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

Genomic insights into gestational weight gain uncover tissue-specific mechanisms and pathways

Gestational weight gain (GWG) is linked to adverse outcomes in pregnant persons and offspring. The Early Growth Genetics Consortium previously identified genetic variants contributing to GWG from fetal and maternal genomes. However, their biologic mechanisms and tissue-specificity are unknown. We evaluated the association between genetically predicted gene expression in relevant maternal (subcutaneous and visceral adipose, breast, uterus, and whole blood) tissues from GTEx (v7) and fetal (placenta) tissue and early, late, and total GWG using S-PrediXcan. We tested for pathway enrichment using the GENE2FUNC module from Functional Mapping and Annotation of Genome-Wide Association Studies. After Bonferroni correction, we found no associations between maternal or fetal gene expression and GWG. Among nominally significant (P < 0.05) maternal genes, there was enrichment of several biological pathways, including metabolic processes, secretion, and intracellular transport, that varied across pregnancy. These results indicate the likely influence of diverse pathways, varying by tissue and weeks of gestation, on GWG.

The Genetic Variants Influencing Hypertension Prevalence Based on the Risk of Insulin Resistance as Assessed Using the Metabolic Score for Insulin Resistance (METS-IR)

Insulin resistance is a major indicator of cardiovascular diseases, including hypertension. The Metabolic Score for Insulin Resistance (METS-IR) offers a simplified and cost-effective way to evaluate insulin resistance. This study aimed to identify genetic variants associated with the prevalence of hypertension stratified by METS-IR score levels. Data from the Korean Genome and Epidemiology Study (KoGES) were analyzed. The METS-IR was calculated using the following formula: ln [(2 × fasting blood glucose (FBG) + triglycerides (TG)) × body mass index (BMI)]/ ln [high-density lipoprotein cholesterol (HDL-C)]. The participants were divided into tertiles 1 (T1) and 3 (T3) based on their METS-IR scores. Genome-wide association studies (GWAS) were performed for hypertensive cases and non-hypertensive controls within these tertile groups using logistic regression adjusted for age, sex, and lifestyle factors. Among the METS-IR tertile groups, 3517 of the 19,774 participants (17.8%) at T1 had hypertension, whereas 8653 of the 20,374 participants (42.5%) at T3 had hypertension. A total of 113 single-nucleotide polymorphisms (SNPs) reached the GWAS significance threshold (p < 5 × 10-8) in at least one tertile group, mapping to six distinct genetic loci. Notably, four loci, rs11899121 (chr2p24), rs7556898 (chr2q24.3), rs17249754 (ATP2B1), and rs1980854 (chr20p12.2), were significantly associated with hypertension in the high-METS-score group (T3). rs10857147 (FGF5) was significant in both the T1 and T3 groups, whereas rs671 (ALDH2) was significant only in the T1 group. The GWASs identified six genetic loci significantly associated with hypertension, with distinct patterns across METS-IR tertiles, highlighting the role of metabolic context in genetic susceptibility. These findings underscore critical genetic factors influencing hypertension prevalence and provide insights into the metabolic-genetic interplay underlying this condition.

Genome-wide meta-analysis identifies 22 loci for normal tension glaucoma with significant overlap with high tension glaucoma

Primary open-angle glaucoma typically presents as two subtypes. This study aimed to elucidate the shared and distinct genetic architectures of normal-tension (NTG) and high-tension glaucoma (HTG), motivated by the need to develop intraocular pressure (IOP)-independent drug targets for the disease. We conducted a comprehensive multi-ethnic meta-analysis, prioritized variants based on functional annotation, and explored drug-gene interactions. We further assessed the genetic overlap between NTG and HTG using pairwise GWAS analysis. We identified 22 risk loci associated with NTG, 17 of which have not previously been reported for NTG. Two loci, BMP4 and TBKBP1, have not previously been associated with glaucoma at the genome-wide significance level. Our results indicate that while there is a significant overlap in risk loci between tension subtypes, the magnitude of the effect tends to be lower in NTG compared to HTG, particularly for IOP-related loci. Additionally, we identified a potential role for biologic immunomodulatory treatments as neuroprotective agents.

Gene-environment interactions in the influence of maternal education on adolescent neurodevelopment using ABCD study

Maternal education was strongly correlated with adolescent brain morphology, cognitive performances, and mental health. However, the molecular basis for the effects of maternal education on the structural neurodevelopment remains unknown. Here, we conducted gene-environment-wide interaction study using the Adolescent Brain Cognitive Development cohort. Seven genomic loci with significant gene-environment interactions (G×E) on regional gray matter volumes were identified, with enriched biological functions related to metabolic process, inflammatory process, and synaptic plasticity. Additionally, genetic overlapping results with behavioral and disease-related phenotypes indicated shared biological mechanism between maternal education modified neurodevelopment and related behavioral traits. Finally, by decomposing the multidimensional components of maternal education, we found that socioeconomic status, rather than family environment, played a more important role in modifying the genetic effects on neurodevelopment. In summary, our study provided analytical evidence for G×E effects regarding adolescent neurodevelopment and explored potential biological mechanisms as well as social mechanisms through which maternal education could modify the genetic effects on regional brain development.

Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study

BACKGROUND

Artificial intelligence (AI)-enabled electrocardiography (ECG) can be used to predict risk of future disease and mortality but has not yet been adopted into clinical practice. Existing model predictions do not have actionability at an individual patient level, explainability, or biological plausibi. We sought to address these limitations of previous AI-ECG approaches by developing the AI-ECG risk estimator (AIRE) platform.

METHODS

The AIRE platform was developed in a secondary care dataset (Beth Israel Deaconess Medical Center [BIDMC]) of 1 163 401 ECGs from 189 539 patients with deep learning and a discrete-time survival model to create a patient-specific survival curve with a single ECG. Therefore, AIRE predicts not only risk of mortality, but also time-to-mortality. AIRE was validated in five diverse, transnational cohorts from the USA, Brazil, and the UK (UK Biobank [UKB]), including volunteers, primary care patients, and secondary care patients.

FINDINGS

AIRE accurately predicts risk of all-cause mortality (BIDMC C-index 0·775, 95% CI 0·773-0·776; C-indices on external validation datasets 0·638-0·773), future ventricular arrhythmia (BIDMC C-index 0·760, 95% CI 0·756-0·763; UKB C-index 0·719, 95% CI 0·635-0·803), future atherosclerotic cardiovascular disease (0·696, 0·694-0·698; 0·643, 0·624-0·662), and future heart failure (0·787, 0·785-0·789; 0·768, 0·733-0·802). Through phenome-wide and genome-wide association studies, we identified candidate biological pathways for the prediction of increased risk, including changes in cardiac structure and function, and genes associated with cardiac structure, biological ageing, and metabolic syndrome.

INTERPRETATION

AIRE is an actionable, explainable, and biologically plausible AI-ECG risk estimation platform that has the potential for use worldwide across a wide range of clinical contexts for short-term and long-term risk estimation.

FUNDING

British Heart Foundation, National Institute for Health and Care Research, and Medical Research Council.

A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity

Introduction

We investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications.

Methods

We conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis. We followed up with stratified GWAS analyses by sex and self-reported race.

Results

In ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP rs73407935 (7q11.22) (P = 5.8e-10) with a local replication in ARIC. In black individuals, the variant rs10739419 on chromosome 9 in the Whirlin (WHRN) gene formally replicated (meta-P = 2.2e-9). The SNP-based heritability of HGI was 0.39 (P< 1e-10). HGI had significant sex-specific associations with SNPs in or near GALNT11 in women and HECW2 in men. Finally, in Hispanic participants, we observed genome-wide significant associations with variants near USF1 and NXNL2/SPIN1.

Discussion

Many HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race.

A comprehensive lifestyle index and its associations with DNA methylation and type 2 diabetes among Ghanaian adults: the rodam study

BACKGROUND

A series of modifiable lifestyle factors, such as diet quality, physical activity, alcohol intake, and smoking, may drive the rising burden of type 2 diabetes (T2DM) among sub-Saharan Africans globally. It is unclear whether epigenetic changes play a mediatory role in the associations between these lifestyle factors and T2DM. We assessed the associations between a comprehensive lifestyle index, DNA methylation and T2DM among Ghanaian adults.

METHODS

We used whole-blood Illumina 450 k DNA methylation data from 713 Ghanaians from the Research on Obesity and Diabetes among African Migrants (RODAM) study. We constructed a comprehensive lifestyle index based on established cut-offs for diet quality, physical activity, alcohol intake, and smoking status. In the T2DM-free discovery cohort (n = 457), linear models were fitted to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) associated with the lifestyle index after adjustment for age, sex, body mass index (BMI), and technical covariates. Associations between the identified DMPs and the primary outcome (T2DM), as well as secondary outcomes (fasting blood glucose (FBG) and HbA1c), were determined via logistic and linear regression models, respectively.

RESULTS

In the present study population (mean age: 52 ± 10 years; male: 42.6%), the comprehensive lifestyle index showed a significant association with one DMP annotated to an intergenic region on chromosome 7 (false discovery rate (FDR) = 0.024). Others were annotated to ADCY7, SMARCE1, AHRR, LOXL2, and PTBP1 genes. One DMR was identified and annotated to the GFPT2 gene (familywise error rate (FWER) from bumphunter bootstrap = 0.036). None of the DMPs showed significant associations with T2DM; directions of effect were positive for the DMP in the AHRR and inverse for all the other DMPs. Higher methylation of the ADCY7 DMP was associated with higher FBG (p = 0.024); LOXL2 DMP was associated with lower FBG (p = 0.023) and HbA1c (p = 0.049); and PTBP1 DMP was associated with lower HbA1c (p = 0.002).

CONCLUSIONS

In this explorative epigenome-wide association study among Ghanaians, we identified one DMP and DMR associated with a comprehensive lifestyle index not previously associated with individual lifestyle factors. Based on our findings, we infer that lifestyle factors in combination, affect DNA methylation, thereby influencing the risk of T2DM among Ghanaian adults living in different contexts.

An epigenome-wide association study of waist circumference in Chinese monozygotic twins

OBJECTIVES

Central obesity poses significant health risks because it increases susceptibility to multiple chronic diseases. Epigenetic features such as DNA methylation may be associated with specific obesity traits, which could help us understand how genetic and environmental factors interact to influence the development of obesity. This study aims to identify DNA methylation sites associated with the waist circumference (WC) in Northern Han Chinese population, and to elucidate potential causal relationships.

METHODS

A total of 59 pairs of WC discordant monozygotic twins (ΔWC >0) were selected from the Qingdao Twin Registry in China. Generalized estimated equation model was employed to estimate the methylation levels of CpG sites on WC. Causal relationships between methylation and WC were assessed through the examination of family confounding factors using FAmiliaL CONfounding (ICE FALCON). Additionally, the findings of the epigenome-wide analysis were corroborated in the validation stage.

RESULTS

We identified 26 CpG sites with differential methylation reached false discovery rate (FDR) < 0.05 and 22 differentially methylated regions (slk-corrected p < 0.05) strongly linked to WC. These findings provided annotations for 26 genes, with notable emphasis on MMP17, ITGA11, COL23A1, TFPI, A2ML1-AS1, MRGPRE, C2orf82, and NINJ2. ICE FALCON analysis indicated the DNA methylation of ITGA11 and TFPI had a causal effect on WC and vice versa (p < 0.05). Subsequent validation analysis successfully replicated 10 (p < 0.05) out of the 26 identified sites.

CONCLUSIONS

Our research has ascertained an association between specific epigenetic variations and WC in the Northern Han Chinese population. These DNA methylation features can offer fresh insights into the epigenetic regulation of obesity and WC as well as hints to plausible biological mechanisms.

Genetic determinants of obesity in Korean populations: exploring genome-wide associations and polygenic risk scores

East Asian populations exhibit a genetic predisposition to obesity, yet comprehensive research on these traits is limited. We conducted a genome-wide association study (GWAS) with 93,673 Korean subjects to uncover novel genetic loci linked to obesity, examining metrics such as body mass index, waist circumference, body fat ratio, and abdominal fat ratio. Participants were categorized into non-obese, metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) groups. Using advanced computational methods, we developed a multifaceted polygenic risk scores (PRS) model to predict obesity. Our GWAS identified significant genetic effects with distinct sizes and directions within the MHO and MUO groups compared with the non-obese group. Gene-based and gene-set analyses, along with cluster analysis, revealed heterogeneous patterns of significant genes on chromosomes 3 (MUO group) and 11 (MHO group). In analyses targeting genetic predisposition differences based on metabolic health, odds ratios of high PRS compared with medium PRS showed significant differences between non-obese and MUO, and non-obese and MHO. Similar patterns were seen for low PRS compared with medium PRS. These findings were supported by the estimated genetic correlation (0.89 from bivariate GREML). Regional analyses highlighted significant local genetic correlations on chromosome 11, while single variant approaches suggested widespread pleiotropic effects, especially on chromosome 11. In conclusion, our study identifies specific genetic loci and risks associated with obesity in the Korean population, emphasizing the heterogeneous genetic factors contributing to MHO and MUO.

Comparative analysis of body mass index and obesity-related anthropometric indices for mortality prediction: a study of the Namwon and Dong-gu cohort in Korea

OBJECTIVES

This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices' predictive ability with that of the body mass index (BMI).

METHODS

We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index).

RESULTS

Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant.

CONCLUSIONS

In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease

The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R2 of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.

Cardiorespiratory fitness, body composition, diabetes, and longevity: a two-sample Mendelian randomization study

CONTEXT

Cardiorespiratory fitness, commonly assessed as maximal volume of oxygen consumption (VO2max), has emerged as an important predictor of morbidity and mortality.

OBJECTIVE

We investigated the causality and directionality of the associations of VO2max with body composition, physical activity, diabetes, performance enhancers, and longevity.

METHODS

Using publicly available summary statistics from the largest genome-wide association studies publicly available, we conducted a bidirectional two-sample Mendelian randomization (MR) study. Bidirectional MR tested directionality, and estimated the total causal effects, whereas multivariable MR (MVMR) estimated independent causal effects. Cardiorespiratory fitness (VO2max) was estimated from a submaximal cycle ramp test (N≈90,000) and scaled to total body weight, and in additional analyses to fat-free mass (mL/min/kg).

RESULTS

Genetically predicted higher (per one standard deviation increase) body fat percentage was associated with lower VO2max (β=-0.36 [95% CI: -0.40, -0.32], p=6E-77). Meanwhile, genetically predicted higher appendicular lean mass (0.10 [0.08,0.13] p=3E-16), physical activity (0.29 [0.07,0.52]), and performance enhancers (fasting insulin, hematocrit, and free testosterone in men) were all positively associated with VO2max (p<0.01). Genetic predisposition to diabetes had no effect on VO2max. MVMR showed independent causal effects of body fat percentage, appendicular lean mass, physical activity, and hematocrit on VO2max, as well as of body fat percentage and type 2 diabetes (T2D) on longevity. Genetically predicted VO2max showed no associations.

CONCLUSION

Cardiorespiratory fitness can be improved by favorable body composition, physical activity, and performance enhancers. Despite being a strong predictor of mortality, VO2max is not causally associated with T2D or longevity.

Genome-wide association studies (GWAS) and post-GWAS analyses of impulsivity: A systematic review

Impulsivity is related to a host of mental and behavioral problems. It is a complex construct with many different manifestations, most of which are heritable. The genetic compositions of these impulsivity manifestations, however, remain unclear. A number of genome-wide association studies (GWAS) and post-GWAS analyses have tried to address this issue. We conducted a systematic review of all GWAS and post-GWAS analyses of impulsivity published up to December 2023. Available data suggest that single nucleotide polymorphisms (SNPs) in more than a dozen of genes (e.g., CADM2, CTNNA2, GPM6B) are associated with different measures of impulsivity at genome-wide significant levels. Post-GWAS analyses further show that different measures of impulsivity are subject to different degrees of genetic influence, share few genetic variants, and have divergent genetic overlap with basic personality traits such as extroversion and neuroticism, cognitive ability, psychiatric disorders, substance use, and obesity. These findings shed light on controversies in the conceptualization and measurement of impulsivity, while providing new insights on the underlying mechanisms that yoke impulsivity to psychopathology.

Genomic Insights into Gestational Weight Gain: Uncovering Tissue-Specific Mechanisms and Pathways

Increasing gestational weight gain (GWG) is linked to adverse outcomes in pregnant persons and their children. The Early Growth Genetics (EGG) Consortium identified previously genetic variants that could contribute to early, late, and total GWG from fetal and maternal genomes. However, the biologic mechanisms and tissue-Specificity of these variants in GWG is unknown. We evaluated the association between genetically predicted gene expression in five relevant maternal (subcutaneous and visceral adipose, breast, uterus, and whole blood) from GTEx (v7) and fetal (placenta) tissues and early, late, and total GWG using S-PrediXcan. We tested enrichment of pre-defined biological pathways for nominally (P < 0.05) significant associations using the GENE2FUNC module from Functional Mapping and Annotation of Genome-Wide Association Studies. After multiple testing correction, we did not find significant associations between maternal and fetal gene expression and early, late, or total GWG. There was significant enrichment of several biological pathways, including metabolic processes, secretion, and intracellular transport, among nominally significant genes from the maternal analyses (false discovery rate p-values: 0.016 to 9.37×10). Enriched biological pathways varied across pregnancy. Though additional research is necessary, these results indicate that diverse biological pathways are likely to impact GWG, with their influence varying by tissue and weeks of gestation.

Novel signals and polygenic score for height are associated with pubertal growth traits in Southwestern American Indians

Most genetic variants associated with adult height have been identified through large genome-wide association studies (GWASs) in European-ancestry cohorts. However, it is unclear how these variants influence linear growth during adolescence. This study uses anthropometric and genotypic data from a longitudinal study conducted in an American Indian community in Arizona between 1965-2007. Growth parameters (i.e. height, velocity, and timing of growth spurt) were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, in 787 participants with height measurements spanning the whole period of growth. Heritability estimates suggested that genetic factors could explain 25% to 71% of the variance of pubertal growth traits. We performed a GWAS of growth parameters, testing their associations with 5 077 595 imputed or directly genotyped variants. Six variants associated with height at peak velocity (P < 5 × 10-8, adjusted for sex, birth year and principal components). Implicated genes include NUDT3, previously associated with adult height, and PACSIN1. Two novel variants associated with duration of growth spurt (P < 5 × 10-8) in LOC105375344, an uncharacterized gene with unknown function. We finally examined the association of growth parameters with a polygenic score for height derived from 9557 single nucleotide polymorphisms (SNPs) identified in the GIANT meta-analysis for which genotypic data were available for the American Indian study population. Height polygenic score was correlated with the magnitude and velocity of height growth that occurred before and at the peak of the adolescent growth spurt, indicating overlapping genetic architecture, with no influence on the timing of adolescent growth.

Allometric versus traditional body-shape indices and risk of colorectal cancer: a Mendelian randomization analysis

BACKGROUND

Traditional body-shape indices such as Waist Circumference (WC), Hip Circumference (HC), and Waist-to-Hip Ratio (WHR) are associated with colorectal cancer (CRC) risk, but are correlated with Body Mass Index (BMI), and adjustment for BMI introduces a strong correlation with height. Thus, new allometric indices have been developed, namely A Body Shape Index (ABSI), Hip Index (HI), and Waist-to-Hip Index (WHI), which are uncorrelated with weight and height; these have also been associated with CRC risk in observational studies, but information from Mendelian randomization (MR) studies is missing.

METHODS

We used two-sample MR to examine potential causal cancer site- and sex-specific associations of the genetically-predicted allometric body-shape indices with CRC risk, and compared them with BMI-adjusted traditional body-shape indices, and BMI. Data were obtained from UK Biobank and the GIANT consortium, and from GECCO, CORECT and CCFR consortia.

RESULTS

WHI was positively associated with CRC in men (OR per SD: 1.20, 95% CI: 1.03-1.39) and in women (1.15, 1.06-1.24), and similarly for colon and rectal cancer. ABSI was positively associated with colon and rectal cancer in men (1.27, 1.03-1.57; and 1.40, 1.10-1.77, respectively), and with colon cancer in women (1.20, 1.07-1.35). There was little evidence for association between HI and colon or rectal cancer. The BMI-adjusted WHR and HC showed similar associations to WHI and HI, whereas WC showed similar associations to ABSI only in women.

CONCLUSIONS

This large MR study provides strong evidence for a potential causal positive association of the allometric indices ABSI and WHI with CRC in both sexes, thus establishing the association between abdominal fat and CRC without the limitations of the traditional waist size indices and independently of BMI. Among the BMI-adjusted traditional indices, WHR and HC provided equivalent associations with WHI and HI, while differences were observed between WC and ABSI.

Tissue-specific genetic variation suggests distinct molecular pathways between body shape phenotypes and colorectal cancer

It remains unknown whether adiposity subtypes are differentially associated with colorectal cancer (CRC). To move beyond single-trait anthropometric indicators, we derived four multi-trait body shape phenotypes reflecting adiposity subtypes from principal components analysis on body mass index, height, weight, waist-to-hip ratio, and waist and hip circumference. A generally obese (PC1) and a tall, centrally obese (PC3) body shape were both positively associated with CRC risk in observational analyses in 329,828 UK Biobank participants (3728 cases). In genome-wide association studies in 460,198 UK Biobank participants, we identified 3414 genetic variants across four body shapes and Mendelian randomization analyses confirmed positive associations of PC1 and PC3 with CRC risk (52,775 cases/45,940 controls from GECCO/CORECT/CCFR). Brain tissue-specific genetic instruments, mapped to PC1 through enrichment analysis, were responsible for the relationship between PC1 and CRC, while the relationship between PC3 and CRC was predominantly driven by adipose tissue-specific genetic instruments. This study suggests distinct putative causal pathways between adiposity subtypes and CRC.

Obesity-Dependent Association of the rs10454142 PPP1R21 with Breast Cancer

The purpose of this work was to find a link between the breast cancer (BC)-risk effects of sex hormone-binding globulin (SHBG)-associated polymorphisms and obesity. The study was conducted on a sample of 1498 women (358 BC; 1140 controls) who, depending on the presence/absence of obesity, were divided into two groups: obese (119 BC; 253 controls) and non-obese (239 BC; 887 controls). Genotyping of nine SHBG-associated single nucleotide polymorphisms (SNP)-rs17496332 PRMT6, rs780093 GCKR, rs10454142 PPP1R21, rs3779195 BAIAP2L1, rs440837 ZBTB10, rs7910927 JMJD1C, rs4149056 SLCO1B1, rs8023580 NR2F2, and rs12150660 SHBG-was executed, and the BC-risk impact of these loci was analyzed by logistic regression separately in each group of obese/non-obese women. We found that the BC-risk effect correlated by GWAS with the SHBG-level polymorphism rs10454142 PPP1R21 depends on the presence/absence of obesity. The SHBG-lowering allele C rs10454142 PPP1R21 has a risk value for BC in obese women (allelic model: CvsT, OR = 1.52, 95%CI = 1.10-2.11, and pperm = 0.013; additive model: CCvsTCvsTT, OR = 1.71, 95%CI = 1.15-2.62, and pperm = 0.011; dominant model: CC + TCvsTT, OR = 1.95, 95%CI = 1.13-3.37, and pperm = 0.017) and is not associated with the disease in women without obesity. SNP rs10454142 PPP1R21 and 10 proxy SNPs have adipose-specific regulatory effects (epigenetic modifications of promoters/enhancers, DNA interaction with 51 transcription factors, eQTL/sQTL effects on five genes (PPP1R21, RP11-460M2.1, GTF2A1L, STON1-GTF2A1L, and STON1), etc.), can be "likely cancer driver" SNPs, and are involved in cancer-significant pathways. In conclusion, our study detected an obesity-dependent association of the rs10454142 PPP1R21 with BC in women.

Identifying BMI-associated genes via a genome-wide multi-omics integrative approach using summary data

OBJECTIVE

This study aims to identify BMI-associated genes by integrating aggregated summary information from different omics data.

METHODS

We conducted a meta-analysis to leverage information from a genome-wide association study (n = 339 224), a transcriptome-wide association study (n = 5619), and an epigenome-wide association study (n = 3743). We prioritized the significant genes with a machine learning-based method, netWAS, which borrows information from adipose tissue-specific interaction networks. We also used the brain-specific network in netWAS to investigate genes potentially involved in brain-adipose interaction.

RESULTS

We identified 195 genes that were significantly associated with BMI through meta-analysis. The netWAS analysis narrowed down the list to 21 genes in adipose tissue. Among these 21 genes, six genes, including FUS, STX4, CCNT2, FUBP1, NDUFS3, and RAPSN, were not reported to be BMI-associated in PubMed or GWAS Catalog. We also identified 11 genes that were significantly associated with BMI in both adipose and whole brain tissues.

CONCLUSION

This study integrated three types of omics data and identified a group of genes that have not previously been reported to be associated with BMI. This strategy could provide new insights for future studies to identify molecular mechanisms contributing to BMI regulation.

SMYD3: a new regulator of adipocyte precursor proliferation at the early steps of differentiation

BACKGROUND

In obesity, adipose tissue undergoes a remodeling process characterized by increased adipocyte size (hypertrophia) and number (hyperplasia). The ability to tip the balance toward the hyperplastic growth, with recruitment of new fat cells through adipogenesis, seems to be critical for a healthy adipose tissue expansion, as opposed to a hypertrophic growth that is accompanied by the development of inflammation and metabolic dysfunction. However, the molecular mechanisms underlying the fine-tuned regulation of adipose tissue expansion are far from being understood.

METHODS

We analyzed by mass spectrometry-based proteomics visceral white adipose tissue (vWAT) samples collected from C57BL6 mice fed with a HFD for 8 weeks. A subset of these mice, called low inflammation (Low-INFL), showed reduced adipose tissue inflammation, as opposed to those developing the expected inflammatory response (Hi-INFL). We identified the discriminants between Low-INFL and Hi-INFL vWAT samples and explored their function in Adipose-Derived human Mesenchymal Stem Cells (AD-hMSCs) differentiated to adipocytes.

RESULTS

vWAT proteomics allowed us to quantify 6051 proteins. Among the candidates that most differentiate Low-INFL from Hi-INFL vWAT, we found proteins involved in adipocyte function, including adiponectin and hormone sensitive lipase, suggesting that adipocyte differentiation is enhanced in Low-INFL, as compared to Hi-INFL. The chromatin modifier SET and MYND Domain Containing 3 (SMYD3), whose function in adipose tissue was so far unknown, was another top-scored hit. SMYD3 expression was significantly higher in Low-INFL vWAT, as confirmed by western blot analysis. Using AD-hMSCs in culture, we found that SMYD3 mRNA and protein levels decrease rapidly during the adipocyte differentiation. Moreover, SMYD3 knock-down before adipocyte differentiation resulted in reduced H3K4me3 and decreased cell proliferation, thus limiting the number of cells available for adipogenesis.

CONCLUSIONS

Our study describes an important role of SMYD3 as a newly discovered regulator of adipocyte precursor proliferation during the early steps of adipogenesis.

Polymorphism rs143384 GDF5 reduces the risk of knee osteoarthritis development in obese individuals and increases the disease risk in non-obese population

BACKGROUND

We investigated the effect of obesity on the association of genome-wide associative studies (GWAS)-significant genes with the risk of knee osteoarthritis (KOA).

METHODS

All study participants (n = 1,100) were divided into 2 groups in terms of body mass index (BMI): BMI ≥ 30 (255 KOA patients and 167 controls) and BMI < 30 (245 KOA and 433 controls). The eight GWAS-significant KOA single nucleotide polymorphisms (SNP) of six candidate genes, such as LYPLAL1 (rs2820436, rs2820443), SBNO1 (rs1060105, rs56116847), WWP2 (rs34195470), NFAT5 (rs6499244), TGFA (rs3771501), GDF5 (rs143384), were genotyped. Logistic regression analysis (gPLINK online program) was used for SNPs associations study with the risk of developing KOA into 2 groups (BMI ≥ 30 and BMI < 30) separately. The functional effects of KOA risk loci were evaluated using in silico bioinformatic analysis.

RESULTS

Multidirectional relationships of the rs143384 GDF5 with KOA in BMI-different groups were found: This SNP was KOA protective locus among individuals with BMI ≥ 30 (OR 0.41 [95%CI 0.20-0.94] recessive model) and was disorder risk locus among individuals with BMI < 30 (OR 1.32 [95%CI 1.05-1.65] allele model, OR 1.44 [95%CI 1.10-1.86] additive model, OR 1.67 [95%CI 1.10-2.52] dominant model). Polymorphism rs143384 GDF5 manifested its regulatory effects in relation to nine genes (GDF5, CPNE1, EDEM2, ERGIC3, GDF5OS, PROCR, RBM39, RPL36P4, UQCC1) in adipose tissue, which were involved in the regulation of pathways of apoptosis of striated muscle cells.

CONCLUSIONS

In summary, the effect of obesity on the association of the rs143384 GDF5 with KOA was shown: the "protective" value of this polymorphism in the BMI ≥ 30 group and the "risk" meaning in BMI < 30 cohort.

Links between the genetic determinants of morning plasma cortisol and body shape: a two-sample Mendelian randomisation study

High cortisol production in Cushing's syndrome leads to fat centralisation. The influence of modest cortisol variations on body shape, however, is less clear. We examined potentially causal associations between morning plasma cortisol and body shape and obesity with inverse-variance weighted random-effects models in a two-sample Mendelian randomisation analysis. We used publicly available summary statistics from the CORtisol NETwork (CORNET) consortium, UK Biobank, and the Genetic Investigation of Anthropometric Traits (GIANT) consortium. Only in women, morning plasma cortisol (proxied by ten genetic polymorphisms) was associated positively with waist size reflected in waist-to-hip index (WHI, 0.035 standard deviation (SD) units change per one SD cortisol increase; 95% confidence interval (0.002-0.067); p = 0.036) and "a body shape index" (ABSI; 0.039 (0.006-0.071); p = 0.021). There was no evidence for associations with hip index (HI) or body mass index (BMI). Among individual polymorphisms, rs7450600 stood out (chromosome 6; Long Intergenic Non-Protein-Coding RNA 473 gene, LINC00473). Morning plasma cortisol proxied by rs7450600 was associated positively with WHI and inversely with HI and BMI in women and men. Our findings support a causal association of higher morning plasma cortisol with larger waist size in women and highlight LINC00473 as a genetic link between morning plasma cortisol and body shape.

Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci

Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes.

Uncovering myocardial infarction genetic signatures using GWAS exploration in Saudi and European cohorts

Genome-wide association studies (GWAS) have yielded significant insights into the genetic architecture of myocardial infarction (MI), although studies in non-European populations are still lacking. Saudi Arabian cohorts offer an opportunity to discover novel genetic variants impacting disease risk due to a high rate of consanguinity. Genome-wide genotyping (GWG), imputation and GWAS followed by meta-analysis were performed based on two independent Saudi Arabian studies comprising 3950 MI patients and 2324 non-MI controls. Meta-analyses were then performed with these two Saudi MI studies and the CardioGRAMplusC4D and UK BioBank GWAS as controls. Meta-analyses of the two Saudi MI studies resulted in 17 SNPs with genome-wide significance. Meta-analyses of all 4 studies revealed 66 loci with genome-wide significance levels of p < 5 × 10-8. All of these variants, except rs2764203, have previously been reported as MI-associated loci or to have high linkage disequilibrium with known loci. One SNP association in Shisa family member 5 (SHISA5) (rs11707229) was evident at a much higher frequency in the Saudi MI populations (> 12% MAF). In conclusion, our results replicated many MI associations, whereas in Saudi-only GWAS (meta-analyses), several new loci were implicated that require future validation and functional analyses.

Association of ESR1 germline variants with TP53 somatic variants in breast tumors in a genome-wide study

Background

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. HER2 positive and triple negative breast cancers (TNBC) have a higher frequency of TP53 somatic mutations than other subtypes. PIK3CA mutations are more frequently observed in hormone receptor positive tumors. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors.

Methods

A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC.

Results

The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons.

Conclusions

We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.

Genome-wide Association Analysis of Schizophrenia and Vitamin D Levels Shows Shared Genetic Architecture and Identifies Novel Risk Loci

Low vitamin D (vitD) levels have been consistently reported in schizophrenia (SCZ) suggesting a role in the etiopathology. However, little is known about the role of underlying shared genetic mechanisms. We applied a conditional/conjunctional false discovery rate approach (FDR) on large, nonoverlapping genome-wide association studies for SCZ (N cases = 53 386, N controls = 77 258) and vitD serum concentration (N = 417 580) to evaluate shared common genetic variants. The identified genomic loci were characterized using functional analyses and biological repositories. We observed cross-trait SNP enrichment in SCZ conditioned on vitD and vice versa, demonstrating shared genetic architecture. Applying the conjunctional FDR approach, we identified 72 loci jointly associated with SCZ and vitD at conjunctional FDR < 0.05. Among the 72 shared loci, 40 loci have not previously been reported for vitD, and 9 were novel for SCZ. Further, 64% had discordant effects on SCZ-risk and vitD levels. A mixture of shared variants with concordant and discordant effects with a predominance of discordant effects was in line with weak negative genetic correlation (rg = -0.085). Our results displayed shared genetic architecture between SCZ and vitD with mixed effect directions, suggesting overlapping biological pathways. Shared genetic variants with complex overlapping mechanisms may contribute to the coexistence of SCZ and vitD deficiency and influence the clinical picture.

Multi-view information fusion using multi-view variational autoencoder to predict proximal femoral fracture load

Background

Hip fracture occurs when an applied force exceeds the force that the proximal femur can support (the fracture load or "strength") and can have devastating consequences with poor functional outcomes. Proximal femoral strengths for specific loading conditions can be computed by subject-specific finite element analysis (FEA) using quantitative computerized tomography (QCT) images. However, the radiation and availability of QCT limit its clinical usability. Alternative low-dose and widely available measurements, such as dual energy X-ray absorptiometry (DXA) and genetic factors, would be preferable for bone strength assessment. The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion.

Results

We developed new models using multi-view variational autoencoder (MVAE) for feature representation learning and a product of expert (PoE) model for multi-view information fusion. We applied the proposed models to an in-house Louisiana Osteoporosis Study (LOS) cohort with 931 male subjects, including 345 African Americans and 586 Caucasians. We performed genome-wide association studies (GWAS) to select 256 genetic variants with the lowest p-values for each proximal femoral strength and integrated whole genome sequence (WGS) features and DXA-derived imaging features to predict proximal femoral strength. The best prediction model for fall fracture load was acquired by integrating WGS features and DXA-derived imaging features. The designed models achieved the mean absolute percentage error of 18.04%, 6.84% and 7.95% for predicting proximal femoral fracture loads using linear models of fall loading, nonlinear models of fall loading, and nonlinear models of stance loading, respectively.

Conclusion

The proposed models are capable of predicting proximal femoral strength using WGS features and DXA-derived imaging features. Though this tool is not a substitute for predicting FEA using QCT images, it would make improved assessment of hip fracture risk more widely available while avoiding the increased radiation exposure from QCT.

Overall Obesity Not Abdominal Obesity Has a Causal Relationship with Obstructive Sleep Apnea in Individual Level Data

Objective

Both obstructive sleep apnea (OSA) and obesity are highly prevalent worldwide, and are intrinsically linked. Previous studies showed that obesity is one of the major risk factors for OSA, but the causality of the relationship is still unclear. The study was to investigate the causal relationships of overall obesity and abdominal obesity with OSA and its quantitative traits.

Methods

In this case-control study, a total of 7134 participants, including 4335 moderate-to-severe OSA diagnosed by standard polysomnography and 2799 community-based controls were enrolled. Anthropometric and biochemical data were collected. Mendelian randomization (MR) analyses were performed using the genetic risk score, based on 29 body mass index (BMI)- and 11 waist-hip-ratio (WHR)-associated single nucleotide polymorphisms as instrumental variables. The causal associations of these genetic scores with OSA and its quantitative phenotypes were analyzed.

Results

Obesity was strongly correlated with OSA in observational analysis (β= 0.055, P = 3.7 × 10-5). In MR analysis, each increase by one standard deviation in BMI was associated with increased OSA risk [odds ratio (OR): 2.21, 95% confidence interval (CI): 1.62-3.02, P = 5.57 × 10-7] and with 2.72-, 4.68-, and 3.25-fold increases in AHI, ODI, and MAI, respectively (all P < 0.05) in men. However, no causal associations were found between WHR and OSA risk or OSA quantitative traits in men and women.

Conclusion

Compared to abdominal obesity, overall obesity showed a causal relationship with OSA and its quantitative traits, especially in men.

The Physiological and Pathological Role of Acyl-CoA Oxidation

Fatty acid metabolism, including β-oxidation (βOX), plays an important role in human physiology and pathology. βOX is an essential process in the energy metabolism of most human cells. Moreover, βOX is also the source of acetyl-CoA, the substrate for (a) ketone bodies synthesis, (b) cholesterol synthesis, (c) phase II detoxication, (d) protein acetylation, and (d) the synthesis of many other compounds, including N-acetylglutamate-an important regulator of urea synthesis. This review describes the current knowledge on the importance of the mitochondrial and peroxisomal βOX in various organs, including the liver, heart, kidney, lung, gastrointestinal tract, peripheral white blood cells, and other cells. In addition, the diseases associated with a disturbance of fatty acid oxidation (FAO) in the liver, heart, kidney, lung, alimentary tract, and other organs or cells are presented. Special attention was paid to abnormalities of FAO in cancer cells and the diseases caused by mutations in gene-encoding enzymes involved in FAO. Finally, issues related to α- and ω- fatty acid oxidation are discussed.

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

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

The complete and fully-phased diploid genome of a male Han Chinese

Since the release of the complete human genome, the priority of human genomic study has now been shifting towards closing gaps in ethnic diversity. Here, we present a fully phased and well-annotated diploid human genome from a Han Chinese male individual (CN1), in which the assemblies of both haploids achieve the telomere-to-telomere (T2T) level. Comparison of this diploid genome with the CHM13 haploid T2T genome revealed significant variations in the centromere. Outside the centromere, we discovered 11,413 structural variations, including numerous novel ones. We also detected thousands of CN1 alleles that have accumulated high substitution rates and a few that have been under positive selection in the East Asian population. Further, we found that CN1 outperforms CHM13 as a reference genome in mapping and variant calling for the East Asian population owing to the distinct structural variants of the two references. Comparison of SNP calling for a large cohort of 8869 Chinese genomes using CN1 and CHM13 as reference respectively showed that the reference bias profoundly impacts rare SNP calling, with nearly 2 million rare SNPs miss-called with different reference genomes. Finally, applying the CN1 as a reference, we discovered 5.80 Mb and 4.21 Mb putative introgression sequences from Neanderthal and Denisovan, respectively, including many East Asian specific ones undetected using CHM13 as the reference. Our analyses reveal the advances of using CN1 as a reference for population genomic studies and paleo-genomic studies. This complete genome will serve as an alternative reference for future genomic studies on the East Asian population.

Glucocorticoid Receptor Gene (NR3C1) Polymorphisms and Metabolic Syndrome: Insights from the Mennonite Population

The regulation of the hypothalamic-pituitary-adrenal (HPA) axis is associated with polymorphisms and the methylation degree of the glucocorticoid receptor gene (NR3C1) and is potentially involved in the development of metabolic syndrome (MetS). In order to evaluate the association between MetS with the polymorphisms, methylation, and gene expression of the NR3C1 in the genetically isolated Brazilian Mennonite population, we genotyped 20 NR3C1 polymorphisms in 74 affected (MetS) and 138 unaffected individuals without affected first-degree relatives (Co), using exome sequencing, as well as five variants from non-exonic regions, in 70 MetS and 166 Co, using mass spectrometry. The methylation levels of 11 1F CpG sites were quantified using pyrosequencing (66 MetS and 141 Co), and the NR3C1 expression was evaluated via RT-qPCR (14 MetS and 25 Co). Age, physical activity, and family environment during childhood were associated with MetS. Susceptibility to MetS, independent of these factors, was associated with homozygosity for rs10482605*C (OR = 4.74, pcorr = 0.024) and the haplotype containing TTCGTTGATT (rs3806855*T_ rs3806854*T_rs10482605*C_rs10482614*G_rs6188*T_rs258813*T_rs33944801*G_rs34176759*A_rs17209258*T_rs6196*T, OR = 4.74, pcorr = 0.048), as well as for the CCT haplotype (rs41423247*C_ rs6877893*C_rs258763*T), OR = 6.02, pcorr = 0.030), but not to the differences in methylation or gene expression. Thus, NR3C1 polymorphisms seem to modulate the susceptibility to MetS in Mennonites, independently of lifestyle and early childhood events, and their role seems to be unrelated to DNA methylation and gene expression.

Multi-trait discovery and fine-mapping of lipid loci in 125,000 individuals of African ancestry

Most genome-wide association studies (GWAS) for lipid traits focus on the separate analysis of lipid traits. Moreover, there are limited GWASs evaluating the genetic variants associated with multiple lipid traits in African ancestry. To further identify and localize loci with pleiotropic effects on lipid traits, we conducted a genome-wide meta-analysis, multi-trait analysis of GWAS (MTAG), and multi-trait fine-mapping (flashfm) in 125,000 individuals of African ancestry. Our meta-analysis and MTAG identified four and 14 novel loci associated with lipid traits, respectively. flashfm yielded an 18% mean reduction in the 99% credible set size compared to single-trait fine-mapping with JAM. Moreover, we identified more genetic variants with a posterior probability of causality >0.9 with flashfm than with JAM. In conclusion, we identified additional novel loci associated with lipid traits, and flashfm reduced the 99% credible set size to identify causal genetic variants associated with multiple lipid traits in African ancestry.

Maternal pre-pregnancy BMI, offspring epigenome-wide DNA methylation, and childhood obesity: findings from the Boston Birth Cohort

BACKGROUND

Maternal pre-pregnancy obesity is an established risk factor for childhood obesity. Investigating epigenetic alterations induced by maternal obesity during fetal development could gain mechanistic insight into the developmental origins of childhood obesity. While obesity disproportionately affects underrepresented racial and ethnic mothers and children in the USA, few studies investigated the role of prenatal epigenetic programming in intergenerational obesity of these high-risk populations.

METHODS

This study included 903 mother-child pairs from the Boston Birth Cohort, a predominantly urban, low-income minority birth cohort. Mother-infant dyads were enrolled at birth and the children were followed prospectively to age 18 years. Infinium Methylation EPIC BeadChip was used to measure epigenome-wide methylation level of cord blood. We performed an epigenome-wide association study of maternal pre-pregnancy body mass index (BMI) and cord blood DNA methylation (DNAm). To quantify the degree to which cord blood DNAm mediates the maternal BMI-childhood obesity, we further investigated whether maternal BMI-associated DNAm sites impact birthweight or childhood overweight or obesity (OWO) from age 1 to age 18 and performed corresponding mediation analyses.

RESULTS

The study sample contained 52.8% maternal pre-pregnancy OWO and 63.2% offspring OWO at age 1-18 years. Maternal BMI was associated with cord blood DNAm at 8 CpG sites (genome-wide false discovery rate [FDR] < 0.05). After accounting for the possible interplay of maternal BMI and smoking, 481 CpG sites were discovered for association with maternal BMI. Among them 123 CpGs were associated with childhood OWO, ranging from 42% decrease to 87% increase in OWO risk for each SD increase in DNAm. A total of 14 identified CpG sites showed a significant mediation effect on the maternal BMI-child OWO association (FDR < 0.05), with mediating proportion ranging from 3.99% to 25.21%. Several of these 14 CpGs were mapped to genes in association with energy balance and metabolism (AKAP7) and adulthood metabolic syndrome (CAMK2B).

CONCLUSIONS

This prospective birth cohort study in a high-risk yet understudied US population found that maternal pre-pregnancy OWO significantly altered DNAm in newborn cord blood and provided suggestive evidence of epigenetic involvement in the intergenerational risk of obesity.

Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study

DNA methylation studies of incident type 2 diabetes in US populations are limited, and to our knowledge none included individuals of African descent living in the US. We performed an epigenome-wide association analysis of blood-based methylation levels at CpG sites with incident type 2 diabetes using Cox regression in 2,091 Black and 1,029 White individuals from the Atherosclerosis Risk in Communities study. At an epigenome-wide significance threshold of 10-7, we detected 7 novel diabetes-associated CpG sites in C1orf151 (cg05380846: HR= 0.89, p = 8.4 × 10-12), ZNF2 (cg01585592: HR= 0.88, p = 1.6 × 10-9), JPH3 (cg16696007: HR= 0.87, p = 7.8 × 10-9), GPX6 (cg02793507: HR= 0.85, p = 2.7 × 10-8 and cg00647063: HR= 1.20, p = 2.5 × 10-8), chr17q25 (cg16865890: HR= 0.8, p = 6.9 × 10-8), and chr11p15 (cg13738793: HR= 1.11, p = 7.7 × 10-8). The CpG sites at C1orf151, ZNF2, JPH3 and GPX6, were identified in Black adults, chr17q25 was identified in White adults, and chr11p15 was identified upon meta-analyzing the two groups. The CpG sites at JPH3 and GPX6 were likely associated with incident type 2 diabetes independent of BMI. All the CpG sites, except at JPH3, were likely consequences of elevated glucose at baseline. We additionally replicated known type 2 diabetes-associated CpG sites including cg19693031 at TXNIP, cg00574958 at CPT1A, cg16567056 at PLBC2, cg11024682 at SREBF1, cg08857797 at VPS25, and cg06500161 at ABCG1, 3 of which were replicated in Black adults at the epigenome-wide threshold. We observed modest increase in type 2 diabetes variance explained upon addition of the significantly associated CpG sites to a Cox model that included traditional type 2 diabetes risk factors and fasting glucose (increase from 26.2% to 30.5% in Black adults; increase from 36.9% to 39.4% in White adults). We examined if groups of proximal CpG sites were associated with incident type 2 diabetes using a gene-region specific and a gene-region agnostic differentially methylated region (DMR) analysis. Our DMR analyses revealed several clusters of significant CpG sites, including a DMR consisting of a previously discovered CpG site at ADCY7 and promoter regions of TP63 which were differentially methylated across all race groups. This study illustrates improved discovery of CpG sites/regions by leveraging both individual CpG site and DMR analyses in an unexplored population. Our findings include genes linked to diabetes in experimental studies (e.g., GPX6, JPH3, and TP63), and future gene-specific methylation studies could elucidate the link between genes, environment, and methylation in the pathogenesis of type 2 diabetes.

Using the collaborative cross to identify the role of host genetics in defining the murine gut microbiome

BACKGROUND

The human gut microbiota is a complex community comprised of trillions of bacteria and is critical for the digestion and absorption of nutrients. Bacterial communities of the intestinal microbiota influence the development of several conditions and diseases. We studied the effect of host genetics on gut microbial composition using Collaborative Cross (CC) mice. CC mice are a panel of mice that are genetically diverse across strains, but genetically identical within a given strain allowing repetition and deeper analysis than is possible with other collections of genetically diverse mice.

RESULTS

16S rRNA from the feces of 167 mice from 28 different CC strains was sequenced and analyzed using the Qiime2 pipeline. We observed a large variance in the bacterial composition across CC strains starting at the phylum level. Using bacterial composition data, we identified 17 significant Quantitative Trait Loci (QTL) linked to 14 genera on 9 different mouse chromosomes. Genes within these intervals were analyzed for significant association with pathways and the previously known human GWAS database using Enrichr analysis and Genecards database. Multiple host genes involved in obesity, glucose homeostasis, immunity, neurological diseases, and many other protein-coding genes located in these regions may play roles in determining the composition of the gut microbiota. A subset of these CC mice was infected with Salmonella Typhimurium. Using infection outcome data, an increase in abundance of genus Lachnospiraceae and decrease in genus Parasutterella correlated with positive health outcomes after infection. Machine learning classifiers accurately predicted the CC strain and the infection outcome using pre-infection bacterial composition data from the feces.

CONCLUSION

Our study supports the hypothesis that multiple host genes influence the gut microbiome composition and homeostasis, and that certain organisms may influence health outcomes after S. Typhimurium infection. Video Abstract.

Maternal Age at Menarche Gene Polymorphisms Are Associated with Offspring Birth Weight

In this study, the association between maternal age at menarche (AAM)-related polymorphisms and offspring birth weight (BW) was studied. The work was performed on a sample of 716 pregnant women and their newborns. All pregnant women underwent genotyping of 50 SNPs of AAM candidate genes. Regression methods (linear and Model-Based Multifactor Dimensionality Reduction (MB-MDR)) with permutation procedures (the indicator p_perm was calculated) were used to identify the correlation between SNPs and newborn weight (transformed BW values were analyzed) and in silico bioinformatic examination was applied to assess the intended functionality of BW-associated loci. Four AAM-related genetic variants were BW-associated including genes such as POMC (rs7589318) (β_additive = 0.202/p_perm = 0.015), KDM3B (rs757647) (β_recessive = 0.323/p_perm = 0.005), INHBA (rs1079866) (β_additive = 0.110/p_perm = 0.014) and NKX2-1 (rs999460) (β_recessive = -0.176/p_perm = 0.015). Ten BW-significant models of interSNPs interactions (p_perm ≤ 0.001) were identified for 20 polymorphisms. SNPs rs7538038 KISS1, rs713586 RBJ, rs12324955 FTO and rs713586 RBJ-rs12324955 FTO two-locus interaction were included in the largest number of BW-associated models (30% models each). BW-associated AAM-linked 22 SNPs and 350 proxy loci were functionally related to 49 genes relevant to pathways such as the hormone biosynthesis/process and female/male gonad development. In conclusion, maternal AMM-related genes polymorphism is associated with the offspring BW.

Variants in JAZF1 are associated with asthma, type 2 diabetes, and height in the United Kingdom biobank population

Background: Asthma, type 2 diabetes (T2D), and anthropometric measures are correlated complex traits that all have a major genetic component. Objective: To investigate the overlap in genetic variants associated with these complex traits. Methods: Using United Kingdom Biobank data, we performed univariate association analysis, fine-mapping, and mediation analysis to identify and dissect shared genomic regions associated with asthma, T2D, height, weight, body mass index (BMI), and waist circumference (WC). Results: We found several genome-wide significant variants in and around the JAZF1 gene that are associated with asthma, T2D, or height with two of these variants shared by the three phenotypes. We also observed an association in this region with WC when adjusted for BMI. However, there was no association with WC when it was not adjusted for BMI or weight. Additionally, only suggestive associations between variants in this region and BMI were observed. Fine-mapping analyses suggested that within JAZF1 there are non-overlapping regions harboring causal susceptibility variants for asthma, T2D, and height. Mediation analyses supported the conclusion that these are independent associations. Conclusion: Our findings indicate that variants in the JAZF1 are associated with asthma, T2D, and height, but the associated causal variant(s) are different for each of the three phenotypes.

CADM2 is implicated in impulsive personality and numerous other traits by genome- and phenome-wide association studies in humans and mice

Impulsivity is a multidimensional heritable phenotype that broadly refers to the tendency to act prematurely and is associated with multiple forms of psychopathology, including substance use disorders. We performed genome-wide association studies (GWAS) of eight impulsive personality traits from the Barratt Impulsiveness Scale and the short UPPS-P Impulsive Personality Scale (N = 123,509-133,517 23andMe research participants of European ancestry), and a measure of Drug Experimentation (N = 130,684). Because these GWAS implicated the gene CADM2, we next performed single-SNP phenome-wide studies (PheWAS) of several of the implicated variants in CADM2 in a multi-ancestral 23andMe cohort (N = 3,229,317, European; N = 579,623, Latin American; N = 199,663, African American). Finally, we produced Cadm2 mutant mice and used them to perform a Mouse-PheWAS ("MouseWAS") by testing them with a battery of relevant behavioral tasks. In humans, impulsive personality traits showed modest chip-heritability (~6-11%), and moderate genetic correlations (rg = 0.20-0.50) with other personality traits, and various psychiatric and medical traits. We identified significant associations proximal to genes such as TCF4 and PTPRF, and also identified nominal associations proximal to DRD2 and CRHR1. PheWAS for CADM2 variants identified associations with 378 traits in European participants, and 47 traits in Latin American participants, replicating associations with risky behaviors, cognition and BMI, and revealing novel associations including allergies, anxiety, irritable bowel syndrome, and migraine. Our MouseWAS recapitulated some of the associations found in humans, including impulsivity, cognition, and BMI. Our results further delineate the role of CADM2 in impulsivity and numerous other psychiatric and somatic traits across ancestries and species.

Comparison of intergenerational instrumental variable analyses of body mass index and mortality in UK Biobank

BACKGROUND

An increasing proportion of people have a body mass index (BMI) classified as overweight or obese and published studies disagree whether this will be beneficial or detrimental to health. We applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality in a cohort with many deaths: the parents of UK Biobank participants.

METHODS

In Cox regression models, parental BMI was instrumented by offspring BMI using an 'offspring as instrument' (OAI) estimation and by offspring BMI-related genetic variants in a 'proxy-genotype Mendelian randomization' (PGMR) estimation.

RESULTS

Complete-case analyses were performed in parents of 233 361 UK Biobank participants with full phenotypic, genotypic and covariate data. The PGMR method suggested that higher BMI increased mortality with hazard ratios per kg/m2 of 1.02 (95% CI: 1.01, 1.04) for mothers and 1.04 (95% CI: 1.02, 1.05) for fathers. The OAI method gave considerably higher estimates, which varied according to the parent-offspring pairing between 1.08 (95% CI: 1.06, 1.10; mother-son) and 1.23 (95% CI: 1.16, 1.29; father-daughter).

CONCLUSION

Both methods supported a causal role of higher BMI increasing mortality, although caution is required regarding the immediate causal interpretation of these exact values. Evidence of instrument invalidity from measured covariates was limited for the OAI method and minimal for the PGMR method. The methods are complementary for interrogating the average putative causal effects because the biases are expected to differ between them.

StocSum: stochastic summary statistics for whole genome sequencing studies

Genomic summary statistics, usually defined as single-variant test results from genome-wide association studies, have been widely used to advance the genetics field in a wide range of applications. Applications that involve multiple genetic variants also require their correlations or linkage disequilibrium (LD) information, often obtained from an external reference panel. In practice, it is usually difficult to find suitable external reference panels that represent the LD structure for underrepresented and admixed populations, or rare genetic variants from whole genome sequencing (WGS) studies, limiting the scope of applications for genomic summary statistics. Here we introduce StocSum, a novel reference-panel-free statistical framework for generating, managing, and analyzing stochastic summary statistics using random vectors. We develop various downstream applications using StocSum including single-variant tests, conditional association tests, gene-environment interaction tests, variant set tests, as well as meta-analysis and LD score regression tools. We demonstrate the accuracy and computational efficiency of StocSum using two cohorts from the Trans-Omics for Precision Medicine Program. StocSum will facilitate sharing and utilization of genomic summary statistics from WGS studies, especially for underrepresented and admixed populations.

Genome-wide association study of population-standardised cognitive performance phenotypes in a rural South African community

Cognitive function is an indicator for global physical and mental health, and cognitive impairment has been associated with poorer life outcomes and earlier mortality. A standard cognition test, adapted to a rural-dwelling African community, and the Oxford Cognition Screen-Plus were used to capture cognitive performance as five continuous traits (total cognition score, verbal episodic memory, executive function, language, and visuospatial ability) for 2,246 adults in this population of South Africans. A novel common variant, rs73485231, reached genome-wide significance for association with episodic memory using data for ~14 million markers imputed from the H3Africa genotyping array data. Window-based replication of previously implicated variants and regions of interest support the discovery of African-specific associated variants despite the small population size and low allele frequency. This African genome-wide association study identifies suggestive associations with general cognition and domain-specific cognitive pathways and lays the groundwork for further genomic studies on cognition in Africa.

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

Background

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

Methods

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

Findings

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

Interpretation

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

Whole-Exome Sequencing in Family Trios Reveals De Novo Mutations Associated with Type 1 Diabetes Mellitus

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease characterized by insulin deficiency and loss of pancreatic islet β-cells. The objective of this study is to identify de novo mutations in 13 trios from singleton families that contribute to the genetic basis of T1DM through the application of whole-exome sequencing (WES). Of the 13 families sampled for this project, 12 had de novo variants, with Family 7 having the highest number (nine) of variants linked to T1DM/autoimmune pathways, whilst Family 4 did not have any variants past the filtering steps. There were 10 variants of 7 genes reportedly associated with T1DM (MST1; TDG; TYRO3; IFIHI; GLIS3; VEGFA; TYK2). There were 20 variants of 13 genes that were linked to endocrine, metabolic, or autoimmune diseases. Our findings demonstrate that trio-based WES is a powerful approach for identifying new candidate genes for the pathogenesis of T1D. Genotyping and functional annotation of the discovered de novo variants in a large cohort is recommended to ascertain their association with disease pathogenesis.

Allometric body shape indices, type 2 diabetes and kidney function: A two-sample Mendelian randomization study

AIM

To examine the association between body mass index (BMI)-independent allometric body shape indices and kidney function.

MATERIALS AND METHODS

We performed a two-sample Mendelian randomization (MR) analysis, using summary statistics from UK Biobank, CKDGen and DIAGRAM. BMI-independent allometric body shape indices were: A Body Shape Index (ABSI), Waist-Hip Index (WHI) and Hip Index (HI). Kidney function outcomes were: urinary albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate and blood urea nitrogen. Furthermore, we investigated type 2 diabetes (T2D) as a potential mediator on the pathway to albuminuria. The main analysis was inverse variance-weighted random-effects MR in participants of European ancestry. We also performed several sensitivity MR analyses.

RESULTS

A 1-standard deviation (SD) increase in genetically predicted ABSI and WHI levels was associated with higher UACR (β = 0.039 [95% confidence interval: 0.016, 0.063] log [UACR], P = 0.001 for ABSI, and β = 0.028 [0.012, 0.044] log [UACR], P = 6 x 10^-4 for WHI) in women, but not in men. Meanwhile, a 1-SD increase in genetically predicted HI was associated with lower UACR in women (β = -0.021 [-0.041, 0.000] log [UACR], P = 0.05) and in men (β = -0.026 [-0.058, 0.005] log [UACR], P = 0.10). Corresponding estimates in individuals with diabetes were substantially augmented. Risk of T2D increased for genetically high ABSI and WHI in women (P < 6 x 10^-19 ) only, but decreased for genetically high HI in both sexes (P < 9 x 10^-3 ). No other associations were observed.

CONCLUSIONS

Genetically high HI was associated with decreased risk of albuminuria, mediated through decreased T2D risk in both sexes. Opposite associations applied to genetically high ABSI and WHI in women only.

UK Biobank: a globally important resource for cancer research

UK Biobank is a large-scale prospective study with deep phenotyping and genomic data. Its open-access policy allows researchers worldwide, from academia or industry, to perform health research in the public interest. Between 2006 and 2010, the study recruited 502,000 adults aged 40-69 years from the general population of the United Kingdom. At enrolment, participants provided information on a wide range of factors, physical measurements were taken, and biological samples (blood, urine and saliva) were collected for long-term storage. Participants have now been followed up for over a decade with more than 52,000 incident cancer cases recorded. The study continues to be enhanced with repeat assessments, web-based questionnaires, multi-modal imaging, and conversion of the stored biological samples to genomic and other '-omic' data. The study has already demonstrated its value in enabling research into the determinants of cancer, and future planned enhancements will make the resource even more valuable to cancer researchers. Over 26,000 researchers worldwide are currently using the data, performing a wide range of cancer research. UK Biobank is uniquely placed to transform our understanding of the causes of cancer development and progression, and drive improvements in cancer treatment and prevention over the coming decades.

Identification of Novel Genetic Risk Factors for Focal Segmental Glomerulosclerosis in Children: Results From the Chronic Kidney Disease in Children (CKiD) Cohort

RATIONALE & OBJECTIVE

Focal segmental glomerulosclerosis (FSGS) is a major cause of pediatric nephrotic syndrome, and African Americans exhibit an increased risk for developing FSGS compared with other populations. Predisposing genetic factors have previously been described in adults. Here we performed genomic screening of primary FSGS in a pediatric African American population.

STUDY DESIGN

Prospective cohort with case-control genetic association study design.

SETTING & PARTICIPANTS

140 African American children with chronic kidney disease from the Chronic Kidney Disease in Children (CKiD) cohort, including 32 cases with FSGS.

PREDICTORS

Over 680,000 common single-nucleotide polymorphisms (SNPs) were tested for association. We also ran a pathway enrichment analysis and a human leucocyte antigen (HLA)-focused association study.

OUTCOME

Primary biopsy-proven pediatric FSGS.

ANALYTICAL APPROACH

Multivariate logistic regression models.

RESULTS

The genome-wide association study revealed 169 SNPs from 14 independent loci significantly associated with FSGS (false discovery rate [FDR]<5%). We observed notable signals for genetic variants within the APOL1 (P=8.6×10^-7; OR, 25.8 [95% CI, 7.1-94.0]), ALMS1 (P=1.3×10^-7; 13.0% in FSGS cases vs 0% in controls), and FGFR4 (P=4.3×10^-6; OR, 24.8 [95% CI, 6.3-97.7]) genes, all of which had previously been associated with adult FSGS, kidney function, or chronic kidney disease. We also highlighted novel, functionally relevant genes, including GRB2 (which encodes a slit diaphragm protein promoting podocyte structure through actin polymerization) and ITGB1 (which is linked to renal injuries). Our results suggest a major role for immune responses and antigen presentation in pediatric FSGS through (1) associations with SNPs in PTPRJ (or CD148, P=3.5×10^-7), which plays a role in T-cell receptor signaling, (2) HLA-DRB1∗11:01 association (P=6.1×10^-3; OR, 4.5 [95% CI, 1.5-13.0]), and (3) signaling pathway enrichment (P=1.3×10^-6).

LIMITATIONS

Sample size and no independent replication cohort with genomic data readily available.

CONCLUSIONS

Our genetic study has identified functionally relevant risk factors and the importance of immune regulation for pediatric primary FSGS, which contributes to a better description of its molecular pathophysiological mechanisms.

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

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

Combining genome-wide association studies highlight novel loci involved in human facial variation

Standard genome-wide association studies (GWASs) rely on analyzing a single trait at a time. However, many human phenotypes are complex and composed by multiple correlated traits. Here we introduce C-GWAS, a method for combining GWAS summary statistics of multiple potentially correlated traits. Extensive computer simulations demonstrated increased statistical power of C-GWAS compared to the minimal p-values of multiple single-trait GWASs (MinGWAS) and the current state-of-the-art method for combining single-trait GWASs (MTAG). Applying C-GWAS to a meta-analysis dataset of 78 single trait facial GWASs from 10,115 Europeans identified 56 study-wide suggestively significant loci with multi-trait effects on facial morphology of which 17 are novel loci. Using data from additional 13,622 European and Asian samples, 46 (82%) loci, including 9 (53%) novel loci, were replicated at nominal significance with consistent allele effects. Functional analyses further strengthen the reliability of our C-GWAS findings. Our study introduces the C-GWAS method and makes it available as computationally efficient open-source R package for widespread future use. Our work also provides insights into the genetic architecture of human facial appearance.

Short Chain Fatty Acid Metabolism in Relation to Gut Microbiota and Genetic Variability

It is widely accepted that the gut microbiota plays a significant role in modulating inflammatory and immune responses of their host. In recent years, the host-microbiota interface has gained relevance in understanding the development of many non-communicable chronic conditions, including cardiovascular disease, cancer, autoimmunity and neurodegeneration. Importantly, dietary fibre (DF) and associated compounds digested by the microbiota and their resulting metabolites, especially short-chain fatty acids (SCFA), were significantly associated with health beneficial effects, such as via proposed anti-inflammatory mechanisms. However, SCFA metabolic pathways are not fully understood. Major steps include production of SCFA by microbiota, uptake in the colonic epithelium, first-pass effects at the liver, followed by biodistribution and metabolism at the host's cellular level. As dietary patterns do not affect all individuals equally, the host genetic makeup may play a role in the metabolic fate of these metabolites, in addition to other factors that might influence the microbiota, such as age, birth through caesarean, medication intake, alcohol and tobacco consumption, pathogen exposure and physical activity. In this article, we review the metabolic pathways of DF, from intake to the intracellular metabolism of fibre-derived products, and identify possible sources of inter-individual variability related to genetic variation. Such variability may be indicative of the phenotypic flexibility in response to diet, and may be predictive of long-term adaptations to dietary factors, including maladaptation and tissue damage, which may develop into disease in individuals with specific predispositions, thus allowing for a better prediction of potential health effects following personalized intervention with DF.