Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

Rare Variant Analysis of Obesity-Associated Genes in Young Adults With Severe Obesity From a Consanguineous Population of Pakistan

Recent advances in genetic analysis have significantly helped in progressively attenuating the heritability gap of obesity and have brought into focus monogenic variants that disrupt the melanocortin signaling. In a previous study, next-generation sequencing revealed a monogenic etiology in ∼50% of the children with severe obesity from a consanguineous population in Pakistan. Here we assess rare variants in obesity-causing genes in young adults with severe obesity from the same region. Genomic DNA from 126 randomly selected young adult obese subjects (BMI 37.2 ± 0.3 kg/m2; age 18.4 ± 0.3 years) was screened by conventional or augmented whole-exome analysis for point mutations and copy number variants (CNVs). Leptin, insulin, and cortisol levels were measured by ELISA. We identified 13 subjects carrying 13 different pathogenic or likely pathogenic variants in LEPR, PCSK1, MC4R, NTRK2, POMC, SH2B1, and SIM1. We also identified for the first time in the human, two homozygous stop-gain mutations in ASNSD1 and IFI16 genes. Inactivation of these genes in mouse models has been shown to result in obesity. Additionally, we describe nine homozygous mutations (seven missense, one stop-gain, and one stop-loss) and four copy-loss CNVs in genes or genomic regions previously linked to obesity-associated traits by genome-wide association studies. Unexpectedly, in contrast to obese children, pathogenic mutations in LEP and LEPR were either absent or rare in this cohort of young adults. High morbidity and mortality risks and social disadvantage of children with LEP or LEPR deficiency may in part explain this difference between the two cohorts.

Evidence That Substantia Nigra Pars Compacta Dopaminergic Neurons Are Selectively Vulnerable to Oxidative Stress Because They Are Highly Metabolically Active

There are 400–500 thousand dopaminergic cells within each side of the human substantia nigra pars compacta (SNpc) making them a minuscule portion of total brain mass. These tiny clusters of cells have an outsized impact on motor output and behavior as seen in disorders such as Parkinson’s disease (PD). SNpc dopaminergic neurons are more vulnerable to oxidative stress compared to other brain cell types, but the reasons for this are not precisely known. Here we provide evidence to support the hypothesis that this selective vulnerability is because SNpc neurons sustain high metabolic rates compared to other neurons. A higher baseline requirement for ATP production may lead to a selective vulnerability to impairments in oxidative phosphorylation (OXPHOS) or genetic insults that impair Complex I of the electron transport chain. We suggest that the energy demands of the unique morphological and electrophysiological properties of SNpc neurons may be one reason these cells produce more ATP than other cells. We further provide evidence to support the hypothesis that transcription factors (TFs) required to drive induction, differentiation, and maintenance of midbrain dopaminergic neural progenitor cells which give rise to terminally differentiated SNpc neurons are uniquely involved in both developmental patterning and metabolism, a dual function unlike other TFs that program neurons in other brain regions. The use of these TFs during induction and differentiation may program ventral midbrain progenitor cells metabolically to higher ATP levels, allowing for the development of those specialized cell processes seen in terminally differentiated cells. This paper provides a cellular and developmental framework for understanding the selective vulnerability of SNpc dopaminergic cells to oxidative stress.

Polygenic risk for mental disorder reveals distinct association profiles across social behaviour in the general population

Many mental health conditions present a spectrum of social difficulties that overlaps with social behaviour in the general population including shared but little characterised genetic links. Here, we systematically investigate heterogeneity in shared genetic liabilities with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), bipolar disorder (BP), major depression (MD) and schizophrenia across a spectrum of different social symptoms. Longitudinally assessed low-prosociality and peer-problem scores in two UK population-based cohorts (4-17 years; parent- and teacher-reports; Avon Longitudinal Study of Parents and Children(ALSPAC): N ≤ 6,174; Twins Early Development Study(TEDS): N ≤ 7,112) were regressed on polygenic risk scores for disorder, as informed by genome-wide summary statistics from large consortia, using negative binomial regression models. Across ALSPAC and TEDS, we replicated univariate polygenic associations between social behaviour and risk for ADHD, MD and schizophrenia. Modelling variation in univariate genetic effects jointly using random-effect meta-regression revealed evidence for polygenic links between social behaviour and ADHD, ASD, MD, and schizophrenia risk, but not BP. Differences in age, reporter and social trait captured 45-88% in univariate effect variation. Cross-disorder adjusted analyses demonstrated that age-related heterogeneity in univariate effects is shared across mental health conditions, while reporter- and social trait-specific heterogeneity captures disorder-specific profiles. In particular, ADHD, MD, and ASD polygenic risk were more strongly linked to peer problems than low prosociality, while schizophrenia was associated with low prosociality only. The identified association profiles suggest differences in the social genetic architecture across mental disorders when investigating polygenic overlap with population-based social symptoms spanning 13 years of child and adolescent development.

Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans

Background

Imputation from genotyping array to whole-genome sequence variants using resequencing of representative reference populations enhances our ability to map genetic factors affecting complex phenotypes in livestock species. The accumulation of knowledge about gene function in human and laboratory animals can provide substantial advantage for genomic research in livestock species.

Results

In this study, 201,388 pigs from three commercial Danish breeds genotyped with low to medium (8.5k to 70k) SNP arrays were imputed to whole genome sequence variants using a two-step approach. Both imputation steps achieved high accuracies, and in total this yielded 26,447,434 markers on 18 autosomes. The average estimated imputation accuracy of markers with minor allele frequency ≥ 0.05 was 0.94. To overcome the memory consumption of running genome-wide association study (GWAS) for each breed, we performed within-breed subpopulation GWAS then within-breed meta-analysis for average daily weight gain (ADG), followed by a multi-breed meta-analysis of GWAS summary statistics. We identified 15 quantitative trait loci (QTL). Our post-GWAS analysis strategy to prioritize of candidate genes including information like gene ontology, mammalian phenotype database, differential expression gene analysis of high and low feed efficiency pig and human GWAS catalog for height, obesity, and body mass index, we proposed MRAP2, LEPROT, PMAIP1, ENSSSCG00000036234, BMP2, ELFN1, LIG4 and FAM155A as the candidate genes with biological support for ADG in pigs.

Conclusion

Our post-GWAS analysis strategy helped to identify candidate genes not just by distance to the lead SNP but also by multiple sources of biological evidence. Besides, the identified QTL overlap with genes which are known for their association with human growth-related traits. The GWAS with this large data set showed the power to map the genetic factors associated with ADG in pigs and have added to our understanding of the genetics of growth across mammalian species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08373-3.

Ultra Low-Coverage Whole-Genome Sequencing as an Alternative to Genotyping Arrays in Genome-Wide Association Studies

An array-based genotyping approach has been the standard practice for genome-wide association studies (GWASs); however, as sequencing costs plummet over the past years, ultra low-coverage whole-genome sequencing (ulcWGS <0.5× coverage) has emerged as a promising alternative that provides superior genomic coverage with substantial reduction of genotyping cost. To evaluate the potential utility of ulcWGS, we performed a whole-genome sequencing (WGS) of 72 European individuals to a target coverage of 0.4× and compared its performance with the widely used Infinium Global Screening Multi-Disease Array (GSA-MD). We showed that the number of variants captured by ulcWGS is comparable with imputed GSA-MD platform, particularly for low-frequency (95.5%) and common variants (99.9%), with high imputation R² accuracy (mean 0.93 for SNPs and 0.86 for indels). Using deep-coverage 30× WGS as the “truth” genotypes, we found that ulcWGS has higher overall nonreference genotype concordance compared with imputed GSA-MD for both SNPs (0.90 vs. 0.88) and indels (0.86 vs. 0.83). In addition, ulcWGS proved to be as sensitive as the genotyping-based method in sex imputation and ancestry prediction producing similar principal component (PC) scores. Our findings provide important evidence that the cost efficient ulcWGS of <0.5× generates high genotype accuracy, outperforming the standard genotyping arrays, making it an attractive alternative to the array-based method in next-generation GWAS design.

Genetic Connections and Convergent Evolution of Tropical Indigenous Peoples in Asia

Tropical indigenous peoples in Asia (TIA) attract much attention for their unique appearance, whereas their genetic history and adaptive evolution remain mysteries. We conducted a comprehensive study to characterize the genetic distinction and connection of broad geographical TIAs. Despite the diverse genetic makeup and large interarea genetic differentiation between the TIA groups, we identified a basal Asian ancestry (bASN) specifically shared by these populations. The bASN ancestry was relatively enriched in ancient Asian human genomes dated as early as ∼50,000 years before the present and diminished in more recent history. Notably, the bASN ancestry is unlikely to be derived from archaic hominins. Instead, we suggest it may be better modeled as a survived lineage of the initial peopling of Asia. Shared adaptations inherited from the ancient Asian ancestry were detected among the TIA groups (e.g., LIMS1 for hair morphology, and COL24A1 for bone formation), and they are enriched in neurological functions either at an identical locus (e.g., NKAIN3), or different loci in an identical gene (e.g., TENM4). The bASN ancestry could also have formed the substrate of the genetic architecture of the dark pigmentation observed in the TIA peoples. We hypothesize that phenotypic convergence of the dark pigmentation in TIAs could have resulted from parallel (e.g., DDB1/DAK) or genetic convergence driven by admixture (e.g., MTHFD1 and RAD18), new mutations (e.g., STK11), or notably purifying selection (e.g., MC1R). Our results provide new insights into the initial peopling of Asia and an advanced understanding of the phenotypic convergence of the TIA peoples.

SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): Joint Mapping of Common and Rare Variation Affecting Complex Traits

We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM). SNHap-RHM captures regions in the genome contributing to the phenotypic variation that existing genome-wide analysis methods may fail to capture. We further demonstrate that there are real benefits to be gained from this approach by applying it to real data from about 20,000 individuals from the Generation Scotland: Scottish Family Health Study. We analysed height and major depressive disorder (MDD). We identified seven genomic regions that are genome-wide significant for height, and three regions significant at a suggestive threshold (p-value < 1 × 10-5) for MDD. These significant regions have genes mapped to within 400 kb of them. The genes mapped for height have been reported to be associated with height in humans. Similarly, those mapped for MDD have been reported to be associated with major depressive disorder and other psychiatry phenotypes. The results show that SNHap-RHM presents an exciting new opportunity to analyse complex traits by allowing the joint mapping of novel genomic regions tagged by either SNPs or haplotypes, potentially leading to the recovery of some of the "missing" heritability.

Genome-Wide Association Analysis to Search for New Loci Associated with Lifelong Premature Ejaculation Risk in Chinese Male Han Population

PURPOSE

Genetic factors play an indispensable role in the pathogenesis of lifelong premature ejaculation (LPE). The susceptibility genes/SNPs that have been discovered are very limited and can only explain part of the genetic effects of LPE. Therefore, discovering more genetic polymorphisms associated with the occurrence and development of LPE will help reveal the pathogenesis of LPE.

MATERIALS AND METHODS

We conducted a genome-wide association study of LPE in 486 Chinese male Han people (cases and controls). We used Gene Titan multi-channel instrument and Axiom Analysis Suite 6.0 software for genotyping. Imputation was performed by IMPUTE2 software and the 1000 Genomes Project (Phase3) was used as reference for haplotype. Finally, logistic regression analysis was performed on all loci that passed the quality control. The odds ratio and 95% confidence interval were calculated to determine the association between each SNPs and Chinese male Han population LPE risk.

RESULTS

The results showed that a total of 33 genetic variants in 13 genes (LACTBL1, SSBP3, ACOT11, LINC02486, TMEM154, LINC01098, NONE, HCG27, HLA-C, TNFSF8, TNC, FAM53B, SULF2) have a suggestively significant genome-wide association with LPE risk (p<5×10^-6).

CONCLUSIONS

This study is the first to conduct a GWAS on LPE in Chinese male Han population 33 genetic polymorphisms have a suggestive genome-wide association with LPE risk. This study have provided data supplement for the genetic loci of LPE risk, and laid a scientific foundation for the pathogenesis and the targeted therapy of LPE.

Genomics and transcriptomics landscapes associated to changes in insulin sensitivity in response to endurance exercise training

Despite good adherence to supervised endurance exercise training (EET), some individuals experience no or little improvement in peripheral insulin sensitivity. The genetic and molecular mechanisms underlying this phenomenon are currently not understood. By investigating genome-wide variants associated with baseline and exercise-induced changes (∆) in insulin sensitivity index (S_i) in healthy volunteers, we have identified novel candidate genes whose mouse knockouts phenotypes were consistent with a causative effect on S_i. An integrative analysis of functional genomic and transcriptomic profiles suggests genetic variants have an aggregate effect on baseline S_i and ∆S_i, focused around cholinergic signalling, including downstream calcium and chemokine signalling. The identification of calcium regulated MEF2A transcription factor as the most statistically significant candidate driving the transcriptional signature associated to ∆S_i further strengthens the relevance of calcium signalling in EET mediated S_i response.

Genome-wide association study of occupational attainment as a proxy for cognitive reserve

Occupational attainment, which represents middle-age cognitive activities, is a known proxy marker of cognitive reserve for Alzheimer's disease. Previous genome-wide association studies (GWAS) have identified numerous genetic variants and revealed the genetic architecture of educational attainment, another marker of cognitive reserve. However, the genetic architecture and heritability for occupational attainment remain elusive. We performed a large-scale GWAS of occupational attainment with 248,847 European individuals from the UK Biobank using the proportional odds logistic mixed model method. In this analysis, we defined occupational attainment using the classified job levels formulated in the UK Standard Occupational Classification system considering the individual professional skill and academic level. We identified 30 significant loci (P < 5 × 10-8); 12 were novel variants, unassociated with other traits. Among them, four lead variants were associated with genes expressed in brain tissues by expression quantitative trait loci mapping from 10 brain regions: rs13002946, rs3741368, rs11654986, and rs1627527. The single nucleotide polymorphism (SNP)-based heritability was estimated to be 8.5% (s.e. = 0.004) and partitioned heritability was enriched in the central nervous system and brain tissues. Genetic correlation analysis showed shared genetic backgrounds between occupational attainment and multiple traits, including education, intelligence, leisure activities, life satisfaction, and neuropsychiatric disorders. In two-sample Mendelian randomization (MR) analysis, we demonstrated that high occupation levels were associated with reduced risk for Alzheimer's disease (OR = 0.78, 95% CI = 0.65-0.92 in inverse variance weighted (IVW) method; OR = 0.73, 95% CI = 0.57-0.92 in the weighted median (WM) method). This causal relationship between occupational attainment and Alzheimer's disease was robust in additional sensitivity analysis that excluded potentially pleiotropic SNPs (OR = 0.72, 95% CI = 0.57-0.91 in the IVW method; OR = 0.72, 95% CI = 0.53-0.97 in the WM method). Multivariable MR confirmed that occupational attainment had an independent effect on the risk for Alzheimer's disease even after taking educational attainment into account (OR = 0.72, 95% CI = 0.54-0.95 in the IVW method; OR = 0.68, 95% CI = 0.48-0.97 in the WM method). Overall, our analyses provide insights into the genetic architecture of occupational attainment and demonstrate that occupational attainment is a potential causal protective factor for Alzheimer's disease as a proxy marker of cognitive reserve.

How (Epi)Genetic Regulation of the LIM-Domain Protein FHL2 Impacts Multifactorial Disease

Susceptibility to complex pathological conditions such as obesity, type 2 diabetes and cardiovascular disease is highly variable among individuals and arises from specific changes in gene expression in combination with external factors. The regulation of gene expression is determined by genetic variation (SNPs) and epigenetic marks that are influenced by environmental factors. Aging is a major risk factor for many multifactorial diseases and is increasingly associated with changes in DNA methylation, leading to differences in gene expression. Four and a half LIM domains 2 (FHL2) is a key regulator of intracellular signal transduction pathways and the FHL2 gene is consistently found as one of the top hyper-methylated genes upon aging. Remarkably, FHL2 expression increases with methylation. This was demonstrated in relevant metabolic tissues: white adipose tissue, pancreatic β-cells, and skeletal muscle. In this review, we provide an overview of the current knowledge on regulation of FHL2 by genetic variation and epigenetic DNA modification, and the potential consequences for age-related complex multifactorial diseases.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

Multivariate genome-wide covariance analyses of literacy, language and working memory skills reveal distinct etiologies

Several abilities outside literacy proper are associated with reading and spelling, both phenotypically and genetically, though our knowledge of multivariate genomic covariance structures is incomplete. Here, we introduce structural models describing genetic and residual influences between traits to study multivariate links across measures of literacy, phonological awareness, oral language, and phonological working memory (PWM) in unrelated UK youth (8-13 years, N = 6453). We find that all phenotypes share a large proportion of underlying genetic variation, although especially oral language and PWM reveal substantial differences in their genetic variance composition with substantial trait-specific genetic influences. Multivariate genetic and residual trait covariance showed concordant patterns, except for marked differences between oral language and literacy/phonological awareness, where strong genetic links contrasted near-zero residual overlap. These findings suggest differences in etiological mechanisms, acting beyond a pleiotropic set of genetic variants, and implicate variation in trait modifiability even among phenotypes that have high genetic correlations.

Genome-wide association study in the Taiwan biobank identifies four novel genes for human height: NABP2, RASA2, RNF41 and SLC39A5

Numerous genome-wide association studies (GWASs) have been conducted for the identification of genetic variants involved with human height. The vast majority of these studies, however, have been conducted in populations of European ancestry. Here, we report the first GWAS of adult height in the Taiwan Biobank using a discovery sample of 14 571 individuals and an independent replication sample of 20 506 individuals. From our analysis we generalize to the Taiwanese population genome-wide significant associations with height and 18 previously identified genes in European and non-Taiwanese East Asian populations. We also identify and replicate, at the genome-wide significance level, associated variants for height in four novel genes at two loci that have not previously been reported: RASA2 on chromosome 3 and NABP2, RNF41, and SLC39A5 at 12q13.3 on chromosome 12. RASA2 and RNF41 are strong candidates for having a role in height with copy number and loss of function variants in RASA2 previously found to be associated with short stature disorders, and decreased expression of the RNF41 gene resulting in insulin resistance in skeletal muscle. The results from our analysis of the Taiwan Biobank underscore the potential for the identification of novel genetic discoveries in underrepresented worldwide populations, even for traits, such as height, that have been extensively investigated in large-scale studies of European ancestry populations.

A novel nonlinear dimension reduction approach to infer population structure for low-coverage sequencing data

BACKGROUND

Low-depth sequencing allows researchers to increase sample size at the expense of lower accuracy. To incorporate uncertainties while maintaining statistical power, we introduce MCPCA_PopGen to analyze population structure of low-depth sequencing data.

RESULTS

The method optimizes the choice of nonlinear transformations of dosages to maximize the Ky Fan norm of the covariance matrix. The transformation incorporates the uncertainty in calling between heterozygotes and the common homozygotes for loci having a rare allele and is more linear when both variants are common.

CONCLUSIONS

We apply MCPCA_PopGen to samples from two indigenous Siberian populations and reveal hidden population structure accurately using only a single chromosome. The MCPCA_PopGen package is available on https://github.com/yiwenstat/MCPCA_PopGen .

Genome-wide association study of body fat distribution traits in Hispanics/Latinos from the HCHS/SOL

Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify the loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC) and hip circumference (HIP) adjusted for body mass index (adjBMI) by using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban and Dominican) background residing in the USA. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for waist-to-hip ratio adjusted for body mass index (WHRadjBMI), 22 for waist circumference adjusted for body mass index (WCadjBMI) and 28 for hip circumference adjusted for body mass index (HIPadjBMI), which reached suggestive significance (P < 1 × 10-6). Many loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in cohorts (N = 34 161) with participants of Hispanic/Latino, African and European descent. We confirmed four novel loci (P < 0.05 and consistent direction of effect, and P < 5 × 10-8 after meta-analysis), including two for WHRadjBMI (rs13301996, rs79478137); one for WCadjBMI (rs3168072) and one for HIPadjBMI (rs28692724). Also, we generalized previously reported associations to HCHS/SOL, (8 for WHRadjBMI, 10 for WCadjBMI and 12 for HIPadjBMI). Our study highlights the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity susceptibility that may be ancestry-specific.

Genetics of Body Fat Distribution: Comparative Analyses in Populations with European, Asian and African Ancestries

Preferential fat accumulation in visceral vs. subcutaneous depots makes obese individuals more prone to metabolic complications. Body fat distribution (FD) is regulated by genetics. FD patterns vary across ethnic groups independent of obesity. Asians have more and Africans have less visceral fat compared with Europeans. Consequently, Asians tend to be more susceptible to type 2 diabetes even with lower BMIs when compared with Europeans. To date, genome-wide association studies (GWAS) have identified more than 460 loci related to FD traits. However, the majority of these data were generated in European populations. In this review, we aimed to summarize recent advances in FD genetics with a focus on comparisons between European and non-European populations (Asians and Africans). We therefore not only compared FD-related susceptibility loci identified in three ethnicities but also discussed whether known genetic variants might explain the FD pattern heterogeneity across different ancestries. Moreover, we describe several novel candidate genes potentially regulating FD, including NID2, HECTD4 and GNAS, identified in studies with Asian populations. It is of note that in agreement with current knowledge, most of the proposed FD candidate genes found in Asians belong to the group of developmental genes.

GWAS of allometric body-shape indices in UK Biobank identifies loci suggesting associations with morphogenesis, organogenesis, adrenal cell renewal and cancer

Genetic studies have examined body-shape measures adjusted for body mass index (BMI), while allometric indices are additionally adjusted for height. We performed the first genome-wide association study of A Body Shape Index (ABSI), Hip Index (HI) and the new Waist-to-Hip Index and compared these with traditional indices, using data from the UK Biobank Resource for 219,872 women and 186,825 men with white British ancestry and Bayesian linear mixed-models (BOLT-LMM). One to two thirds of the loci identified for allometric body-shape indices were novel. Most prominent was rs72959041 variant in RSPO3 gene, expressed in visceral adipose tissue and regulating adrenal cell renewal. Highly ranked were genes related to morphogenesis and organogenesis, previously additionally linked to cancer development and progression. Genetic associations were fewer in men compared to women. Prominent region-specific associations showed variants in loci VEGFA and HMGA1 for ABSI and KLF14 for HI in women, and C5orf67 and HOXC4/5 for ABSI and RSPO3, VEGFA and SLC30A10 for HI in men. Although more variants were associated with waist and hip circumference adjusted for BMI compared to ABSI and HI, associations with height had previously been reported for many of the additional variants, illustrating the importance of adjusting correctly for height.

A Genome-Wide Association Study of Novel Genetic Variants Associated With Anthropometric Traits in Koreans

Most previous genome-wide association studies (GWAS) have identified genetic variants associated with anthropometric traits. However, most of the evidence were reported in European populations. Anthropometric traits such as height and body fat distribution are significantly affected by gender and genetic factors. Here we performed GWAS involving 64,193 Koreans to identify the genetic factors associated with anthropometric phenotypes including height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip ratio. We found nine novel single-nucleotide polymorphisms (SNPs) and 59 independent genetic signals in genomic regions that were reported previously. Of the 19 SNPs reported previously, eight genetic variants at RP11-513I15.6 and one genetic variant at the RP11-977G19.10 region and six Asian-specific genetic variants were newly found. We compared our findings with those of previous studies in other populations. Five overlapping genetic regions (PAN2, ANKRD52, RNF41, HGMA1, and C6orf106) had been reported previously but none of the SNPs were independently identified in the current study. Seven of the nine newly found novel loci associated with height in women revealed a statistically significant skeletal expression of quantitative trait loci. Our study provides additional insight into the genetic effects of anthropometric phenotypes in East Asians.

Genetics of Obesity: What We Have Learned Over Decades of Research

There is a genetic component to human obesity that accounts for 40% to 50% of the variability in body weight status but that is lower among normal weight individuals (about 30%) and substantially higher in the subpopulation of individuals with obesity and severe obesity (about 60%-80%). The appreciation that heritability varies across classes of BMI represents an important advance. After controlling for BMI, ectopic fat and fat distribution traits are characterized by heritability levels ranging from 30% to 55%. Defects in at least 15 genes are the cause of monogenic obesity cases, resulting mostly from deficiencies in the leptin-melanocortin signaling pathway. Approximately two-thirds of the BMI heritability can be imputed to common DNA variants, whereas low-frequency and rare variants explain the remaining fraction. Diminishing allele effect size is observed as the number of obesity-associated variants expands, with most BMI-increasing or -decreasing alleles contributing only a few grams or less to body weight. Obesity-promoting alleles exert minimal effects in normal weight individuals but have larger effects in individuals with a proneness to obesity, suggesting a higher penetrance; however, it is not known whether these larger effect sizes precede obesity or are caused by an obese state. The obesity genetic risk is conditioned by thousands of DNA variants that make genetically based obesity prevention and treatment a major challenge.

Estimating the causal effect of BMI on mortality risk in people with heart disease, diabetes and cancer using Mendelian randomization

BACKGROUND

Observational data have reported that being overweight or obese, compared to being normal weight, is associated with a lower risk for death - the "obesity paradox". We used Mendelian randomization (MR) to estimate causal effects of body mass index (BMI) on mortality risks in people with coronary heart disease (CHD), type 2 diabetes mellitus (T2DM) or malignancy in whom this paradox has been often reported.

METHODS

We studied 457,746 White British UK Biobank participants including three subgroups with T2DM (n = 19,737), CHD (n = 21,925) or cancer (n = 42,612) at baseline and used multivariable-adjusted Cox models and MR approaches to describe relationships between BMI and mortality risk.

RESULTS

Observational Cox models showed J-shaped relationships between BMI and mortality risk including within disease subgroups in which the BMI values associated with minimum mortality risk were within overweight/obese ranges (26.5-32.5 kg/m2). In all participants, MR analyses showed a positive linear causal effect of BMI on mortality risk (HR for mortality per unit higher BMI: 1.05; 95% CI: 1.03-1.08), also evident in people with CHD (HR: 1.08; 95% CI: 1.01-1.14). Point estimates for hazard ratios across all BMI values in participants with T2DM and cancer were consistent with overall positive linear effects but confidence intervals included the null.

CONCLUSION

These data support the idea that population efforts to promote intentional weight loss towards the normal BMI range would reduce, not enhance, mortality risk in the general population including, importantly, individuals with CHD.

Geographic variation in the polygenic score of height in Japan

A geographical gradient of height has existed in Japan for approximately 100 years. People in northern Japan tend to be taller than those in southern Japan. The differences in annual temperature and day length between the northern and southern prefectures of Japan have been suggested as possible causes of the height gradient. Although height is well known to be a polygenic trait with high heritability, the genetic contributions to the gradient have not yet been explored. Polygenic score (PS) is calculated by aggregating the effects of genetic variants identified by genome-wide association studies (GWASs) to predict the traits of individual subjects. Here, we calculated the PS of height for 10,840 Japanese individuals from all 47 prefectures in Japan. The median height PS for each prefecture was significantly correlated with the mean height of females and males obtained from another independent Japanese nation-wide height dataset, suggesting genetic contribution to the observed height gradient. We also found that individuals and prefectures genetically closer to continental East Asian ancestry tended to have a higher PS; modern Japanese people are considered to have originated as result of admixture between indigenous Jomon people and immigrants from continental East Asia. Another PS analysis based on the GWAS using only the mainland Japanese was conducted to evaluate the effect of population stratification on PS. The result also supported genetic contribution to height, and indicated that the PS might be affected by a bias due to population stratification even in a relatively homogenous population like Japanese.

A QTL for conformation of back and croup influences lateral gait quality in Icelandic horses

BACKGROUND

The back plays a vital role in horse locomotion, where the spine functions as a spring during the stride cycle. A complex interaction between the spine and the muscles of the back contribute to locomotion soundness, gait ability, and performance of riding and racehorses. Conformation is commonly used to select horses for breeding and performance in multiple horse breeds, where the back and croup conformation plays a significant role. The conformation of back and croup plays an important role on riding ability in Icelandic horses. However, the genes behind this trait are still unknown. Therefore, the aim of this study was to identify genomic regions associated with conformation of back and croup in Icelandic horses and to investigate their effects on riding ability. One hundred seventy-seven assessed Icelandic horses were included in the study. A genome-wide association analysis was performed using the 670 K+ Axiom Equine Genotyping Array, and the effects of different haplotypes in the top associated region were estimated for riding ability and additional conformation traits assessed during breeding field tests.

RESULTS

A suggestive quantitative trait loci (QTL) for the score of back and croup was detected on Equus caballus (ECA) 22 (p-value = 2.67 × 10- 7). Haplotype analysis revealed two opposite haplotypes, which resulted in higher and lower scores of the back and croup, respectively (p-value < 0.001). Horses with the favorable haplotype were more inclined to have a well-balanced backline with an uphill conformation and had, on average, higher scores for the lateral gaits tölt (p-value = 0.02) and pace (p-value = 0.004). This genomic region harbors three genes: C20orf85, ANKRD60 and LOC100056167. ANKRD60 is associated with body height in humans. C20orf85 and ANKRD60 are potentially linked to adolescent idiopathic scoliosis in humans.

CONCLUSIONS

Our results show that the detected QTL for conformation of back and croup is of importance for quality of lateral gaits in Icelandic horses. These findings could result in a genetic test to aid in the selection of breeding horses, thus they are of major interest for horse breeders. The results may also offer a gateway to comparative functional genomics by potentially linking both motor laterality and back inclination in horses with scoliosis in humans.

Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

Prioritization of Osteoporosis-Associated Genome-wide Association Study (GWAS) Single-Nucleotide Polymorphisms (SNPs) Using Epigenomics and Transcriptomics

Genetic risk factors for osteoporosis, a prevalent disease associated with aging, have been examined in many genome-wide association studies (GWASs). A major challenge is to prioritize transcription-regulatory GWAS-derived variants that are likely to be functional. Given the critical role of epigenetics in gene regulation, we have used an unusual epigenetics-based and transcription-based approach to identify some of the credible regulatory single-nucleotide polymorphisms (SNPs) relevant to osteoporosis from 38 reported bone mineral density (BMD) GWASs. Using Roadmap databases, we prioritized SNPs based upon their overlap with strong enhancer or promoter chromatin preferentially in osteoblasts relative to 12 heterologous cell culture types. We also required that these SNPs overlap open chromatin (Deoxyribonuclease I [DNaseI]-hypersensitive sites) and DNA sequences predicted to bind to osteoblast-relevant transcription factors in an allele-specific manner. From >50,000 GWAS-derived SNPs, we identified 14 novel and credible regulatory SNPs (Tier-1 SNPs) for osteoporosis risk. Their associated genes, BICC1, LGR4, DAAM2, NPR3, or HMGA2, are involved in osteoblastogenesis or bone homeostasis and regulate cell signaling or enhancer function. Four of these genes are preferentially expressed in osteoblasts. BICC1, LGR4, and DAAM2 play important roles in canonical Wnt signaling, a pathway critical for bone formation and repair. The transcription factors predicted to bind to the Tier-1 SNP-containing DNA sequences also have bone-related functions. We present evidence that some of the Tier-1 SNPs exert their effects on BMD risk indirectly through little-studied long noncoding RNA (lncRNA) genes, which may, in turn, control the nearby bone-related protein-encoding gene. Our study illustrates a method to identify novel BMD-related causal regulatory SNPs for future study and to prioritize candidate regulatory GWAS-derived SNPs, in general. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

A Genome-Wide Association Study of Childhood Body Fatness

OBJECTIVE

This study aimed to uncover genetic contributors to adiposity in early life.

METHODS

A genome-wide association study of childhood body fatness in 34,401 individuals within the Nurses' Health Studies and the Health Professionals Follow-up Study was conducted. Data were imputed to the 1000 Genomes Phase 3 version 5 reference panel.

RESULTS

A total of 1,354 single-nucleotide polymorphisms (P < 10^-4 ) were selected for replication in a previously published genome-wide association study of childhood BMI. Nineteen significant genome-wide (P < 5 × 10^-8 ) regions were observed, fourteen of which were previously associated with childhood obesity and five were novel: BNDF (P = 7.58 × 10^-13 ), PRKD1 (P = 1.43 × 10^-10 ), 20p13 (P = 2.05 × 10^-10 ), FHIT (P = 1.77 × 10^-8 ), and LOC101927575 (P = 3.22 × 10^-8 ). The BNDF, FHIT, and PRKD1 regions were previously associated with adult BMI. LOC101927575 and 20p13 regions have not previously been associated with adiposity phenotypes. In a transcriptome-wide analysis, associations for POMC at 2p23.3 (P = 3.36 × 10^-6 ) and with TMEM18 at 2p25.3 (P = 3.53 × 10^-7 ) were observed. Childhood body fatness was genetically correlated with hip (r_g = 0.42, P = 4.44 × 10^-16 ) and waist circumference (r_g = 0.39, P = 5.56 × 10^-16 ), as well as age at menarche (r_g = -0.37, P = 7.96 × 10^-19 ).

CONCLUSIONS

Additional loci that contribute to childhood adiposity were identified, further explicating its genetic architecture.

Combination of Genome-Wide Polymorphisms and Copy Number Variations of Pharmacogenes in Koreans

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.

Contrasting effects of Western vs Mediterranean diets on monocyte inflammatory gene expression and social behavior in a primate model

Dietary changes associated with industrialization increase the prevalence of chronic diseases, such as obesity, type II diabetes, and cardiovascular disease. This relationship is often attributed to an 'evolutionary mismatch' between human physiology and modern nutritional environments. Western diets enriched with foods that were scarce throughout human evolutionary history (e.g. simple sugars and saturated fats) promote inflammation and disease relative to diets more akin to ancestral human hunter-gatherer diets, such as a Mediterranean diet. Peripheral blood monocytes, precursors to macrophages and important mediators of innate immunity and inflammation, are sensitive to the environment and may represent a critical intermediate in the pathway linking diet to disease. We evaluated the effects of 15 months of whole diet manipulations mimicking Western or Mediterranean diet patterns on monocyte polarization in a well-established model of human health, the cynomolgus macaque (Macaca fascicularis). Monocyte transcriptional profiles differed markedly between diets, with 40% of transcripts showing differential expression (FDR < 0.05). Monocytes from Western diet consumers were polarized toward a more proinflammatory phenotype. The Western diet shifted the co-expression of 445 gene pairs, including small RNAs and transcription factors associated with metabolism and adiposity in humans, and dramatically altered behavior. For example, Western-fed individuals were more anxious and less socially integrated. These behavioral changes were also associated with some of the effects of diet on gene expression, suggesting an interaction between diet, central nervous system activity, and monocyte gene expression. This study provides new molecular insights into an evolutionary mismatch and uncovers new pathways through which Western diets alter monocyte polarization toward a proinflammatory phenotype.

BDNF Gene as a Precision Skill of Obesity Management

The scarcity of the results obtained for the treatment of obesity leads us to consider new strategies, contemplating all the factors involved in the development of the disease. One of the key molecules for controlling body weight and energy homeostasis is the brain-derived neurotrophic factor (BDNF). This work summarizes the mechanisms in which BDNF gene regulates this multifactorial disease. In addition, we discuss the role of other BDNF polymorphisms as genetic determinants of obesity. In this context, a total of 14 SNPs near or inside BDNF/BDNF-AS related to BMI were identified in various GWASs. Finally, we assess gene-diet interaction as a novel tool to prevent obesity and formulate solid and personalized nutritional management. Our research group has performed the first study on the association of BDNF-AS rs925946 polymorphism and calcium intake as potential modulators of the nutritional status. Although these results should be confirmed in future studies, they open the path for new prevention opportunities.

Genome-wide association studies for growth-related traits in a crossbreed pig population

Growth-related traits are important economic traits in the pig industry that directly influence pork production efficiency. To detect quantitative trait loci and candidate genes affecting growth traits, genome-wide association studies were performed for backfat thickness (BF) and loin muscle depth (LMD) in 370 Chuying-black pigs using Illumina PorcineSNP50 BeadChip array. We totally identified 14 BF-associated SNPs, which included 11 genome-wide SNPs (P < 1.39E-06) and 3 chromosome-wide suggestive SNPs (P < 2.79E-05) and for LMD, 9 SNPs surpassed the genome-wide significant threshold (P < 1.39E-06). These SNPs explained 30.33 and 27.51% phenotypic variance for BF and LMD respectively. Furthermore, 14 and 9 genes nearest to the significant SNPs were selected to be candidate genes, including MAGED1, GPHN, CCSER1, and GUCY2D for BF and PARM1, COL18A1, HSF5, and SCML2 genes for LMD. One significant SNP, which explained 6.07% of phenotypic variance for BF, mapped to a pleiotropic quantitative trait locus with a 494-kb interval. Together, the SNPs and candidate genes identified in this study will advance our understanding of the complex genetic architecture of BF and LMD traits, and they will also provide important clues for future implementation of a genomic selection program in Chuying-black pigs.

Population-Matched Transcriptome Prediction Increases TWAS Discovery and Replication Rate

Most genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) focus on European populations; however, these results cannot always be accurately applied to non-European populations due to genetic architecture differences. Using GWAS summary statistics in the Population Architecture using Genomics and Epidemiology study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we perform TWAS to determine gene-trait associations. We compared results using three transcriptome prediction models derived from Multi-Ethnic Study of Atherosclerosis populations: the African American and Hispanic/Latino (AFHI) model, the European (EUR) model, and the African American, Hispanic/Latino, and European (ALL) model. We identified 240 unique significant trait-associated genes. We found more significant, colocalized genes that replicate in larger cohorts when applying the AFHI model than the EUR or ALL model. Thus, TWAS with population-matched transcriptome models have more power for discovery and replication, demonstrating the need for more transcriptome studies in diverse populations.

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TWAS mechanistically extends GWAS findings in diverse populations

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Population-matched transcriptome models detect more replicable associations

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Colocalization shows GWAS variants likely act through gene expression regulation

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More GWAS and transcriptome modeling in diverse populations are needed

Multiple-Tissue Integrative Transcriptome-Wide Association Studies Discovered New Genes Associated With Amyotrophic Lateral Sclerosis

Genome-wide association studies (GWAS) have identified multiple causal genes associated with amyotrophic lateral sclerosis (ALS); however, the genetic architecture of ALS remains completely unknown and a large number of causal genes have yet been discovered. To full such gap in part, we implemented an integrative analysis of transcriptome-wide association study (TWAS) for ALS to prioritize causal genes with summary statistics from 80,610 European individuals and employed 13 GTEx brain tissues as reference transcriptome panels. The summary-level TWAS analysis with single brain tissue was first undertaken and then a flexible p-value combination strategy, called summary data-based Cauchy Aggregation TWAS (SCAT), was proposed to pool association signals from single-tissue TWAS analysis while protecting against highly positive correlation among tests. Extensive simulations demonstrated SCAT can produce well-calibrated p-value for the control of type I error and was often much more powerful to identify association signals across various scenarios compared with single-tissue TWAS analysis. Using SCAT, we replicated three ALS-associated genes (i.e., ATXN3, SCFD1, and C9orf72) identified in previous GWASs and discovered additional five genes (i.e., SLC9A8, FAM66D, TRIP11, JUP, and RP11-529H20.6) which were not reported before. Furthermore, we discovered the five associations were largely driven by genes themselves and thus might be new genes which were likely related to the risk of ALS. However, further investigations are warranted to verify these results and untangle the pathophysiological function of the genes in developing ALS.

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.

Genetic Determinants of Lung Cancer Prognosis in Never Smokers: A Pooled Analysis in the International Lung Cancer Consortium

BACKGROUND

Lung cancer remains the leading cause of cancer death worldwide, with 15% to 20% occurring in never smokers. To assess genetic determinants for prognosis among never smokers, we conducted a genome-wide investigation in the International Lung Cancer Consortium (ILCCO).

METHODS

Genomic and clinical data from 1,569 never-smoking patients with lung cancer of European ancestry from 10 ILCCO studies were included. HRs and 95% confidence intervals of overall survival were estimated. We assessed whether the associations were mediated through mRNA expression-based 1,553 normal lung tissues from the lung expression quantitative trait loci (eQTL) dataset and Genotype-Tissue Expression (GTEx). For cross-ethnicity generalization, we assessed the associations in a Japanese study (N = 887).

RESULTS

One locus at 13q22.2 was associated with lung adenocarcinoma survival at genome-wide level, with carriers of rs12875562-T allele exhibiting poor prognosis [HR = 1.71 (1.41-2.07), P = 3.60 × 10-8], and altered mRNA expression of LMO7DN in lung tissue (GTEx, P = 9.40 × 10-7; Lung eQTL dataset, P = 0.003). Furthermore, 2 of 11 independent loci that reached the suggestive significance level (P < 10-6) were significant eQTL affecting mRNA expression of nearby genes in lung tissues, including CAPZB at 1p36.13 and UBAC1 at 9q34.3. One locus encoding NWD2/KIAA1239 at 4p14 showed associations in both European [HR = 0.50 (0.38-0.66), P = 6.92 × 10-7] and Japanese populations [HR = 0.79 (0.67-0.94), P = 0.007].

CONCLUSIONS

Based on the largest genomic investigation on the lung cancer prognosis of never smokers to date, we observed that lung cancer prognosis is affected by inherited genetic variants.

IMPACT

We identified one locus near LMO7DN at genome-wide level and several potential prognostic genes with cis-effect on mRNA expression. Further functional genomics work is required to understand their role in tumor progression.

Four pleiotropic loci associated with fat mass and lean mass

BACKGROUND

Fat mass and lean mass are two biggest components of body mass. Both fat mass and lean mass are under strong genetic determinants and are correlated.

METHODS

We performed a bivariate genome-wide association meta-analysis of (lean adjusted) leg fat mass and (fat adjusted) leg lean mass in 12,517 subjects from 6 samples, and followed by in silico replication in large-scale UK biobank cohort sample (N = 370 097).

RESULTS

We identified four loci that were significant at the genome-wide significance (GWS, α = 5.0 × 10-8) level at the discovery meta-analysis, and successfully replicated in the replication sample: 2q36.3 (rs1024137, pdiscovery = 3.32 × 10-8, preplication = 4.07 × 10-13), 5q13.1 (rs4976033, pdiscovery = 1.93 × 10-9, preplication = 6.35 × 10-7), 12q24.31 (rs4765528, pdiscovery = 7.19 × 10-12, preplication = 1.88 × 10-11) and 18q21.32 (rs371326986, pdiscovery = 9.04 × 10-9, preplication = 2.35 × 10-95). The above four pleiotropic loci may play a pleiotropic role for fat mass and lean mass development.

CONCLUSIONS

Our findings further enhance the understanding of the genetic association between fat mass and lean mass and provide a new theoretical basis for their understanding.

Whole-exome sequencing and genome-wide association studies identify novel sarcopenia risk genes in Han Chinese

Sarcopenia is a complex polygenic disease, and its molecular mechanism is still unclear. Whole lean body mass (WLBM) is a heritable trait predicting sarcopenia. To identify genomic loci underlying, we performed a whole-exome sequencing (WES) of WLBM variation with high sequencing depth (more than 40*) in 101 Chinese subjects. We then replicated in the major findings in the large-scale UK Biobank (UKB) cohort (N = 217,822) for WLBM. The results of four single-nucleotide polymorphisms (SNPs) were significant both in the discovery stage and replication stage: SNP rs740681 (discovery p = 1.66 × 10-6 , replication p = .05), rs2272303 (discovery p = 3.20 × 10-4 , replication p = 3.10 × 10-4 ), rs11170413 (discovery p = 3.99 × 10-4 , replication p = 2.90 × 10-4 ), and rs2272302 (discovery p = 9.13 × 10-4 , replication p = 3.10 × 10-4 ). We combined p values of the significant SNPs. Functional annotations highlighted two candidate genes, including FZR1 and SOAT2, that may exert pleiotropic effects to the development of body mass. Our findings provide useful insights that further enhance our understanding of genetic interplay in sarcopenia.

Evaluation of genetic susceptibility of common variants in SOX9 in patients with congenital talipes equinovarus in the Han Chinese population

Background

Congenital talipes equinovarus (CTEV) is a common birth defect that causes severe deformities of one or both feet. Genetics have been proven to play a key role in the risk of CTEV. Our study aimed to evaluate the genetic susceptibility of common variants in the SOX9 gene to CTEV in a Han Chinese population.

Methods

In this study, we recruited 2,205 study participants, including 692 CTEV patients and 1513 healthy controls. A total of seven selected single-nucleotide polymorphisms (SNPs) within the SOX9 gene were genotyped, and environmental variables, including maternal smoking and alcoholic drinking habits, were assessed. In addition, bioinformatics analyses were performed to explore the potential biological functions of the associated SNPs.

Results

The SNP rs73354570 was identified to be significantly associated with the risk of CTEV (OR = 1.53, P = 2.11 × 10⁻⁵), and the C allele was associated with an increased risk of CTEV. A dose-dependent pattern could be observed in genotypic analyses. The OR for individuals with AC genotypes was 1.37 (95% CI 1.09–1.71), and the OR for individuals with CC homozygotes was 1.47 (95% CI 1.18–1.82). Further analyses identified that rs73354570 is located within a region of multiple binding proteins, including CEBPB and POLR2A, which suggested that this SNP was also part of genetic motifs that are found within several cell types.

Conclusion

Our results provide evidence supporting the important role of the SOX9 gene in the contribution to the risk of CTEV.

Mid-Gestation lethality of Atxn2l-Ablated Mice

Depletion of yeast/fly Ataxin-2 rescues TDP-43 overexpression toxicity. In mouse models of Amyotrophic Lateral Sclerosis via TDP-43 overexpression, depletion of its ortholog ATXN2 mitigated motor neuron degeneration and extended lifespan from 25 days to >300 days. There is another ortholog in mammals, named ATXN2L (Ataxin-2-like), which is almost uncharacterized but also functions in RNA surveillance at stress granules. We generated mice with Crispr/Cas9-mediated deletion of Atxn2l exons 5-8, studying homozygotes prenatally and heterozygotes during aging. Our novel findings indicate that ATXN2L absence triggers mid-gestational embryonic lethality, affecting female animals more strongly. Weight and development stages of homozygous mutants were reduced. Placenta phenotypes were not apparent, but brain histology showed lamination defects and apoptosis. Aged heterozygotes showed no locomotor deficits or weight loss over 12 months. Null mutants in vivo displayed compensatory efforts to maximize Atxn2l expression, which were prevented upon nutrient abundance in vitro. Mouse embryonal fibroblast cells revealed more multinucleated giant cells upon ATXN2L deficiency. In addition, in human neural cells, transcript levels of ATXN2L were induced upon starvation and glucose and amino acids exposure, but this induction was partially prevented by serum or low cholesterol administration. Neither ATXN2L depletion triggered dysregulation of ATXN2, nor a converse effect was observed. Overall, this essential role of ATXN2L for embryogenesis raises questions about its role in neurodegenerative diseases and neuroprotective therapies.

Concentrations of persistent organic pollutants in maternal plasma and epigenome-wide placental DNA methylation

Background

Prenatal maternal plasma persistent organic pollutant (POP) concentrations have been associated with neonatal outcomes. However, the underlying mechanisms remain unknown. Placental epigenetic mechanisms may be involved, but no prior epigenome-wide studies have investigated the impact of maternal POPs on placental DNA methylation. We studied the association between maternal plasma POP concentration in early pregnancy and epigenome-wide placental DNA methylation among 260 pregnant women from the NICHD Fetal Growth Studies.

Results

Our analysis focused on POPs with more than 80% plasma concentrations above the limit of quantification, including 3 organochlorine pesticides (hexachlorobenzene, trans-nonachlor, p,p’-dichlorodiphenyldichloroethylene), 1 polybrominated diphenyl ether (PBDE 47), 3 polychlorinated biphenyls (138/158, 153, 180), and 6 poly- and perfluorinated alkyl substances (PFASs) (perfluorodecanoic acid, perfluorohexanesulfonic acid, perfluorononanoic acid, perfluorooctanesulfonic acid, perfluoroundecanoic acid (PFUnDA)). Using 5% false discovery rate, POPs were associated with a total of 214 differentially methylated CpG sites (nominal p values ranging from 2.61 × 10⁻²¹ to 2.11 × 10⁻⁷). Out of the 214 CpG sites, 24 (11%) were significantly correlated with placental expression of 21 genes. Notably, higher PFUnDA was associated with increased methylation at 3 CpG sites (cg13996963, cg12089439, cg18145877) annotated to TUSC3, and increased methylation at those 3 CpG sites was correlated with decreased expression of TUSC3 in the placenta. Increased methylation at cg18145877 (TUSC3) and decreased expression of TUSC3 were correlated with shorter birth length. Out of the 214 CpG sites, methylation at 44 CpG sites was correlated (p value < 0.10) with at least one neonatal anthropometry measure (i.e., birth weight, birth length, and head circumference). Seven CpG sites mediated (p value < 0.05) the association between PBDE 47 and neonatal anthropometry measures. Genes annotating the top differentially methylated CpG sites were enriched in pathways related to differentiation of embryonic cells (PBDE 47) and in pathways related to brain size and brain morphology (PFASs).

Conclusions

DNA methylation changes in the placenta were significantly associated with maternal plasma POPs concentration. The findings suggest that placental DNA methylation and gene expression mechanism may be involved in the prenatal toxicity of POPs and their association with neonatal anthropometry measures.

Very low-depth whole-genome sequencing in complex trait association studies

Motivation

Very low-depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterization of the genotype quality and association power for very low-depth sequencing designs is still lacking.

Results

We perform cohort-wide whole-genome sequencing (WGS) at low depth in 1239 individuals (990 at 1× depth and 249 at 4× depth) from an isolated population, and establish a robust pipeline for calling and imputing very low-depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (75× depth) and high-depth (22×) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1× WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1× further allowed the discovery of 140 844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low-depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design.

Availability and implementation

The HELIC genotype and WGS datasets have been deposited to the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home): EGAD00010000518; EGAD00010000522; EGAD00010000610; EGAD00001001636, EGAD00001001637. The peakplotter software is available at https://github.com/wtsi-team144/peakplotter, the transformPhenotype app can be downloaded at https://github.com/wtsi-team144/transformPhenotype.

Supplementary information

Supplementary data are available at Bioinformatics online.

Power loss due to testing association between covariate-adjusted traits and genetic variants

Multiple linear regression is commonly used to test for association between genetic variants and continuous traits and estimate genetic effect sizes. Confounding variables are controlled for by including them as additional covariates. An alternative technique that is increasingly used is to regress out covariates from the raw trait and then perform regression analysis with only the genetic variants included as predictors. In the case of single-variant analysis, this adjusted trait regression (ATR) technique is known to be less powerful than the traditional technique when the genetic variant is correlated with the covariates We extend previous results for single-variant tests by deriving exact relationships between the single-variant score, Wald, likelihood-ratio, and F test statistics and their ATR analogs. We also derive the asymptotic power of ATR analogs of the multiple-variant score and burden tests. We show that the maximum power loss of the ATR analog of the multiple-variant score test is completely characterized by the canonical correlations between the set of genetic variants and the set of covariates. Further, we show that for both single- and multiple-variant tests, the power loss for ATR analogs increases with increasing stringency of Type 1 error control ( α ) and increasing correlation (or canonical correlations) between the genetic variant (or multiple variants) and covariates. We recommend using ATR only when maximum canonical correlation between variants and covariates is low, as is typically true.

A big-data approach to understanding metabolic rate and response to obesity in laboratory mice

Maintaining a healthy body weight requires an exquisite balance between energy intake and energy expenditure. To understand the genetic and environmental factors that contribute to the regulation of body weight, an important first step is to establish the normal range of metabolic values and primary sources contributing to variability. Energy metabolism is measured by powerful and sensitive indirect calorimetry devices. Analysis of nearly 10,000 wild-type mice from two large-scale experiments revealed that the largest variation in energy expenditure is due to body composition, ambient temperature, and institutional site of experimentation. We also analyze variation in 2329 knockout strains and establish a reference for the magnitude of metabolic changes. Based on these findings, we provide suggestions for how best to design and conduct energy balance experiments in rodents. These recommendations will move us closer to the goal of a centralized physiological repository to foster transparency, rigor and reproducibility in metabolic physiology experimentation.

Insights into the aetiology of snoring from observational and genetic investigations in the UK Biobank

Although snoring is common in the general population, its aetiology has been largely understudied. Here we report a genetic study on snoring (n ~ 408,000; snorers ~ 152,000) using data from the UK Biobank. We identify 42 genome-wide significant loci, with an SNP-based heritability estimate of ~10% on the liability scale. Genetic correlations with body mass index, alcohol intake, smoking, schizophrenia, anorexia nervosa and neuroticism are observed. Gene-based associations identify 173 genes, including DLEU7, MSRB3 and POC5, highlighting genes expressed in the brain, cerebellum, lungs, blood and oesophagus. We use polygenic scores (PGS) to predict recent snoring and probable obstructive sleep apnoea (OSA) in an independent Australian sample (n ~ 8000). Mendelian randomization analyses suggest a potential causal relationship between high BMI and snoring. Altogether, our results uncover insights into the aetiology of snoring as a complex sleep-related trait and its role in health and disease beyond it being a cardinal symptom of OSA.

Snoring is common in the population and tends to be more prevalent in older and/or male individuals. Here, the authors perform GWAS for habitual snoring, identify 41 genomic loci and explore potential causal relationships with anthropometric and cardiometabolic disease traits.

Combining sequence data from multiple studies: Impact of analysis strategies on rare variant calling and association results

Individual sequencing studies often have limited sample sizes and so limited power to detect trait associations with rare variants. A common strategy is to aggregate data from multiple studies. For studying rare variants, jointly calling all samples together is the gold standard strategy but can be difficult to implement due to privacy restrictions and computational burden. Here, we compare joint calling to the alternative of single-study calling in terms of variant detection sensitivity and genotype accuracy as a function of sequencing coverage and assess their impact on downstream association analysis. To do so, we analyze deep-coverage (~82×) exome and low-coverage (~5×) genome sequence data on 2,250 individuals from the Genetics of Type 2 Diabetes study jointly and separately within five geographic cohorts. For rare single nucleotide variants (SNVs): (a) ≥97% of discovered SNVs are found by both calling strategies; (b) nonreference concordance with a set of highly accurate genotypes is ≥99% for both calling strategies; (c) meta-analysis has similar power to joint analysis in deep-coverage sequence data but can be less powerful in low-coverage sequence data. Given similar data processing and quality control steps, we recommend single-study calling as a viable alternative to joint calling for analyzing SNVs of all minor allele frequency in deep-coverage data.

Benefits and limitations of genome-wide association studies

Genome-wide association studies (GWAS) involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have revolutionized the field of complex disease genetics over the past decade, providing numerous compelling associations for human complex traits and diseases. Despite clear successes in identifying novel disease susceptibility genes and biological pathways and in translating these findings into clinical care, GWAS have not been without controversy. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. In this Review, we comprehensively assess the benefits and limitations of GWAS in human populations and discuss the relevance of performing more GWAS.

DNA Methylation Signatures of Breastfeeding in Buccal Cells Collected in Mid-Childhood

Breastfeeding has long-term benefits for children that may be mediated via the epigenome. This pathway has been hypothesized, but the number of empirical studies in humans is small and mostly done by using peripheral blood as the DNA source. We performed an epigenome-wide association study (EWAS) in buccal cells collected around age nine (mean = 9.5) from 1006 twins recruited by the Netherlands Twin Register (NTR). An age-stratified analysis examined if effects attenuate with age (median split at 10 years; n<10 = 517, mean age = 7.9; n>10 = 489, mean age = 11.2). We performed replication analyses in two independent cohorts from the NTR (buccal cells) and the Avon Longitudinal Study of Parents and Children (ALSPAC) (peripheral blood), and we tested loci previously associated with breastfeeding in epigenetic studies. Genome-wide DNA methylation was assessed with the Illumina Infinium MethylationEPIC BeadChip (Illumina, San Diego, CA, USA) in the NTR and with the HumanMethylation450 Bead Chip in the ALSPAC. The duration of breastfeeding was dichotomized ('never' vs. 'ever'). In the total sample, no robustly associated epigenome-wide significant CpGs were identified (α = 6.34 × 10-8). In the sub-group of children younger than 10 years, four significant CpGs were associated with breastfeeding after adjusting for child and maternal characteristics. In children older than 10 years, methylation differences at these CpGs were smaller and non-significant. The findings did not replicate in the NTR sample (n = 98; mean age = 7.5 years), and no nearby sites were associated with breastfeeding in the ALSPAC study (n = 938; mean age = 7.4). Of the CpG sites previously reported in the literature, three were associated with breastfeeding in children younger than 10 years, thus showing that these CpGs are associated with breastfeeding in buccal and blood cells. Our study is the first to show that breastfeeding is associated with epigenetic variation in buccal cells in children. Further studies are needed to investigate if methylation differences at these loci are caused by breastfeeding or by other unmeasured confounders, as well as what mechanism drives changes in associations with age.

Characterizing rare and low-frequency height-associated variants in the Japanese population

Human height is a representative phenotype to elucidate genetic architecture. However, the majority of large studies have been performed in European population. To investigate the rare and low-frequency variants associated with height, we construct a reference panel (N = 3,541) for genotype imputation by integrating the whole-genome sequence data from 1,037 Japanese with that of the 1000 Genomes Project, and perform a genome-wide association study in 191,787 Japanese. We report 573 height-associated variants, including 22 rare and 42 low-frequency variants. These 64 variants explain 1.7% of the phenotypic variance. Furthermore, a gene-based analysis identifies two genes with multiple height-increasing rare and low-frequency nonsynonymous variants (SLC27A3 and CYP26B1; P_SKAT-O < 2.5 × 10⁻⁶). Our analysis shows a general tendency of the effect sizes of rare variants towards increasing height, which is contrary to findings among Europeans, suggesting that height-associated rare variants are under different selection pressure in Japanese and European populations.

Thousands of genetic loci are known to associate with human height, but these are mainly based on studies in European ancestry populations. Here, Akiyama et al. construct a genotype reference panel for the Japanese population followed by GWAS and report 573 height associated variants in 191,787 Japanese.

Functional rare variants influence the clinical response to anti-TNF therapy in Crohn's disease

BACKGROUND

The effect of low-frequency functional variation on anti-tumor necrosis factor alpha (TNF) response in Crohn's disease (CD) patients remains unexplored. The objective of this study was to investigate the impact of functional rare variants in clinical response to anti-TNF therapy in CD.

METHODS

CD anti-TNF naïve patients starting anti-TNF treatment due to active disease [Crohn's Disease Activity Index (CDAI > 150)] were included. The whole genome was sequenced using the Illumina Hiseq4000 platform. Clinical response was defined as a CDAI score <150 at week 14 of anti-TNF treatment. Low-frequency variants were annotated and classified according to their damaging potential. The whole genome of CD patients was screened to identify homozygous loss-of-function (LoF) variants. The TNF signaling pathway was tested for overabundance of damaging variants using the SKAT-O method. Functional implication of the associated rare variation was evaluated using cell-type epigenetic enrichment analyses.

RESULTS

A total of 41 consecutive CD patients were included; 3250 functional rare variants were identified (2682 damaging and 568 LoF variants). Two homozygous LoF mutations were found in HLA-B and HLA-DRB1 genes associated with lack of response and remission, respectively. Genome-wide LoF variants were enriched in epigenetic marks specific for the gastrointestinal tissue (colon, p = 4.11e-4; duodenum, p = 0.011). The burden of damaging variation in the TNF signaling pathway was associated with response to anti-TNF therapy (p = 0.016); damaging variants were enriched in epigenetic marks from CD8⁺ (p = 6.01e-4) and CD4+ (p = 0.032) T cells.

CONCLUSIONS

Functional rare variants are involved in the response to anti-TNF therapy in CD. Cell-type enrichment analysis suggests that the gut mucosa and CD8⁺ T cells are the main mediators of this response.