An approach to identify gene-environment interactions and reveal new biological insight in complex traits.

There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the Gene-Lifestyle Interactions Working Group within the Cohorts for Heart and Aging Research in Genetic Epidemiology Consortium has been spearheading efforts to investigate G × E in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identify and confirm 5 loci (6 independent signals) interacted with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrate that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated heritability is significant (P < 0.02) for low-density lipoprotein cholesterol and triglycerides in Cross-Population data. Our study improves the understanding of the genetic architecture and environmental contributions to complex traits.

Untargeted metabolomic profiling reveals molecular signatures associated with type 2 diabetes in Nigerians.

BACKGROUND: Type 2 diabetes (T2D) has reached epidemic proportions globally, including in Africa. However, molecular studies to understand the pathophysiology of T2D remain scarce outside Europe and North America. The aims of this study are to use an untargeted metabolomics approach to identify: (a) metabolites that are differentially expressed between individuals with and without T2D and (b) a metabolic signature associated with T2D in a population of Sub-Saharan Africa (SSA). METHODS: A total of 580 adult Nigerians from the Africa America Diabetes Mellitus (AADM) study were studied. The discovery study included 310 individuals (210 without T2D, 100 with T2D). Metabolites in plasma were assessed by reverse phase, ultra-performance liquid chromatography and mass spectrometry (RP)/UPLC-MS/MS methods on the Metabolon Platform. Welch's two-sample t-test was used to identify differentially expressed metabolites (DEMs), followed by the construction of a biomarker panel using a random forest (RF) algorithm. The biomarker panel was evaluated in a replication sample of 270 individuals (110 without T2D and 160 with T2D) from the same study. RESULTS: Untargeted metabolomic analyses revealed 280 DEMs between individuals with and without T2D. The DEMs predominantly belonged to the lipid (51%, 142/280), amino acid (21%, 59/280), xenobiotics (13%, 35/280), carbohydrate (4%, 10/280) and nucleotide (4%, 10/280) super pathways. At the sub-pathway level, glycolysis, free fatty acid, bile metabolism, and branched chain amino acid catabolism were altered in T2D individuals. A 10-metabolite biomarker panel including glucose, gluconate, mannose, mannonate, 1,5-anhydroglucitol, fructose, fructosyl-lysine, 1-carboxylethylleucine, metformin, and methyl-glucopyranoside predicted T2D with an area under the curve (AUC) of 0.924 (95% CI: 0.845-0.966) and a predicted accuracy of 89.3%. The panel was validated with a similar AUC (0.935, 95% CI 0.906-0.958) in the replication cohort. The 10 metabolites in the biomarker panel correlated significantly with several T2D-related glycemic indices, including Hba1C, insulin resistance (HOMA-IR), and diabetes duration. CONCLUSIONS: We demonstrate that metabolomic dysregulation associated with T2D in Nigerians affects multiple processes, including glycolysis, free fatty acid and bile metabolism, and branched chain amino acid catabolism. Our study replicated previous findings in other populations and identified a metabolic signature that could be used as a biomarker panel of T2D risk and glycemic control thus enhancing our knowledge of molecular pathophysiologic changes in T2D. The metabolomics dataset generated in this study represents an invaluable addition to publicly available multi-omics data on understudied African ancestry populations.

Semiparametric partial linear modeling of risk factors for ear infections: the Early Childhood Longitudinal Study.

The Early Childhood Longitudinal Study-Kindergarten Class of 2010-2011 (ECLS-K:2011) ascertained timing of ear infections within age specified intervals and parent's/caregiver's report of medically diagnosed hearing loss. In this nationally representative, school-based sample of children followed from kindergarten entry through fifth grade, academic performance in reading, mathematics, and science was assessed longitudinally. Prior investigations of this ECLS-K:2011 cohort showed that age has a non-linear, monotonically increasing functional relationship with academic performance. Because of this knowledge, a semiparametric partial linear model is proposed, in which the effect of age is modeled by an unknown monotonically increasing function along with other regression parameters. The parameters are estimated by a semiparametric maximum likelihood estimator. A test of a constant effect of age is also proposed. Simulation studies are conducted to evaluate the performance of the proposed method, as compared with the commonly used linear model; the former outperforms the latter based on several criteria. We then analyzed ECLS-K:2011 data to compare results of the partial linear parametric model estimation with that of classical linear regression models.

Genome, HLA and polygenic risk score analyses for prevalent and persistent cervical human papillomavirus (HPV) infections.

Genetic variants that underlie susceptibility to cervical high-risk human papillomavirus (hrHPV) infections are largely unknown. We conducted discovery genome-wide association studies (GWAS), replication, meta-analysis and colocalization, generated polygenic risk scores (PRS) and examined the association of classical HLA alleles and cervical hrHPV infections in a cohort of over 10,000 women. We identified genome-wide significant variants for prevalent hrHPV around LDB2 and for persistent hrHPV near TPTE2, SMAD2, and CDH12, which code for proteins that are significantly expressed in the human endocervix. Genetic variants associated with persistent hrHPV are in genes enriched for the antigen processing and presentation gene set. HLA-DRB1*13:02, HLA-DQB1*05:02 and HLA-DRB1*03:01 were associated with increased risk, and HLA-DRB1*15:03 was associated with decreased risk of persistent hrHPV. The analyses of peptide binding predictions showed that HLA-DRB1 alleles that were positively associated with persistent hrHPV showed weaker binding with peptides derived from hrHPV proteins and vice versa. The PRS for persistent hrHPV with the best model fit, had a P-value threshold (PT) of 0.001 and a p-value of 0.06 (-log10(0.06) = 1.22). The findings of this study expand our understanding of genetic risk factors for hrHPV infection and persistence and highlight the roles of MHC class II molecules in hrHPV infection.

Sickle cell allele HBB-rs334(T) is associated with decreased risk of childhood Burkitt lymphoma in East Africa.

Burkitt lymphoma (BL) is an aggressive B-cell lymphoma that significantly contributes to childhood cancer burden in sub-Saharan Africa. Plasmodium falciparum, which causes malaria, is geographically associated with BL, but the evidence remains insufficient for causal inference. Inference could be strengthened by demonstrating that mendelian genes known to protect against malaria-such as the sickle cell trait variant, HBB-rs334(T)-also protect against BL. We investigated this hypothesis among 800 BL cases and 3845 controls in four East African countries using genome-scan data to detect polymorphisms in 22 genes known to affect malaria risk. We fit generalized linear mixed models to estimate odds ratios (OR) and 95% confidence intervals (95% CI), controlling for age, sex, country, and ancestry. The ORs of the loci with BL and P. falciparum infection among controls were correlated (Spearman's ρ = 0.37, p = .039). HBB-rs334(T) was associated with lower P. falciparum infection risk among controls (OR = 0.752, 95% CI 0.628-0.9; p = .00189) and BL risk (OR = 0.687, 95% CI 0.533-0.885; p = .0037). ABO-rs8176703(T) was associated with decreased risk of BL (OR = 0.591, 95% CI 0.379-0.992; p = .00271), but not of P. falciparum infection. Our results increase support for the etiological correlation between P. falciparum and BL risk.

Mendelian randomization analyses suggest a causal role for circulating GIP and IL-1RA levels in homeostatic model assessment-derived measures of ß-cell function and insulin sensitivity in Africans without type 2 diabetes.

BACKGROUND: In vitro and in vivo studies have shown that certain cytokines and hormones may play a role in the development and progression of type 2 diabetes (T2D). However, studies on their role in T2D in humans are scarce. We evaluated associations between 11 circulating cytokines and hormones with T2D among a population of sub-Saharan Africans and tested for causal relationships using Mendelian randomization (MR) analyses. METHODS: We used logistic regression analysis adjusted for age, sex, body mass index, and recruitment country to regress levels of 11 cytokines and hormones (adipsin, leptin, visfatin, PAI-1, GIP, GLP-1, ghrelin, resistin, IL-6, IL-10, IL-1RA) on T2D among Ghanaians, Nigerians, and Kenyans from the Africa America Diabetes Mellitus study including 2276 individuals with T2D and 2790 non-T2D individuals. Similar linear regression models were fitted with homeostatic modelling assessments of insulin sensitivity (HOMA-S) and ß-cell function (HOMA-B) as dependent variables among non-T2D individuals (n = 2790). We used 35 genetic variants previously associated with at least one of these 11 cytokines and hormones among non-T2D individuals as instrumental variables in univariable and multivariable MR analyses. Statistical significance was set at 0.0045 (0.05/11 cytokines and hormones). RESULTS: Circulating GIP and IL-1RA levels were associated with T2D. Nine of the 11 cytokines and hormones (exceptions GLP-1 and IL-6) were associated with HOMA-S, HOMA-B, or both among non-T2D individuals. Two-stage least squares MR analysis provided evidence for a causal effect of GIP and IL-RA on HOMA-S and HOMA-B in multivariable analyses (GIP ~ HOMA-S ß = - 0.67, P-value = 1.88 × 10-6 and HOMA-B ß = 0.59, P-value = 1.88 × 10-5; IL-1RA ~ HOMA-S ß = - 0.51, P-value = 8.49 × 10-5 and HOMA-B ß = 0.48, P-value = 5.71 × 10-4). IL-RA was partly mediated via BMI (30-34%), but GIP was not. Inverse variance weighted MR analysis provided evidence for a causal effect of adipsin on T2D (multivariable OR = 1.83, P-value = 9.79 × 10-6), though these associations were not consistent in all sensitivity analyses. CONCLUSIONS: The findings of this comprehensive MR analysis indicate that circulating GIP and IL-1RA levels are causal for reduced insulin sensitivity and increased ß-cell function. GIP's effect being independent of BMI suggests that circulating levels of GIP could be a promising early biomarker for T2D risk. Our MR analyses do not provide conclusive evidence for a causal role of other circulating cytokines in T2D among sub-Saharan Africans.

Unappreciated subcontinental admixture in Europeans and European Americans and implications for genetic epidemiology studies.

European-ancestry populations are recognized as stratified but not as admixed, implying that residual confounding by locus-specific ancestry can affect studies of association, polygenic adaptation, and polygenic risk scores. We integrate individual-level genome-wide data from ~19,000 European-ancestry individuals across 79 European populations and five European American cohorts. We generate a new reference panel that captures ancestral diversity missed by both the 1000 Genomes and Human Genome Diversity Projects. Both Europeans and European Americans are admixed at the subcontinental level, with admixture dates differing among subgroups of European Americans. After adjustment for both genome-wide and locus-specific ancestry, associations between a highly differentiated variant in LCT (rs4988235) and height or LDL-cholesterol were confirmed to be false positives whereas the association between LCT and body mass index was genuine. We provide formal evidence of subcontinental admixture in individuals with European ancestry, which, if not properly accounted for, can produce spurious results in genetic epidemiology studies.

A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits.

There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the CHARGE Gene-Lifestyle Interactions Working Group has been spearheading efforts to investigate G×E in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identified and confirmed 5 loci (6 independent signals) interacting with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrated that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated contribution ranges from 1.76% to 14.05% of SNP heritability of serum lipids in Cross-Population data. Our study improves the understanding of the genetic architecture and environmental contributions to complex traits.

Universal genome-wide association studies: Powerful joint ancestry and association testing.

The vast majority of human populations and individuals have mixed ancestry. Consequently, adjustment for locus-specific ancestry is essential for genetic association studies. To empower association studies for all populations, it is necessary to integrate effects of locus-specific ancestry and genotype. We developed a joint test of ancestry and association that can be performed with summary statistics, is independent of study design, can take advantage of locus-specific ancestry effects to boost power in association testing, and can utilize association effects to fine map admixture peaks. We illustrate the test using the association between serum triglycerides and LPL. By combining data from African Americans, European Americans, and West Africans, we identify three conditionally independent variants with varying amounts of ancestrally differentiated allele frequencies. Using out-of-sample data, we demonstrate improved prediction achievable by accounting for multiple causal variants and locus-specific ancestry effects at a single locus.

Genes, environment, and African ancestry in cardiometabolic disorders.

The past two decades have been characterized by a substantial global increase in cardiometabolic diseases, but the prevalence and incidence of these diseases and related traits differ across populations. African ancestry populations are among the most affected yet least included in research. Populations of African descent manifest significant genetic and environmental diversity and this under-representation is a missed opportunity for discovery and could exacerbate existing health disparities and curtail equitable implementation of precision medicine. Here, we discuss cardiometabolic diseases and traits in the context of African descent populations, including both genetic and environmental contributors and emphasizing novel discoveries. We also review new initiatives to include more individuals of African descent in genomics to address current gaps in the field.

Ancestral and environmental patterns in the association between triglycerides and other cardiometabolic risk factors.

BACKGROUND: West Africans and African Americans with substantial (∼80%) West African ancestry are characterized by low levels of triglycerides (TG) compared to East Africans and Europeans. The impact of these varying TG levels on other cardiometabolic risk factors is unclear. We compared the strength of association between TG with hypertension, blood pressure, BMI, waist circumference, type 2 diabetes (T2D), and fasting glucose across West African (WA), East African (EA), and European (EU) ancestry populations residing in three vastly different environmental settings: sub-Saharan Africa, United States, and Europe. METHODS: We analysed data from four cross-sectional studies that included WA in sub-Saharan Africa (n = 7201), the U.S. (n = 4390), and Europe (n = 6436), EA in sub-Saharan Africa (n = 781), and EU in the U.S. (n = 8670) and Europe (n = 4541). Linear regression analyses were used to test the association between TG and cardiometabolic risk factors. FINDINGS: Higher adjusted regression coefficients were observed in EU compared with WA ancestry for TG on hypertension (EU ß [95% CI]: 0.179 [0.156, 0.203], WA ß [95% CI]: 0.102 [0.086, 0.118]), BMI (EU ß [95% CI]: 0.028 [0.027, 0.030], WA ß [95% CI]: 0.015 [0.014, 0.016]), and waist circumference (EU ß [95% CI]: 0.013 [0.013, 0.014], WA ß [95% CI]: 0.009 [0.008, 0.009) (all ancestry × trait interaction P-values <0.05), irrespective of environmental differences within ancestry groups. Less consistency was observed among EA. Associations of TG with T2D did not follow ancestry patterns, with substantial variation observed between environments. INTERPRETATION: TG may not be an equally strong associated with other established cardiometabolic risk factors in West and East Africans in contrast to European ancestry populations. The value of TG for identifying individuals at high risk for developing metabolic disorders needs to be re-evaluated for African ancestry populations. FUNDING: National Institutes of Health, European Commission, Dutch Heart Foundation, Netherlands Organization for Health Research and Development, Centers for Disease Control and Prevention.

2022 ASHG presidential address-One human race: Billions of genomes.

This article is based on the address given by the author at the 2022 meeting of The American Society of Human Genetics (ASHG) in Los Angeles, California. The video of the original address can be found at the ASHG website.

Multi-omics insights into the biological mechanisms underlying statistical gene-by-lifestyle interactions with smoking and alcohol consumption.

Though both genetic and lifestyle factors are known to influence cardiometabolic outcomes, less attention has been given to whether lifestyle exposures can alter the association between a genetic variant and these outcomes. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium's Gene-Lifestyle Interactions Working Group has recently published investigations of genome-wide gene-environment interactions in large multi-ancestry meta-analyses with a focus on cigarette smoking and alcohol consumption as lifestyle factors and blood pressure and serum lipids as outcomes. Further description of the biological mechanisms underlying these statistical interactions would represent a significant advance in our understanding of gene-environment interactions, yet accessing and harmonizing individual-level genetic and 'omics data is challenging. Here, we demonstrate the coordinated use of summary-level data for gene-lifestyle interaction associations on up to 600,000 individuals, differential methylation data, and gene expression data for the characterization and prioritization of loci for future follow-up analyses. Using this approach, we identify 48 genes for which there are multiple sources of functional support for the identified gene-lifestyle interaction. We also identified five genes for which differential expression was observed by the same lifestyle factor for which a gene-lifestyle interaction was found. For instance, in gene-lifestyle interaction analysis, the T allele of rs6490056 (ALDH2) was associated with higher systolic blood pressure, and a larger effect was observed in smokers compared to non-smokers. In gene expression studies, this allele is associated with decreased expression of ALDH2, which is part of a major oxidative pathway. Other results show increased expression of ALDH2 among smokers. Oxidative stress is known to contribute to worsening blood pressure. Together these data support the hypothesis that rs6490056 reduces expression of ALDH2, which raises oxidative stress, leading to an increase in blood pressure, with a stronger effect among smokers, in whom the burden of oxidative stress is greater. Other genes for which the aggregation of data types suggest a potential mechanism include: GCNT4×current smoking (HDL), PTPRZ1×ever-smoking (HDL), SYN2×current smoking (pulse pressure), and TMEM116×ever-smoking (mean arterial pressure). This work demonstrates the utility of careful curation of summary-level data from a variety of sources to prioritize gene-lifestyle interaction loci for follow-up analyses.

Mendelian randomization study reveals a causal relationship between adiponectin and LDL cholesterol in Africans.

Adiponectin has been associated with cardiometabolic traits in observational studies across populations, yet it is unclear if these associations are causal. We performed Mendelian randomization (MR) analysis to assess the relationship between adiponectin and cardiometabolic traits in sub-Saharan Africans. We constructed a polygenic risk score (PRS) for adiponectin levels across 3354 unrelated sub-Saharan Africans. The PRS was used as the instrumental variable in two-stage least-squares MR analysis to assess its association with insulin resistance, HDL, LDL, total cholesterol, triglycerides, blood pressure, Type 2 Diabetes (T2D), and hypertension. The adiponectin PRS was causally related with LDL (ß = 0.55, 95%CI 0.07-1.04, P-value = 0.024) but not the other traits. This association was observed in both overweight/obese and normal weight individuals, but only reached statistical significance among overweight/obese individuals (ß = 0.55, 95%CI 0.01-1.08, P-value = 0.045). In normal weight individuals, the adiponectin PRS was associated with T2D (OR = 0.13, 95%CI 0.02-0.73, P-value = 0.021), and in men with HDL (ß = 1.03, 95%CI 0.14-1.92, P-value = 0.023). The findings of this first MR study in sub-Saharan Africans support a causal relationship of adiponectin with LDL, with T2D in normal weight individuals only, and with HDL in men only. These observations add to the small but growing literature on adiponectin MR studies.

An epigenome-wide association study of insulin resistance in African Americans.

BACKGROUND: African Americans have a high risk for type 2 diabetes (T2D) and insulin resistance. Studies among other population groups have identified DNA methylation loci associated with insulin resistance, but data in African Americans are lacking. Using DNA methylation profiles of blood samples obtained from the Illumina Infinium® HumanMethylation450 BeadChip, we performed an epigenome-wide association study to identify DNA methylation loci associated with insulin resistance among 136 non-diabetic, unrelated African American men (mean age 41.6 years) from the Howard University Family Study. RESULTS: We identified three differentially methylated positions (DMPs) for homeostatic model assessment of insulin resistance (HOMA-IR) at 5% FDR. One DMP (cg14013695, HOXA5) is a known locus among Mexican Americans, while the other two DMPs are novel-cg00456326 (OSR1; beta = 0.027) and cg20259981 (ST18; beta = 0.010). Although the cg00456326 DMP is novel, the OSR1 gene has previously been found associated with both insulin resistance and T2D in Europeans. The genes HOXA5 and ST18 have been implicated in biological processes relevant to insulin resistance. Differential methylation at the significant HOXA5 and OSR1 DMPs is associated with differences in gene expression in the iMETHYL database. Analysis of differentially methylated regions (DMRs) did not identify any epigenome-wide DMRs for HOMA-IR. We tested transferability of HOMA-IR associated DMPs from five previous EWAS in Mexican Americans, Indian Asians, Europeans, and European ancestry Americans. Out of the 730 previously reported HOMA-IR DMPs, 47 (6.4%) were associated with HOMA-IR in this cohort of African Americans. CONCLUSIONS: The findings from our study suggest substantial differences in DNA methylation patterns associated with insulin resistance across populations. Two of the DMPs we identified in African Americans have not been reported in other populations, and we found low transferability of HOMA-IR DMPs reported in other populations in African Americans. More work in African-ancestry populations is needed to confirm our findings as well as functional analyses to understand how such DNA methylation alterations contribute to T2D pathology.

Additive genetic effect of GCKR, G6PC2, and SLC30A8 variants on fasting glucose levels and risk of type 2 diabetes.

Impaired glucose tolerance is a major risk factor for type 2 diabetes (T2D) and several cardiometabolic disorders. To identify genetic loci underlying fasting glucose levels, we conducted an analysis of 9,232 individuals of European ancestry who at enrollment were either nondiabetic or had untreated type 2 diabetes. Multivariable linear mixed models were used to test for associations between fasting glucose and 7.9 million SNPs, with adjustment for age, body mass index (BMI), sex, significant principal components of the genotypes, and cryptic relatedness. Three previously discovered loci were genome-wide significant, with the lead SNPs being rs1260326, a missense variant in GCKR (p = 1.06×10-8); rs560887, an intronic variant in G6PC2 (p = 3.39×10-11); and rs13266634, a missense variant in SLC30A8 (p = 4.28×10-10). Fine mapping, genome-wide conditional analysis, and functional annotation indicated that the three loci were independently associated with fasting glucose. Each copy of an alternate allele at any of these three SNPs was associated with a reduction of 0.012 mmol/L in fasting glucose levels (p = 8.0×10-28), and this association was replicated in trans-ethnic analysis of 14,303 individuals (p = 2.2×10-16). The three SNPs were jointly associated with significantly reduced T2D risk, with an odds ratio (95% CI) of 0.93 (0.88, 0.98) per protective allele. Our findings implicate additive effects across pathophysiological pathways involved in type 2 diabetes, including glycolysis, gluconeogenesis, and insulin secretion. Since none of the individuals homozygous for the alternate alleles at all three loci has T2D, it might be possible to use a genetic predictor of fasting glucose levels to identify individuals at low vs. high risk of developing type 2 diabetes.

Genetic differentiation in East African ethnicities and its relationship with endurance running success.

Since the 1960s, East African athletes, mainly from Kenya and Ethiopia, have dominated long-distance running events in both the male and female categories. Further demographic studies have shown that two ethnic groups are overrepresented among elite endurance runners in each of these countries: the Kalenjin, from Kenya, and the Oromo, from Ethiopia, raising the possibility that this dominance results from genetic or/and cultural factors. However, looking at the life history of these athletes or at loci previously associated with endurance athletic performance, no compelling explanation has emerged. Here, we used a population approach to identify peaks of genetic differentiation for these two ethnicities and compared the list of genes close to these regions with a list, manually curated by us, of genes that have been associated with traits possibly relevant to endurance running in GWAS studies, and found a significant enrichment in both populations (Kalenjin, P = 0.048, and Oromo, P = 1.6x10-5). Those traits are mainly related to anthropometry, circulatory and respiratory systems, energy metabolism, and calcium homeostasis. Our results reinforce the notion that endurance running is a systemic activity with a complex genetic architecture, and indicate new candidate genes for future studies. Finally, we argue that a deterministic relationship between genetics and sports must be avoided, as it is both scientifically incorrect and prone to reinforcing population (racial) stereotyping.

Gene-lifestyle interactions in the genomics of human complex traits.

The role and biological significance of gene-environment interactions in human traits and diseases remain poorly understood. To address these questions, the CHARGE Gene-Lifestyle Interactions Working Group conducted series of genome-wide interaction studies (GWIS) involving up to 610,475 individuals across four ancestries for three lipids and four blood pressure traits, while accounting for interaction effects with drinking and smoking exposures. Here we used GWIS summary statistics from these studies to decipher potential differences in genetic associations and G×E interactions across phenotype-exposure-ancestry combinations, and to derive insights on the potential mechanistic underlying G×E through in-silico functional analyses. Our analyses show first that interaction effects likely contribute to the commonly reported ancestry-specific genetic effect in complex traits, and second, that some phenotype-exposures pairs are more likely to benefit from a greater detection power when accounting for interactions. It also highlighted modest correlation between marginal and interaction effects, providing material for future methodological development and biological discussions. We also estimated contributions to phenotypic variance, including in particular the genetic heritability conditional on the exposure, and heritability partitioned across a range of functional annotations and cell types. In these analyses, we found multiple instances of potential heterogeneity of functional partitions between exposed and unexposed individuals, providing new evidence for likely exposure-specific genetic pathways. Finally, along this work, we identified potential biases in methods used to jointly meta-analyze genetic and interaction effects. We performed simulations to characterize these limitations and to provide the community with guidelines for future G×E studies.

ACE2 pathway regulates thermogenesis and energy metabolism.

Identification of key regulators of energy homeostasis holds important therapeutic promise for metabolic disorders, such as obesity and diabetes. ACE2 cleaves angiotensin II (Ang II) to generate Ang-(1-7) which acts mainly through the Mas1 receptor. Here, we identify ACE2 pathway as a critical regulator in the maintenance of thermogenesis and energy expenditure. We found that ACE2 is highly expressed in brown adipose tissue (BAT) and that cold stimulation increases ACE2 and Ang-(1-7) levels in BAT and serum. Ace2 knockout mice (Ace2-/y) and Mas1 knockout mice (Mas1-/-) displayed impaired thermogenesis. Mice transplanted with brown adipose tissue from Mas1-/- display metabolic abnormalities consistent with those seen in the Ace2 and Mas1 knockout mice. In contrast, impaired thermogenesis of Leprdb/db obese diabetic mice and high-fat diet-induced obese mice were ameliorated by overexpression of Ace2 or continuous infusion of Ang-(1-7). Activation of ACE2 pathway was associated with improvement of metabolic parameters, including blood glucose, lipids, and energy expenditure in multiple animal models. Consistently, ACE2 pathway remarkably enhanced the browning of white adipose tissue. Mechanistically, we showed that ACE2 pathway activated Akt/FoxO1 and PKA pathway, leading to induction of UCP1 and activation of mitochondrial function. Our data propose that adaptive thermogenesis requires regulation of ACE2 pathway and highlight novel potential therapeutic targets for the treatment of metabolic disorders.