestral diversity in genetic studies of cardiometabolic disease and the challenges that arise from the (1) lack of diversity in current reference populations and available analytic samples and the (2) unequal generation of health-associated genomic data and their prediction accuracies. Despite these challenges, we conclude that additional, unprecedented opportunities lie ahead for public health genomics and the realization of precision medicine, provided that the gap in diversity can be systematically addressed. Achieving this goal will require concerted efforts by social, academic, professional and regulatory stakeholders and communities, and these efforts must be based on principles of equity and social justice.

Evaluating the promise of inclusion of African ancestry populations in genomics

The lack of representation of diverse ancestral backgrounds in genomic research is well-known, and the resultant scientific and ethical limitations are becoming increasingly appreciated. The paucity of data on individuals with African ancestry is especially noteworthy as Africa is the birthplace of modern humans and harbors the greatest genetic diversity. It is expected that greater representation of those with African ancestry in genomic research will bring novel insights into human biology, and lead to improvements in clinical care and improved understanding of health disparities. Now that major efforts have been undertaken to address this failing, is there evidence of these anticipated advances? Here, we evaluate the promise of including diverse individuals in genomic research in the context of recent literature on individuals of African ancestry. In addition, we discuss progress and achievements on related technological challenges and diversity among scientists conducting genomic research.

A phenome-wide association study (PheWAS) in the Population Architecture using Genomics and Epidemiology (PAGE) study reveals potential pleiotropy in African Americans

We performed a hypothesis-generating phenome-wide association study (PheWAS) to identify and characterize cross-phenotype associations, where one SNP is associated with two or more phenotypes, between thousands of genetic variants assayed on the Metabochip and hundreds of phenotypes in 5,897 African Americans as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study. The PAGE I study was a National Human Genome Research Institute-funded collaboration of four study sites accessing diverse epidemiologic studies genotyped on the Metabochip, a custom genotyping chip that has dense coverage of regions in the genome previously associated with cardio-metabolic traits and outcomes in mostly European-descent populations. Here we focus on identifying novel phenome-genome relationships, where SNPs are associated with more than one phenotype. To do this, we performed a PheWAS, testing each SNP on the Metabochip for an association with up to 273 phenotypes in the participating PAGE I study sites. We identified 133 putative pleiotropic variants, defined as SNPs associated at an empirically derived p-value threshold of p<0.01 in two or more PAGE study sites for two or more phenotype classes. We further annotated these PheWAS-identified variants using publicly available functional data and local genetic ancestry. Amongst our novel findings is SPARC rs4958487, associated with increased glucose levels and hypertension. SPARC has been implicated in the pathogenesis of diabetes and is also known to have a potential role in fibrosis, a common consequence of multiple conditions including hypertension. The SPARC example and others highlight the potential that PheWAS approaches have in improving our understanding of complex disease architecture by identifying novel relationships between genetic variants and an array of common human phenotypes.

Genetic Basis of Obesity and Type 2 Diabetes in Africans: Impact on Precision Medicine

PURPOSE OF REVIEW

Recent advances in genomics provide opportunities for novel understanding of the biology of human traits with the goal of improving human health. Here, we review recent obesity and type 2 diabetes (T2D)-related genomic studies in African populations and discuss the implications of limited genomics studies on health disparity and precision medicine.

RECENT FINDINGS

Genome-wide association studies in Africans have yielded genetic discovery that would otherwise not be possible; these include identification of novel loci associated with obesity (SEMA-4D, PRKCA, WARS2), metabolic syndrome (CA-10, CTNNA3), and T2D (AGMO, ZRANB3). ZRANB3 was recently demonstrated to influence beta cell mass and insulin response. Despite these promising results, genomic studies in African populations are still limited and thus genomics tools and approaches such as polygenic risk scores and precision medicine are likely to have limited utility in Africans with the unacceptable possibility of exacerbating prevailing health disparities. African populations provide unique opportunities for increasing our understanding of the genetic basis of cardiometabolic disorders. We highlight the need for more coordinated and sustained efforts to increase the representation of Africans in genomic studies both as participants and scientists.

Neuroimaging-based pain biomarkers: definitions, clinical and research applications, and evaluation frameworks to achieve personalized pain medicine

One of the key ambitions of neuroimaging-based pain biomarker research is to augment patient and clinician reporting of clinically relevant phenomena with neural measures for prediction, prognosis, and detection of pain. Despite years of productive research on the neuroimaging of pain, such applications have seen little advancement. However, recent developments in identifying brain-based biomarkers of pain through advances in technology and multivariate pattern analysis provide some optimism. Here, we (1) define and review the different types of potential neuroimaging-based biomarkers, their clinical and research applications, and their limitations and (2) describe frameworks for evaluation of pain biomarkers used in other fields (eg, genetics, cancer, cardiovascular disease, immune system disorders, and rare diseases) to achieve broad clinical and research utility and minimize the risks of misapplication of this emerging technology. To conclude, we discuss future directions for neuroimaging-based biomarker research to achieve the goal of personalized pain medicine.

The Future of Genomic Studies Must Be Globally Representative: Perspectives from PAGE

The past decade has seen a technological revolution in human genetics that has empowered population-level investigations into genetic associations with phenotypes. Although these discoveries rely on genetic variation across individuals, association studies have overwhelmingly been performed in populations of European descent. In this review, we describe limitations faced by single-population studies and provide an overview of strategies to improve global representation in existing data sets and future human genomics research via diversity-focused, multiethnic studies. We highlight the successes of individual studies and meta-analysis consortia that have provided unique knowledge. Additionally, we outline the approach taken by the Population Architecture Using Genomics and Epidemiology (PAGE) study to develop best practices for performing genetic epidemiology in multiethnic contexts. Finally, we discuss how limiting investigations to single populations impairs findings in the clinical domain for both rare-variant identification and genetic risk prediction.

Genetics of Obesity in Diverse Populations

PURPOSE OF REVIEW

The prevalence of obesity continues to rise, fueling a global public health crisis characterized by dramatic increases in type 2 diabetes, cardiovascular disease, and many cancers. In the USA, several minority populations, who bear much of the obesity burden (47% in African Americans and Hispanic/Latinos, compared to 38% in European descent groups), are particularly at risk of downstream chronic disease. Compounding these disparities, most genome-wide association studies (GWAS)-including those of obesity-have largely been conducted in populations of European or East Asian ancestry. In fact, analysis of the GWAS Catalog found that while the proportion of participants of non-European or non-Asian descent had risen from 4% in 2009 to 19% in 2016, African-ancestry participants are still just 3% of GWAS, Hispanic/Latinos are < 0.5%, and other ancestries are < 0.3% or not represented at all. This review summarizes recent developments in obesity genomics in US minority populations, with the goal of reducing obesity health disparities and improving public health programs and access to precision medicine.

RECENT FINDINGS

GWAS of populations with the highest burden of obesity are essential to narrow candidate variants for functional follow-up, to identify additional ancestry-specific variants that contribute to individual genetic susceptibility, and to advance both public health and precision medicine approaches to obesity. Given the global public health burden posed by obesity and downstream chronic conditions which disproportionately affect non-European populations, GWAS of obesity-related traits in diverse populations is essential to (1) locate causal variants in GWAS-identified regions through fine mapping, (2) identify variants which influence obesity across ancestries through generalization, and (3) discover novel ancestry-specific variants which may be low frequency in European populations but common in other groups. Recent efforts to expand obesity genomic studies to understudied and underserved populations, including AAAGC, PAGE, and HISLA, are working to reduce obesity health disparities, improve public health, and bring the promise of precision medicine to all.

Complex patterns of direct and indirect association between the transcription Factor-7 like 2 gene, body mass index and type 2 diabetes diagnosis in adulthood in the Hispanic Community Health Study/Study of Latinos

Background

Genome-wide association studies have implicated the transcription factor 7-like 2 (TCF7L2) gene in type 2 diabetes risk, and more recently, in decreased body mass index. Given the contrary direction of genetic effects on these two traits, it has been suggested that the observed association with body mass index may reflect either selection bias or a complex underlying biology at TCF7L2.

Methods

Using 9031 Hispanic/Latino adults (21–76 years) with complete weight history and genetic data from the community-based Hispanic Community Health Study/Study of Latinos (HCHS/SOL, Baseline 2008–2011), we estimated the multivariable association between the additive number of type 2 diabetes increasing-alleles at TCF7L2 (rs7903146-T) and body mass index. We then used structural equation models to simultaneously model the genetic association on changes in body mass index across the life course and estimate the odds of type 2 diabetes per TCF7L2 risk allele.

Results

We observed both significant increases in type 2 diabetes prevalence at examination (independent of body mass index) and decreases in mean body mass index and waist circumference across genotypes at rs7903146. We observed a significant multivariable association between the additive number of type 2 diabetes-risk alleles and lower body mass index at examination. In our structured modeling, we observed non-significant inverse direct associations between rs7903146-T and body mass index at ages 21 and 45 years, and a significant positive association between rs7903146-T and type 2 diabetes onset in both middle and late adulthood.

Conclusions

Herein, we replicated the protective effect of rs7930146-T on body mass index at multiple time points in the life course, and observed that these effects were not explained by past type 2 diabetes status in our structured modeling. The robust replication of the negative effects of TCF7L2 on body mass index in multiple samples, including in our diverse Hispanic/Latino community-based sample, supports a growing body of literature on the complex biologic mechanism underlying the functional consequences of TCF7L2 on obesity and type 2 diabetes across the life course.

Electronic supplementary material

The online version of this article (10.1186/s40608-018-0200-x) contains supplementary material, which is available to authorized users.

The genetic underpinnings of variation in ages at menarche and natural menopause among women from the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) Study: A trans-ethnic meta-analysis

Current knowledge of the genetic architecture of key reproductive events across the female life course is largely based on association studies of European descent women. The relevance of known loci for age at menarche (AAM) and age at natural menopause (ANM) in diverse populations remains unclear. We investigated 32 AAM and 14 ANM previously-identified loci and sought to identify novel loci in a trans-ethnic array-wide study of 196,483 SNPs on the MetaboChip (Illumina, Inc.). A total of 45,364 women of diverse ancestries (African, Hispanic/Latina, Asian American and American Indian/Alaskan Native) in the Population Architecture using Genomics and Epidemiology (PAGE) Study were included in cross-sectional analyses of AAM and ANM. Within each study we conducted a linear regression of SNP associations with self-reported or medical record-derived AAM or ANM (in years), adjusting for birth year, population stratification, and center/region, as appropriate, and meta-analyzed results across studies using multiple meta-analytic techniques. For both AAM and ANM, we observed more directionally consistent associations with the previously reported risk alleles than expected by chance (p-values_binomial≤0.01). Eight densely genotyped reproductive loci generalized significantly to at least one non-European population. We identified one trans-ethnic array-wide SNP association with AAM and two significant associations with ANM, which have not been described previously. Additionally, we observed evidence of independent secondary signals at three of six AAM trans-ethnic loci. Our findings support the transferability of reproductive trait loci discovered in European women to women of other race/ethnicities and indicate the presence of additional trans-ethnic associations both at both novel and established loci. These findings suggest the benefit of including diverse populations in future studies of the genetic architecture of female growth and development.

Prioritizing diversity in human genomics research

Recent studies have highlighted the imperatives of including diverse and under-represented individuals in human genomics research and the striking gaps in attaining that inclusion. With its multidecade experience in supporting research and policy efforts in human genomics, the National Human Genome Research Institute is committed to establishing foundational approaches to study the role of genomic variation in health and disease that include diverse populations. Large-scale efforts to understand biology and health have yielded key scientific findings, lessons and recommendations on how to increase diversity in genomic research studies and the genomic research workforce. Increased attention to diversity will increase the accuracy, utility and acceptability of using genomic information for clinical care.

Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI

OBJECTIVE

Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population.

SUBJECTS

Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models.

RESULTS

We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10-7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue.

CONCLUSION

Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.

Insights from population-based analyses of plasma lipids across the allele frequency spectrum

Plasma lipid levels are heritable quantitative risk factors and therapeutic targets for cardiovascular disease. Plasma lipids have been a model for translating genetic observations across the allele frequency spectrum to unique biological and therapeutic insights. Most large studies to date predominately comprised of individuals of European ancestry. This review focuses on contemporary evidence from 2016 to 2017 looking at the effect of genetic variants on plasma lipid levels across the allele frequency spectrum with incrementally larger sample sizes and the contribution of non-European ancestry studies to the genetic etiology of plasma lipid levels. To date, over 250 loci have been associated with plasma lipid levels and several of these loci have additional evidence of association with rare coding variants providing evidence for causal genes at the locus.

Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution

Trans-ethnic meta-analysis of genome-wide association studies (GWAS) across diverse populations can increase power to detect complex trait loci when the underlying causal variants are shared between ancestry groups. However, heterogeneity in allelic effects between GWAS at these loci can occur that is correlated with ancestry. Here, a novel approach is presented to detect SNP association and quantify the extent of heterogeneity in allelic effects that is correlated with ancestry. We employ trans-ethnic meta-regression to model allelic effects as a function of axes of genetic variation, derived from a matrix of mean pairwise allele frequency differences between GWAS, and implemented in the MR-MEGA software. Through detailed simulations, we demonstrate increased power to detect association for MR-MEGA over fixed- and random-effects meta-analysis across a range of scenarios of heterogeneity in allelic effects between ethnic groups. We also demonstrate improved fine-mapping resolution, in loci containing a single causal variant, compared to these meta-analysis approaches and PAINTOR, and equivalent performance to MANTRA at reduced computational cost. Application of MR-MEGA to trans-ethnic GWAS of kidney function in 71,461 individuals indicates stronger signals of association than fixed-effects meta-analysis when heterogeneity in allelic effects is correlated with ancestry. Application of MR-MEGA to fine-mapping four type 2 diabetes susceptibility loci in 22,086 cases and 42,539 controls highlights: (i) strong evidence for heterogeneity in allelic effects that is correlated with ancestry only at the index SNP for the association signal at the CDKAL1 locus; and (ii) 99% credible sets with six or fewer variants for five distinct association signals.

Challenges and Opportunities in Social Epigenomics and Cancer

Social epigenomics is an area of science that evaluates why and how different social factors and processes affect different components of the epigenome. As it happens with most of the new areas in science, social epigenetics being a relatively new area, only limited progress has been made. However, the potential of implicating social epigenomics in improving health and health related policies is tremendous. Epidemiologic studies evaluating social, behavior, family, and environmental factors have helped understand social inequality and develop the area of social epigenomics. Most of the information in social epidemiology has been gathered from genetic studies. Now the time has come that we may apply similar approaches in social epigenomics because technologies of determining methylation, histone, and noncoding RNA profiling are well developed. The focus of this chapter is to understand the role of epigenetic regulation in social experiences at various stages in life due to altered function of genes and affecting health in populations with different races/ethnicity. Here we discuss the current challenges and opportunities in the field.

Population differentiation in allele frequencies of obesity-associated SNPs

BACKGROUND

Obesity is emerging as a global health problem, with more than one-third of the world's adult population being overweight or obese. In this study, we investigated worldwide population differentiation in allele frequencies of obesity-associated SNPs (single nucleotide polymorphisms).

RESULTS

We collected a total of 225 obesity-associated SNPs from a public database. Their population-level allele frequencies were derived based on the genotype data from 1000 Genomes Project (phase 3). We used hypergeometric model to assess whether the effect allele at a given SNP is significantly enriched or depleted in each of the 26 populations surveyed in the 1000 Genomes Project with respect to the overall pooled population. Our results indicate that 195 out of 225 SNPs (86.7%) possess effect alleles significantly enriched or depleted in at least one of the 26 populations. Populations within the same continental group exhibit similar allele enrichment/depletion patterns whereas inter-continental populations show distinct patterns. Among the 225 SNPs, 15 SNPs cluster in the first intron region of the FTO gene, which is a major gene associated with body-mass index (BMI) and fat mass. African populations exhibit much smaller blocks of LD (linkage disequilibrium) among these15 SNPs while European and Asian populations have larger blocks. To estimate the cumulative effect of all variants associated with obesity, we developed the personal composite genetic risk score for obesity. Our results indicate that the East Asian populations have the lowest averages of the composite risk scores, whereas three European populations have the highest averages. In addition, the population-level average of composite genetic risk scores is significantly correlated (R2 = 0.35, P = 0.0060) with obesity prevalence.

CONCLUSIONS

We have detected substantial population differentiation in allele frequencies of obesity-associated SNPs. The results will help elucidate the genetic basis which may contribute to population disparities in obesity prevalence.

Convergence between biological, behavioural and genetic determinants of obesity

Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.