Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

SH2B1 Tunes Hippocampal ERK Signaling to Influence Fluid Intelligence in Humans and Mice

Fluid intelligence is a cognitive domain that encompasses general reasoning, pattern recognition, and problem-solving abilities independent of task-specific experience. Understanding its genetic and neural underpinnings is critical yet challenging for predicting human development, lifelong health, and well-being. One approach to address this challenge is to map the network of correlations between intelligence and other constructs. In the current study, we performed a genome-wide association study using fluid intelligence quotient scores from the UK Biobank to explore the genetic architecture of the associations between obesity risk and fluid intelligence. Our results revealed novel common genetic loci (SH2B1, TUFM, ATP2A1, and FOXO3) underlying the association between fluid intelligence and body metabolism. Surprisingly, we demonstrated that SH2B1 variation influenced fluid intelligence independently of its effects on metabolism but partially mediated its association with bilateral hippocampal volume. Consistently, selective genetic ablation of Sh2b1 in the mouse hippocampus, particularly in inhibitory neurons, but not in excitatory neurons, significantly impaired working memory, short-term novel object recognition memory, and behavioral flexibility, but not spatial learning and memory, mirroring the human intellectual performance. Single-cell genetic profiling of Sh2B1-regulated molecular pathways revealed that Sh2b1 deletion resulted in aberrantly enhanced extracellular signal-regulated kinase (ERK) signaling, whereas pharmacological inhibition of ERK signaling reversed the associated behavioral impairment. Our cross-species study thus provides unprecedented insight into the role of SH2B1 in fluid intelligence and has implications for understanding the genetic and neural underpinnings of lifelong mental health and well-being.

Candidate genes related to acute cerebral circulatory disorders in Preeclampsia in the Kazakh Population

BACKGROUND

The purpose of this study is to conduct a comparative analysis of the population frequencies of alleles and genotypes of polymorphic variants of coagulation and fibrinolysis genes SERPINE1 rs1799889, ITGA2 rs1126643, THBD rs1042580, FII rs1799963, FV rs6025, FVII rs6046, angiogenesis and endothelial dysfunction PGF rs12411, FLT1 rs4769612, KDR rs2071559, ACE rs4340, GWAS associated with the development of acute cerebral circulatory disorders in preeclampsia, in an ethnically homogeneous population of Kazakhs with previously studied populations of the world.

METHODS

The genomic database was analysed based on the results of genotyping of 1800 conditionally healthy individuals of Kazakh nationality ∼2.5 million SNPs using OmniChip 2.5 M Illumina chips at the DECODE Iceland Genomic Center as part of the joint implementation of the project "Genetic Studies of Preeclampsia in Populations of Central Asia and Europe" (InterPregGen) within the 7th Framework Programme of the European Commission under Grant Agreement No. 282540.

RESULT

The study discovered a significantly higher population frequency of carrying the unfavorable rs1126643 allele of the ITGA2 gene polymorphism when compared with European populations. The population frequencies of carrying minor alleles of the SERPINE1 (rs179988) and KDR (rs2071559) genes in the Kazakh population were significantly lower when compared with the previously studied populations of Europe and Asia. An intermediate frequency of unfavorable minor alleles between European and Asian populations was found in Kazakhs for gene polymorphisms: FV rs6025, PGF rs12411, and ACE rs4340. The genomic analysis determined the choice of polymorphisms for their further replicative genotyping in patients with ACCD in PE in the Kazakh population.

CONCLUSION

The obtained results will serve as a basis for the development of effective methods of early diagnosis and treatment of PE in pregnant women, carriers of unfavorable genotypes.

Frequencies of Diagnostically Significant Polymorphisms of Hereditary Breast Cancer Forms in BRCA1 and BRCA2 Genes in the Kazakh Population

OBJECTIVE

Breast cancer is the most common form of cancer in women in the world with more than 400,000 deaths each year worldwide. The aim of this study is to compare population frequencies of alleles and genotypes of polymorphic variants of BRCA1 and BRCA2 genes associated with breast cancer risk in an ethnically homogenous Kazakh population with previously studied world populations. The material of the study was DNA isolated from peripheral blood of the enrolled population control group, represented by 1800 conditionally healthy individuals of Kazakh ethnicity.

METHODS

The DNA extraction was possible with the use of M-PVA magnetic particle separation method on the Prepito (PerkinElmer) automatic analyser for extraction of Chemagic Prepito (Wallac, Finland) nucleic acids using the PrepitoDNACytoPure reagent kit. Statistical calculations of allele and genotype frequencies, significance tests, and non-parametric χ2 analysis were carried out using PLINK software.

RESULTS

The results favour for the high genetic heterogeneity of the studied polymorphisms, which reflects the specifics of the Kazakh population structure resulted from complex evolutionary and migration processes, as well as the median geographic location between the populations of Asia and Europe.

CONCLUSION

Knowledge of the spectrum and frequency of mutations in BRCA1 and BRCA2 genes predisposing to breast cancer, which are present in varying frequencies in the Kazakh population, will provide a more effective approach to the screening protocol and allow for a faster, less expensive and more accessible genetic testing strategy for the Kazakhstan citizens.

Associations of genome-wide structural variations with phenotypic differences in cross-bred Eurasian pigs

BACKGROUND

During approximately 10,000 years of domestication and selection, a large number of structural variations (SVs) have emerged in the genome of pig breeds, profoundly influencing their phenotypes and the ability to adapt to the local environment. SVs (≥ 50 bp) are widely distributed in the genome, mainly in the form of insertion (INS), mobile element insertion (MEI), deletion (DEL), duplication (DUP), inversion (INV), and translocation (TRA). While studies have investigated the SVs in pig genomes, genome-wide association studies (GWAS)-based on SVs have been rarely conducted.

RESULTS

Here, we obtained a high-quality SV map containing 123,151 SVs from 15 Large White and 15 Min pigs through integrating the power of several SV tools, with 53.95% of the SVs being reported for the first time. These high-quality SVs were used to recover the population genetic structure, confirming the accuracy of genotyping. Potential functional SV loci were then identified based on positional effects and breed stratification. Finally, GWAS were performed for 36 traits by genotyping the screened potential causal loci in the F2 population according to their corresponding genomic positions. We identified a large number of loci involved in 8 carcass traits and 6 skeletal traits on chromosome 7, with FKBP5 containing the most significant SV locus for almost all traits. In addition, we found several significant loci in intramuscular fat, abdominal circumference, heart weight, and liver weight, etc. CONCLUSIONS: We constructed a high-quality SV map using high-coverage sequencing data and then analyzed them by performing GWAS for 25 carcass traits, 7 skeletal traits, and 4 meat quality traits to determine that SVs may affect body size between European and Chinese pig breeds.

Identification of disease modules using higher-order network structure

Motivation

Higher-order interaction patterns among proteins have the potential to reveal mechanisms behind molecular processes and diseases. While clustering methods are used to identify functional groups within molecular interaction networks, these methods largely focus on edge density and do not explicitly take into consideration higher-order interactions. Disease genes in these networks have been shown to exhibit rich higher-order structure in their vicinity, and considering these higher-order interaction patterns in network clustering have the potential to reveal new disease-associated modules.

Results

We propose a higher-order community detection method which identifies community structure in networks with respect to specific higher-order connectivity patterns beyond edges. Higher-order community detection on four different protein-protein interaction networks identifies biologically significant modules and disease modules that conventional edge-based clustering methods fail to discover. Higher-order clusters also identify disease modules from genome-wide association study data, including new modules that were not discovered by top-performing approaches in a Disease Module DREAM Challenge. Our approach provides a more comprehensive view of community structure that enables us to predict new disease-gene associations.

Availability and implementation

https://github.com/Reed-CompBio/graphlet-clustering.

Structural neurodevelopment at the individual level - a life-course investigation using ABCD, IMAGEN and UK Biobank data

Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages and the neurobiological basis underlying individual heterogeneity remains poorly understood. Using structural magnetic resonance imaging from the IMAGEN cohort (n=1,543), we show that adolescents can be clustered into three groups defined by distinct developmental patterns of whole-brain gray matter volume (GMV). Genetic and epigenetic determinants of group clustering and long-term impacts of neurodevelopment in mid-to-late adulthood were investigated using data from the ABCD, IMAGEN and UK Biobank cohorts. Group 1, characterized by continuously decreasing GMV, showed generally the best neurocognitive performances during adolescence. Compared to Group 1, Group 2 exhibited a slower rate of GMV decrease and worsened neurocognitive development, which was associated with epigenetic changes and greater environmental burden. Further, Group 3 showed increasing GMV and delayed neurocognitive development during adolescence due to a genetic variation, while these disadvantages were attenuated in mid-to-late adulthood. In summary, our study revealed novel clusters of adolescent structural neurodevelopment and suggested that genetically-predicted delayed neurodevelopment has limited long-term effects on mental well-being and socio-economic outcomes later in life. Our results could inform future research on policy interventions aimed at reducing the financial and emotional burden of mental illness.

Systemic lupus erythematosus and prostate cancer risk: a pool of cohort studies and Mendelian randomization analysis

BACKGROUND

Current observational studies suggest that there may be a causal relationship between systemic lupus erythematosus (SLE) and prostate cancer (PC). However, there is contradictory evidence. This study aimed to investigate and clarify the association between SLE and PC.

METHODS

We searched PubMed, Embase, Web of Science, and Scopus until May 2022. A meta-analysis was conducted on the standard incidence rate (SIR) and 95% CI. Subgroup analysis was performed based on the follow-up duration, study quality, and appropriate SLE diagnosis. Mendelian randomization (MR) of the two samples was used to determine whether genetically elevated SLE was causal for PC. Summary MR data were obtained from published GWASs, which included 1,959,032 individuals. The results were subjected to sensitivity analysis to verify their reliability.

RESULTS

In a meta-analysis of 79,316 participants from 14 trials, we discovered that patients with SLE had decreased PC risk (SIR, 0.78; 95% CI, 0.70-0.87) significantly. The MR results showed that a one-SD increase in genetic susceptibility to SLE significantly reduced PC risk (OR, 0.9829; 95% CI, 0.9715-0.9943; P = 0.003). Additional MR analyses suggested that the use of immunosuppressants (ISs) (OR, 1.1073; 95% CI, 1.0538-1.1634; P < 0.001), but not glucocorticoids (GCs) or non-steroidal anti-inflammatory drugs (NSAIDs), which were associated with increased PC risk. The results of the sensitivity analyses were stable, and there was no evidence of directional pleiotropy.

CONCLUSIONS

Our results suggest that patients with SLE have a lower risk of developing PC. Additional MR analyses indicated that genetic susceptibility to the use of ISs, but not GCs or NSAIDs, was associated with increased PC risk. This finding enriches our understanding of the potential risk factors for PC in patients with SLE. Further study is required to reach more definitive conclusions regarding these mechanisms.

Identification of Zip8-correlated hub genes in pulmonary hypertension by informatic analysis

Background

Pulmonary hypertension (PH) is a syndrome characterized by marked remodeling of the pulmonary vasculature and increased pulmonary vascular resistance, ultimately leading to right heart failure and even death. The localization of Zrt/Irt-like Protein 8 (ZIP8, a metal ion transporter, encoded by SLC39A8) was abundantly in microvasculature endothelium and its pivotal role in the lung has been demonstrated. However, the role of Zip8 in PH remains unclear.

Methods

Bioinformatics analysis was employed to identify SLC39A8 expression patterns and differentially expressed genes (DEGs) between PH patients and normal controls (NC), based on four datasets (GSE24988, GSE113439, GSE117261, and GSE15197) from the Biotechnology Gene Expression Omnibus (NCBI GEO) database. Gene set enrichment analysis (GSEA) was performed to analyze signaling pathways enriched for DEGs. Hub genes were identified by cytoHubba analysis in Cytoscape. Reverse transcriptase-polymerase chain reaction was used to validate SLC39A8 and its correlated metabolic DEGs expression in PH (SU5416/Hypoxia) mice.

Results

SLC39A8 expression was downregulated in PH patients, and this expression pattern was validated in PH (SU5416/Hypoxia) mouse lung tissue. SLC39A8-correlated genes were mainly enriched in the metabolic pathways. Within these SLC39A8-correlated genes, 202 SLC39A8-correlated metabolic genes were screened out, and seven genes were identified as SLC39A8-correlated metabolic hub genes. The expression patterns of hub genes were analyzed between PH patients and controls and further validated in PH mice. Finally, four genes (Fasn, Nsdhl, Acat2, and Acly) were downregulated in PH mice. However, there were no significant differences in the expression of the other three hub genes between PH mice and controls. Of the four genes, Fasn and Acly are key enzymes in fatty acids synthesis, Nsdhl is involved in cholesterol synthesis, and Acat2 is implicated in cholesterol metabolic transformation. Taken together, these results provide novel insight into the role of Zip8 in PH.

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

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

A multilocus genetic risk score for obesity: Association with BMI and metabolic alterations in a cohort with severe obesity

Genome wide association studies have identified numerous single nucleotide polymorphisms (SNPs) associated with obesity, yet effect sizes of individual SNPs are small. Therefore, the aim of our study was to investigate whether a genetic risk score (GRS) comprising risk alleles of SNPs identified in the GIANT consortium meta-analyses shows association with body mass index (BMI) and other BMI related metabolic alterations in a cohort with an extreme phenotype. Genotyping of 93 SNPs was performed in 314 obese individuals (mean BMI 40.5 ± 7.8 kg/m², aged 45 ± 12 years), participating in a standardized weight reduction program, and in 74 lean controls (mean BMI 24.6 ± 3.3 kg/m², aged 41.7 ± 13.4 years). Allele numbers of all 93 SNPs were added to a GRS. Anthropometric parameters, parameters of glucose/insulin and lipid metabolism were assessed standardized after a 12 hours fast. GRS was significantly different between controls and obese individuals (unweighted GRS: 86.6 vs 89.0, P = .002; weighted GRS: 84.9 vs 88.3, P = .005). Furthermore, linear regression analysis showed significant associations of GRS with BMI ( P < .0001), weight ( P = .0005), waist circumference ( P = .0039), fat mass ( P < .0001) and epicardial fat thickness ( P = .0032), yet with small effect sizes ( r ² < 0.06). In conclusion, in our study GRS could differentiate between extreme obese and lean individuals, and was associated with BMI and its related traits, yet with small effect sizes.

Multiple roles and regulatory mechanisms of the transcription factor HNF4 in the intestine

Hepatocyte nuclear factor 4-alpha (HNF4α) drives a complex array of transcriptional programs across multiple organs. Beyond its previously documented function in the liver, HNF4α has crucial roles in the kidney, intestine, and pancreas. In the intestine, a multitude of functions have been attributed to HNF4 and its accessory transcription factors, including but not limited to, intestinal maturation, differentiation, regeneration, and stem cell renewal. Functional redundancy between HNF4α and its intestine-restricted paralog HNF4γ, and co-regulation with other transcription factors drive these functions. Dysregulated expression of HNF4 results in a wide range of disease manifestations, including the development of a chronic inflammatory state in the intestine. In this review, we focus on the multiple molecular mechanisms of HNF4 in the intestine and explore translational opportunities. We aim to introduce new perspectives in understanding intestinal genetics and the complexity of gastrointestinal disorders through the lens of HNF4 transcription factors.

Mendelian randomization supports causality between overweight status and accelerated aging

It is reported that overweight may lead to accelerated aging. However, there is still a lack of evidence on the causal effect of overweight and aging. We collected genetic variants associated with overweight, age proxy indicators (telomere length, frailty index and facial aging), etc., from genome-wide association studies datasets. Then we performed MR analyses to explore associations between overweight and age proxy indicators. MR analyses were primarily conducted using the inverse variance weighted method, followed by various sensitivity and validation analyses. MR analyses indicated that there were significant associations of overweight on telomere length, frailty index, and facial aging (β = -0.018, 95% CI = -0.033 to -0.003, p = 0.0162; β = 0.055, 95% CI = 0.030-0.079, p < 0.0001; β = 0.029, 95% CI = 0.013-0.046, p = 0.0005 respectively). Overweight also had a significant negative causality with longevity expectancy (90th survival percentile, β = -0.220, 95% CI = -0.323 to -0.118, p < 0.0001; 99th survival percentile, β = -0.389, 95% CI = -0.652 to -0.126, p = 0.0038). Moreover, the findings tend to favor causal links between body fat mass/body fat percentage on aging proxy indicators, but not body fat-free mass. This study provides evidence of the causality between overweight and accelerated aging (telomere length decreased, frailty index increased, facial aging increased) and lower longevity expectancy. Accordingly, the potential significance of weight control and treatment of overweight in combating accelerated aging need to be emphasized.

Genes of Predisposition to Childhood Beta-Cell Acute Lymphoblastic Leukemia in the Kazakh Population

BACKGROUND

Today, acute lymphoblastic leukemia is one of the most common malignant diseases of the hematopoietic system. The genetic predisposition to ALL is not fully explored in various ethnic populations.

OBJECTIVE

The study aimed to conduct a comparative analysis of the population frequencies of alleles and genotypes of polymorphic gene variants: immune regulation GATA3 (rs3824662); transcription and differentiation of B cells: ARID5B (rs7089424, rs10740055), IKZF1 (rs4132601); differentiation of hematopoietic cells: PIP4K2A (rs7088318); apoptosis: CEBPE (rs2239633), tumor suppressors: CDKN2A (rs3731249), TP53 (rs1042522); carcinogen metabolism: CBR3 (rs1056892), CYP1A1 (rs104894, rs4646903), according to genome-wide association studies analyses associated with the risk of developing pediatric beta-cell acute lymphoblastic leukemia (B-cell ALL), in an ethnically homogeneous population of Kazakhs with studied populations.

METHODS

The genomic database consists of 1800 conditionally healthy persons of Kazakh nationality, genotyped using OmniChip 2.5-8 Illumina chips at the deCODE genetics as part of the InterPregGen 7 project of the European Union (EU) framework program under Grant Agreement No. 282540.

RESULTS

High population frequencies of single nucleotide polymorphism (SNP) minor alleles identified for immune regulation genes - GATA3 rs3824662 - 42.5%; transcription and differentiation of B-cells genes - ARID5B rs7089424 - 33.1% and rs10740055 - 48.5%, which suggests their significant genetic contribution to the risk of development and prognosis of the effectiveness of B-cell ALL therapy in the Kazakh population. The significantly lower population frequency of the minor allele G rs1056892 CBR3 gene - 38.6% in the Kazakhs suggests its significant protective effect in reducing the risk of childhood B-cell ALL and the smaller number of cardiac complications after anthracycline therapy.

CONCLUSION

The obtained results will serve as a basis for developing effective methods for predicting the risk of development, early diagnosis, and effectiveness of treatment of B-cell ALL in children.

Gestational Weight Gain Relates to DNA Methylation in Umbilical Cord, Which, In Turn, Associates with Offspring Obesity-Related Parameters

Excessive gestational weight gain (GWG) has a negative impact on offspring's health. Epigenetic modifications mediate these associations by causing changes in gene expression. We studied the association between GWG and DNA methylation in umbilical cord tissue; and determined whether the DNA methylation and the expression of corresponding annotated genes were associated with obesity-related parameters in offspring at 6 years of age. The methylated CpG sites (CpGs) associated with GWG were identified in umbilical cord tissue by genome-wide DNA methylation (n = 24). Twelve top CpGs were validated in a wider sample by pyrosequencing (n = 87), and the expression of their 5 annotated genes (SETD8, TMEM214, SLIT3, RPTOR, and HOXC8) was assessed by RT-PCR. Pyrosequencing results validated the association of SETD8, SLIT3, and RPTOR methylation with GWG and showed that higher levels of SETD8 and RPTOR methylation and lower levels of SLIT3 methylation relate to a higher risk of obesity in the offspring. The association of SETD8 and SLIT3 gene expression with offspring outcomes paralleled the association of methylation levels in opposite directions. Epigenetic changes in the umbilical cord tissue could explain, in part, the relationship between GWG and offspring obesity risk and be early biomarkers for the prevention of overweight and obesity in childhood.

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 pperm 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) (βadditive = 0.202/pperm = 0.015), KDM3B (rs757647) (βrecessive = 0.323/pperm = 0.005), INHBA (rs1079866) (βadditive = 0.110/pperm = 0.014) and NKX2-1 (rs999460) (βrecessive = -0.176/pperm = 0.015). Ten BW-significant models of interSNPs interactions (pperm ≤ 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.

Assessing the genetic relationship between gastroesophageal reflux disease and chronic respiratory diseases: a mendelian randomization study

BACKGROUND

Previous observational studies have found an association between gastroesophageal reflux disease (GERD) and chronic respiratory diseases, but it remains uncertain whether GERD causally influences these diseases. In this study, we aimed to estimate the causal associations between GERD and 5 chronic respiratory diseases.

METHODS

88 GERD-associated single nucleotide polymorphisms (SNPs) identified by the latest genome-wide association study were included as instrumental variables. Individual-level genetic summary data of participants were obtained from corresponding studies and the FinnGen consortium. We applied the inverse-variance weighted method to estimate the causality between genetically predicted GERD and 5 chronic respiratory diseases. Furthermore, the associations between GERD and common risk factors were investigated, and mediation analyses were conducted using multivariable MR. Various sensitivity analyses were also performed to verify the robustness of the findings.

RESULTS

Our study demonstrated that genetically predicted GERD was causally associated with an increased risk of asthma (OR 1.39, 95%CI 1.25-1.56, P < 0.001), idiopathic pulmonary fibrosis (IPF) (OR 1.43, 95%CI 1.05-1.95, P = 0.022), chronic obstructive disease (COPD) (OR 1.64, 95%CI 1.41-1.93, P < 0.001), chronic bronchitis (OR 1.77, 95%CI 1.15-2.74, P = 0.009), while no correlation was observed for bronchiectasis (OR 0.93, 95%CI 0.68-1.27, P = 0.645). Additionally, GERD was associated with 12 common risk factors for chronic respiratory diseases. Nevertheless, no significant mediators were discovered.

CONCLUSIONS

Our study suggested that GERD was a causal factor in the development of asthma, IPF, COPD and chronic bronchitis, indicating that GERD-associated micro-aspiration of gastric contents process might play a role in the development of pulmonary fibrosis in these diseases.

Computational Assessment of the Expression-modulating Potential for Non-coding Variants

Large-scale genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) studies have identified multiple non-coding variants associated with genetic diseases by affecting gene expression. However, pinpointing causal variants effectively and efficiently remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional non-coding expression-modulating variants. Multiple evaluations demonstrated CARMEN's superior performance over state-of-the-art tools. Applying CARMEN to GWAS and eQTL datasets further pinpointed several causal variants other than the reported lead single-nucleotide polymorphisms (SNPs). CARMEN scales well with the massive datasets, and is available online as a web server at http://carmen.gao-lab.org.

Modifiable pathways for longevity: A Mendelian randomization analysis

BACKGROUND

A variety of factors, including diet and lifestyle, obesity, physiology, metabolism, hormone levels, psychology, and inflammation, have been associated with longevity. The specific influences of these factors, however, are poorly understood. Here, possible causal relationships between putative modifiable risk factors and longevity are investigated.

METHODS

A random effects model was used to investigate the association between 25 putative risk factors and longevity. The study population comprised 11,262 long-lived subjects (≥90 years old, including 3484 individuals ≥99 years old) and 25,483 controls (≤60 years old), all of European ancestry. The data were obtained from the UK Biobank database. Genetic variations were used as instruments in two-sample Mendelian randomization to reduce bias. The odds ratios for genetically predicted SD unit increases were calculated for each putative risk factor. Egger regression was used to determine possible violations of the Mendelian randomization model.

RESULTS

Thirteen potential risk factors showed significant associations with longevity (≥90th) after correction for multiple testing. These included smoking initiation (OR:1.606; CI: 1.112-2.319) and educational attainment (OR:2.538, CI: 1.685-3.823) in the diet and lifestyle category, systolic and diastolic blood pressure (OR per SD increase: 0.518; CI: 0.438-0.614 for SBP and 0.620; CI 0.514-0.748 for DBP) and venous thromboembolism (OR:0.002; CI: 0.000-0.047) in the physiology category, obesity (OR: 0.874; CI: 0.796-0.960), BMI (OR per 1-SD increase: 0.691; CI: 0.628-0.760), and body size at age 10 (OR per 1-SD increase:0.728; CI: 0.595-0.890) in the obesity category, type 2 diabetes (T2D) (OR:0.854; CI: 0.816-0.894), LDL cholesterol (OR per 1-SD increase: 0.743; CI: 0.668-0.826), HDL cholesterol (OR per 1-SD increase: 1.243; CI: 1.112-1.390), total cholesterol (TC) (OR per 1-SD increase: 0.786; CI: 0.702-0.881), and triglycerides (TG) (OR per 1-SD increase: 0.865; CI: 0.749-0.998) in the metabolism category. Both longevity (≥90th) and super-longevity (≥99th), smoking initiation, body size at age 10, BMI, obesity, DBP, SBP, T2D, HDL, LDL, and TC were consistently associated with outcomes. The examination of underlying pathways found that BMI indirectly affected longevity through three pathways, namely, SBP, plasma lipids (HDL/TC/LDL), and T2D (p < 0.05).

CONCLUSION

BMI was found to significantly affect longevity through SBP, plasma lipid (HDL/TC/LDL), and T2D. Future strategies should focus on modifying BMI to improve health and longevity.

A Gene-Acculturation Study of Obesity Among US Hispanic/Latinos: The Hispanic Community Health Study/Study of Latinos

OBJECTIVE

In the United States, Hispanic/Latino adults face a high burden of obesity; yet, not all individuals are equally affected, partly due in part to this ethnic group's marked sociocultural diversity. We sought to analyze the modification of body mass index (BMI) genetic effects in Hispanic/Latino adults by their level of acculturation, a complex biosocial phenomenon that remains understudied.

METHODS

Among 11,747 Hispanic/Latinos adults in the Hispanic Community Health Study/Study of Latinos aged 18 to 76 years from four urban communities (2008-2011), we a) tested our hypothesis that the effect of a genetic risk score (GRS) for increased BMI may be exacerbated by higher levels of acculturation and b) examined if GRS acculturation interactions varied by gender or Hispanic/Latino background group. All genetic modeling controlled for relatedness, age, gender, principal components of ancestry, center, and complex study design within a generalized estimated equation framework.

RESULTS

We observed a GRS increase of 0.34 kg/m 2 per risk allele in weighted mean BMI. The estimated main effect of GRS on BMI varied both across acculturation level and across gender. The difference between high and low acculturation ranged from 0.03 to 0.23 kg/m 2 per risk allele, but varied across acculturation measure and gender.

CONCLUSIONS

These results suggest the presence of effect modification by acculturation, with stronger effects on BMI among highly acculturated individuals and female immigrants. Future studies of obesity in the Hispanic/Latino community should account for sociocultural environments and consider their intersection with gender to better target obesity interventions.

Prebiotic and Probiotic Modulation of the Microbiota-Gut-Brain Axis in Depression

Emerging evidence demonstrates that alterations to the gut microbiota can affect mood, suggesting that the microbiota-gut-brain (MGB) axis contributes to the pathogenesis of depression. Many of these pathways overlap with the way in which the gut microbiota are thought to contribute to metabolic disease progression and obesity. In rodents, prebiotics and probiotics have been shown to modulate the composition and function of the gut microbiota. Together with germ-free rodent models, probiotics have provided compelling evidence for a causal relationship between microbes, microbial metabolites, and altered neurochemical signalling and inflammatory pathways in the brain. In humans, probiotic supplementation has demonstrated modest antidepressant effects in individuals with depressive symptoms, though more studies in clinically relevant populations are needed. This review critically discusses the role of the MGB axis in depression pathophysiology, integrating preclinical and clinical evidence, as well as the putative routes of communication between the microbiota-gut interface and the brain. A critical overview of the current approaches to investigating microbiome changes in depression is provided. To effectively translate preclinical breakthroughs in MGB axis research into novel therapies, rigorous placebo-controlled trials alongside a mechanistic and biochemical understanding of prebiotic and probiotic action are required from future research.

Phenome-wide Mendelian randomization study evaluating the association of circulating vitamin D with complex diseases

Background

Circulating vitamin D has been associated with multiple clinical diseases in observational studies, but the association was inconsistent due to the presence of confounders. We conducted a bidirectional Mendelian randomization (MR) study to explore the healthy atlas of vitamin D in many clinical traits and evaluate their causal association.

Methods

Based on a large-scale genome-wide association study (GWAS), the single nucleotide polymorphism (SNPs) instruments of circulating 25-hydroxyvitamin D (25OHD) from 443,734 Europeans and the corresponding effects of 10 clinical diseases and 42 clinical traits in the European population were recruited to conduct a bidirectional two-sample Mendelian randomization study. Under the network of Mendelian randomization analysis, inverse-variance weighting (IVW), weighted median, weighted mode, and Mendelian randomization (MR)–Egger regression were performed to explore the causal effects and pleiotropy. Mendelian randomization pleiotropy RESidual Sum and Outlier (MR-PRESSO) was conducted to uncover and exclude pleiotropic SNPs.

Results

The results revealed that genetically decreased vitamin D was inversely related to the estimated BMD (β = −0.029 g/cm2, p = 0.027), TC (β = −0.269 mmol/L, p = 0.006), TG (β = −0.208 mmol/L, p = 0.002), and pulse pressure (β = −0.241 mmHg, p = 0.043), while positively associated with lymphocyte count (β = 0.037%, p = 0.015). The results did not reveal any causal association of vitamin D with clinical diseases. On the contrary, genetically protected CKD was significantly associated with increased vitamin D (β = 0.056, p = 2.361 × 10−26).

Conclusion

The putative causal effects of circulating vitamin D on estimated bone mass, plasma triglyceride, and total cholesterol were uncovered, but not on clinical diseases. Vitamin D may be linked to clinical disease by affecting health-related metabolic markers.

GWAS-Identified Variants for Obesity Do Not Influence the Risk of Developing Multiple Myeloma: A Population-Based Study and Meta-Analysis

Multiple myeloma (MM) is an incurable disease characterized by the presence of malignant plasma cells in the bone marrow that secrete specific monoclonal immunoglobulins into the blood. Obesity has been associated with the risk of developing solid and hematological cancers, but its role as a risk factor for MM needs to be further explored. Here, we evaluated whether 32 genome-wide association study (GWAS)-identified variants for obesity were associated with the risk of MM in 4189 German subjects from the German Multiple Myeloma Group (GMMG) cohort (2121 MM cases and 2068 controls) and 1293 Spanish subjects (206 MM cases and 1087 controls). Results were then validated through meta-analysis with data from the UKBiobank (554 MM cases and 402,714 controls) and FinnGen cohorts (914 MM cases and 248,695 controls). Finally, we evaluated the correlation of these single nucleotide polymorphisms (SNPs) with cQTL data, serum inflammatory proteins, steroid hormones, and absolute numbers of blood-derived cell populations (n = 520). The meta-analysis of the four European cohorts showed no effect of obesity-related variants on the risk of developing MM. We only found a very modest association of the POC5_rs2112347G and ADCY3_rs11676272G alleles with MM risk that did not remain significant after correction for multiple testing (per-allele OR = 1.08, p = 0.0083 and per-allele OR = 1.06, p = 0.046). No correlation between these SNPs and functional data was found, which confirms that obesity-related variants do not influence MM risk.

Interactions between genetic and lifestyle factors on cardiometabolic disease-related outcomes in Latin American and Caribbean populations: A systematic review

Introduction

The prevalence of cardiometabolic diseases has increased in Latin American and the Caribbean populations (LACP). To identify gene-lifestyle interactions that modify the risk of cardiometabolic diseases in LACP, a systematic search using 11 search engines was conducted up to May 2022.

Methods

Eligible studies were observational and interventional studies in either English, Spanish, or Portuguese. A total of 26,171 publications were screened for title and abstract; of these, 101 potential studies were evaluated for eligibility, and 74 articles were included in this study following full-text screening and risk of bias assessment. The Appraisal tool for Cross-Sectional Studies (AXIS) and the Risk Of Bias In Non-Randomized Studies-of Interventions (ROBINS-I) assessment tool were used to assess the methodological quality and risk of bias of the included studies.

Results

We identified 122 significant interactions between genetic and lifestyle factors on cardiometabolic traits and the vast majority of studies come from Brazil (29), Mexico (15) and Costa Rica (12) with FTO, APOE, and TCF7L2 being the most studied genes. The results of the gene-lifestyle interactions suggest effects which are population-, gender-, and ethnic-specific. Most of the gene-lifestyle interactions were conducted once, necessitating replication to reinforce these results.

Discussion

The findings of this review indicate that 27 out of 33 LACP have not conducted gene-lifestyle interaction studies and only five studies have been undertaken in low-socioeconomic settings. Most of the studies were cross-sectional, indicating a need for longitudinal/prospective studies. Future gene-lifestyle interaction studies will need to replicate primary research of already studied genetic variants to enable comparison, and to explore the interactions between genetic and other lifestyle factors such as those conditioned by socioeconomic factors and the built environment. The protocol has been registered on PROSPERO, number CRD42022308488.

Systematic review registration

https://clinicaltrials.gov, identifier CRD420223 08488.

A genome-wide association study identifies distinct variants associated with pulmonary function among European and African ancestries from the UK Biobank

Pulmonary function is an indicator of well-being, and pulmonary pathologies are the third major cause of death worldwide. We analysed the UK Biobank genome-wide association summary statistics of pulmonary function for Europeans and individuals of recent African descent to identify variants associated with the trait in the two ancestries. Here, we show 627 variants in Europeans and 3 in Africans associated with three pulmonary function parameters. In addition to the 110 variants in Europeans previously reported to be associated with phenotypes related to pulmonary function, we identify 279 novel loci, including an ISX intergenic variant rs369476290 on chromosome 22 in Africans. Remarkably, we find no shared variants among Africans and Europeans. Furthermore, enrichment analyses of variants separately for each ancestry background reveal significant enrichment for terms related to pulmonary phenotypes in Europeans but not Africans. Further analysis of studies of pulmonary phenotypes reveals that individuals of European background are disproportionally overrepresented in datasets compared to Africans, with the gap widening over the past five years. Our findings extend our understanding of the different variants that modify the pulmonary function in Africans and Europeans, a promising finding for future GWASs and medical studies.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Strategies to identify causal common genetic variants and corresponding effector genes for paediatric obesity

BACKGROUND

Childhood obesity rates are on the rise, but there are currently no effective therapies available to slow or halt their progression. Although environmental and lifestyle factors have been implicated in its pathogenesis, childhood obesity is considered a complex disorder with a clear genetic component. Intense genome-wide association study (GWAS) efforts through large-scale collaborations have enabled the discovery of genetic loci robustly associated with childhood obesity beyond the classic FTO locus. That said, GWAS itself does not pinpoint the actual underlying causal effector genes, but rather just yields association signals in the genome.

OBJECTIVE

This review aims to outline what has been elucidated thus far on the genetic aetiology of commong childhood obesity and to describe strategies to identify and validate both causal common genetic variants and their corresponding effector genes.

RESULTS

Relevant cell types for molecular studies can be identified by gene set enrichment analysis and considering known biology of obesity-related physiological processes. Putatively causal single nucleotide polymorphisms (SNPs) can be identified by several methods including statistical fine mapping and 'assay for transposase accessible chromatin sequencing' (ATAC-seq). Variant to gene mapping can then nominate effector genes likely regulated by cis-regulatory elements harbouring putatively causal SNPs. A SNP's cis-regulatory activity can be functionally validated by several in vitro methods including luciferase assay and CRISPR approaches. These CRISPR approaches can also be used to investigate how dysregulatn of effector genes may confer obesity risk.

CONCLUSION

Uncovering the causative genes related to GWAS signals and elucidating their functional contributions to paediatric obesity with these strategies will deepen our understanding of this disease and serve better treatment outcomes.

Conserved roles for Hnf4 family transcription factors in zebrafish development and intestinal function

Transcription factors play important roles in the development of the intestinal epithelium and its ability to respond to endocrine, nutritional, and microbial signals. Hepatocyte nuclear factor 4 family nuclear receptors are liganded transcription factors that are critical for the development and function of multiple digestive organs in vertebrates, including the intestinal epithelium. Zebrafish have 3 hepatocyte nuclear factor 4 homologs, of which, hnf4a was previously shown to mediate intestinal responses to microbiota in zebrafish larvae. To discern the functions of other hepatocyte nuclear factor 4 family members in zebrafish development and intestinal function, we created and characterized mutations in hnf4g and hnf4b. We addressed the possibility of genetic redundancy amongst these factors by creating double and triple mutants which showed different rates of survival, including apparent early lethality in hnf4a; hnf4b double mutants and triple mutants. RNA sequencing performed on digestive tracts from single and double mutant larvae revealed extensive changes in intestinal gene expression in hnf4a mutants that were amplified in hnf4a; hnf4g mutants, but limited in hnf4g mutants. Changes in hnf4a and hnf4a; hnf4g mutants were reminiscent of those seen in mice including decreased expression of genes involved in intestinal function and increased expression of cell proliferation genes, and were validated using transgenic reporters and EdU labeling in the intestinal epithelium. Gnotobiotics combined with RNA sequencing also showed hnf4g has subtler roles than hnf4a in host responses to microbiota. Overall, phenotypic changes in hnf4a single mutants were strongly enhanced in hnf4a; hnf4g double mutants, suggesting a conserved partial genetic redundancy between hnf4a and hnf4g in the vertebrate intestine.

Shared genetics between classes of obesity and psychiatric disorders: A large-scale genome-wide cross-trait analysis

AIMS

Epidemiological studies demonstrate an association between classes of obesity and psychiatric disorders, although little is known about shared genetics and causality of association. Thus, we aimed to investigate shared genetics and causal link between different classes of obesity and psychiatric disorders.

METHODS

We used genome-wide association study (GWAS) summary data range from 9725 to 500,199 sample sizes of European descent, conducted a large-scale genome-wide cross-trait association study to investigate genetic overlap between the classes of obesity and anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, obsessive-compulsive disorder, schizophrenia, anxiety disorders and Tourette syndrome. We conducted transcriptome-wide association study analysis (TWAS) to identified variants regulated gene expression in those related disorders. Finally, pathway enrichment analysis to identified major pathways.

RESULTS

In the combined analysis, we replicated 211 previously reported loci and discovered 58 novel independent loci that were associated with all three classes of obesity and related psychiatric disorders. Functional analysis revealed that the identified variants regulated gene expression in major tissues belonging to exocrine/endocrine, digestive, circulatory, adipose, digestive, respiratory, and nervous systems, such as DCC, NEGR1, INO80E. Mendelian randomization analyses suggested that there may be a two-way or one-way causal relationship between obesity and psychiatric disorders.

CONCLUSION

This large-scale genome-wide cross-trait analysis identified shared genetics and potential causal links between classes of obesity and psychiatric disorders (attention deficit hyperactivity disorder, autism spectrum disorder, anorexia nervosa, major depressive disorder, schizophrenia, and obsessive-compulsive disorder). Such shared genetics suggests potential new biological functions in common among them.

A cross-species approach using an in vivo evaluation platform in mice demonstrates that sequence variation in human RABEP2 modulates ischemic stroke outcomes

Ischemic stroke, caused by vessel blockage, results in cerebral infarction, the death of brain tissue. Previously, quantitative trait locus (QTL) mapping of cerebral infarct volume and collateral vessel number identified a single, strong genetic locus regulating both phenotypes. Additional studies identified RAB GTPase-binding effector protein 2 (Rabep2) as the casual gene. However, there is yet no evidence that variation in the human ortholog of this gene plays any role in ischemic stroke outcomes. We established an in vivo evaluation platform in mice by using adeno-associated virus (AAV) gene replacement and verified that both mouse and human RABEP2 rescue the mouse Rabep2 knockout ischemic stroke volume and collateral vessel phenotypes. Importantly, this cross-species complementation enabled us to experimentally investigate the functional effects of coding sequence variation in human RABEP2. We chose four coding variants from the human population that are predicted by multiple in silico algorithms to be damaging to RABEP2 function. In vitro and in vivo analyses verify that all four led to decreased collateral vessel connections and increased infarct volume. Thus, there are naturally occurring loss-of-function alleles. This cross-species approach will expand the number of targets for therapeutics development for ischemic stroke.

Causal associations of obesity related anthropometric indicators and body compositions with knee and hip arthritis: A large-scale genetic correlation study

Backgrounds

Epidemiological studies have repeatedly investigated the association between obesity related anthropometric indicators and body compositions and osteoarthritis (OA). However, the results have remained inconsistent. This work aimed to investigate the genetic correlation and causal associations of obesity related anthropometric indicators and body compositions with knee and hip OA.

Methods

Single-nucleotide polymorphisms associated with the exposures were searched from the recent genome-wide association studies (GWAS) to obtain full statistics. Summary-level results of knee and hip OA were from the UK Biobank and arcOGEN. First, linkage disequilibrium score regression (LD score regression) was applied to detect the genetic correlation (rg). We further performed a series of sensitivity analyses as validation of primary mendelian randomization (MR) results and the specific evidence of potential causal effects was defined.

Results

We found that genetic components in OA had significant correlation with obesity related traits, except waist-to-hip ratio. In the univariable MR analysis, with the exception of waist-to-hip ratio, obesity related anthropometric indicators were causally associated with increased risks of knee and hip OA. For obesity related body compositions, higher fat-free mass in arm, leg, and whole body increased the risk of knee OA but only fat-free mass in leg showed a significant association with hip OA. Meanwhile trunk fat mass and trunk fat percentage, were associated with knee but not with hip OA. Higher fat mass, and fat percentage in arm, leg, and whole body increased the risk of both knee and hip OA. After adjusting for BMI, the multivariable MR showed maintained results in knee OA. However, in hip OA, only fat mass and fat-free mass in arm, leg, trunk and whole body were significantly associated with the risk of hip OA.

Conclusion

The present study suggests genetic evidence for certain causal associations of obesity related anthropometric indicators and body compositions with knee and hip OA, which may provide important insights for the prevention and treatment on OA.

An application based on bioinformatics and machine learning for risk prediction of sepsis at first clinical presentation using transcriptomic data

Background: Linking genotypic changes to phenotypic traits based on machine learning methods has various challenges. In this study, we developed a workflow based on bioinformatics and machine learning methods using transcriptomic data for sepsis obtained at the first clinical presentation for predicting the risk of sepsis. By combining bioinformatics with machine learning methods, we have attempted to overcome current challenges in predicting disease risk using transcriptomic data.

Methods: High-throughput sequencing transcriptomic data processing and gene annotation were performed using R software. Machine learning models were constructed, and model performance was evaluated by machine learning methods in Python. The models were visualized and interpreted using the Shapley Additive explanation (SHAP) method.

Results: Based on the preset parameters and using recursive feature elimination implemented via machine learning, the top 10 optimal genes were screened for the establishment of the machine learning models. In a comparison of model performance, CatBoost was selected as the optimal model. We explored the significance of each gene in the model and the interaction between each gene through SHAP analysis.

Conclusion: The combination of CatBoost and SHAP may serve as the best-performing machine learning model for predicting transcriptomic and sepsis risks. The workflow outlined may provide a new approach and direction in exploring the mechanisms associated with genes and sepsis risk.

Identifying shared genetic loci between coronavirus disease 2019 and cardiovascular diseases based on cross-trait meta-analysis

People with coronavirus disease 2019 (COVID-19) have different mortality or severity, and this clinical outcome is thought to be mainly attributed to comorbid cardiovascular diseases. However, genetic loci jointly influencing COVID-19 and cardiovascular disorders remain largely unknown. To identify shared genetic loci between COVID-19 and cardiac traits, we conducted a genome-wide cross-trait meta-analysis. Firstly, from eight cardiovascular disorders, we found positive genetic correlations between COVID-19 and coronary artery disease (CAD, R_g = 0.4075, P = 0.0031), type 2 diabetes (T2D, R_g = 0.2320, P = 0.0043), obesity (OBE, R_g = 0.3451, P = 0.0061), as well as hypertension (HTN, R_g = 0.233, P = 0.0026). Secondly, we detected 10 shared genetic loci between COVID-19 and CAD, 3 loci between COVID-19 and T2D, 5 loci between COVID-19 and OBE, and 21 loci between COVID-19 and HTN, respectively. These shared genetic loci were enriched in signaling pathways and secretion pathways. In addition, Mendelian randomization analysis revealed significant causal effect of COVID-19 on CAD, OBE and HTN. Our results have revealed the genetic architecture shared by COVID-19 and CVD, and will help to shed light on the molecular mechanisms underlying the associations between COVID-19 and cardiac traits.

The causal impact of childhood obesity on bone mineral density and fracture in adulthood: A two-sample Mendelian randomization study

Observational studies have indicated the associations between obesity with bone mineral density (BMD) and fracture but yield inconsistent results. The impact of childhood obesity on bone health in adulthood is even less clear. The present study adopted the Mendelian randomization methods to determine whether the genetically predicted childhood obesity was causally associated with BMD and the risk of fracture. Genetic variants were extracted from genome-wide association studies (GWAS) to identify childhood obesity loci [IEU open GWAS project: childhood obesity (ID: ieu-a-1096)] and single nucleotide polymorphisms (SNPs) as instrumental variables to investigate causality. We used two-sample univariable Mendelian randomization (MR) to estimate causal relationships between childhood obesity on BMD and fracture subtypes based on SNPs from European samples. To avoid bias, Cochran's Q test and leave-one-out variant analysis were performed. The MR analysis shows strong evidence that childhood obesity is causally associated with eBMD (OR 1.068, 95% CI 1.043–1.095, P &lt; 0.001) and a weak decreased risk of leg fracture (OR 0.9990, 95% CI 0.9981–0.9999, P =0.033) based on the inverse variance weighting (IVW) method. After adjusting for diabetes and adult obesity, the results of eBMD remained the same. The MR analysis revealed sufficient evidence to indicate childhood obesity was causally associated with increased BMD and decreased risk of leg fracture in adults. Childhood obesity could be taken into consideration when assessing eBMD.

Towards a global view of multiple sclerosis genetics

Multiple sclerosis (MS) is a neuroimmunological disorder of the CNS with a strong heritable component. The genetic architecture of MS susceptibility is well understood in populations of European ancestry. However, the extent to which this architecture explains MS susceptibility in populations of non-European ancestry remains unclear. In this Perspective article, we outline the scientific arguments for studying MS genetics in ancestrally diverse populations. We argue that this approach is likely to yield insights that could benefit individuals with MS from all ancestral groups. We explore the logistical and theoretical challenges that have held back this field to date and conclude that, despite these challenges, inclusion of participants of non-European ancestry in MS genetics studies will ultimately be of value to all patients with MS worldwide.

Variants of SLC2A10 may be Linked to Poor Response to Metformin

Purpose

A study among Filipinos revealed that only 15% of patients with diabetes achieved glycemic control, and poor response to metformin could be one of the possible reasons. Recent studies demonstrate how genetic variations influence response to metformin. Hence, the present study aimed to determine genetic variants associated with poor response to metformin.

Methods

Using a candidate variant approach, 195 adult Filipino participants with newly diagnosed type 2 diabetes mellitus (T2DM) were enrolled in a case-control study. Genomic DNA from blood samples were collected. Allelic and genotypic associations of variants with poor response to metformin were determined using exact statistical methods.

Results

Several polymorphisms were nominally associated with poor response to metformin (P_uncorr < 0.05). The most notable is the association of multiple variants in the SLC2A10 gene—rs2425911, rs3092412, and rs2425904—with common additive genetic mode of inheritance. Other variants that have possible associations with poor drug response include rs340874 (PROX-AS1), rs815815 (CALM2), rs1333049 (CDKN2B-AS1), rs2010963 (VEGFA), rs1535435 and rs9494266 (AHI1), rs11128347 (PDZRN3), rs1805081 (NPC1), and rs13266634 (SLC30A8).

Conclusion

In Filipinos, a trend for the association for several variants was noted, with further observation that several mechanisms may be involved. The results may serve as pilot data for further validation of candidate variants for T2DM pharmacotherapy.

Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study

BACKGROUND

Weight trajectories might reflect individual health status. In this study, we aimed to examine the clinical and genetic associations of adult weight trajectories using electronic health records (EHRs) in the BioMe Biobank.

METHODS

We constructed four weight trajectories based on a-priori definitions of weight changes (5% or 10%) using annual weight in EHRs (stable weight, weight gain, weight loss, and weight cycle); the final weight dataset included 21 487 participants with 162 783 annual weight measures. To confirm accurate assignment of weight trajectories, we manually reviewed weight trajectory plots for 100 random individuals. We then did a hypothesis-free phenome-wide association study (PheWAS) to identify diseases associated with each weight trajectory. Next, we estimated the single-nucleotide polymorphism-based heritability (hSNP2) of weight trajectories using GCTA-GREML, and we did a hypothesis-driven analysis of anorexia nervosa and depression polygenic risk scores (PRS) on these weight trajectories, given both diseases are associated with weight changes. We extended our analyses to the UK Biobank to replicate findings from a patient population to a generally healthy population.

FINDINGS

We found high concordance between manually assigned weight trajectories and those assigned by the algorithm (accuracy ≥98%). Stable weight was consistently associated with lower disease risks among those passing Bonferroni-corrected p value in our PheWAS (p≤4·4 × 10-5). Additionally, we identified an association between depression and weight cycle (odds ratio [OR] 1·42, 95% CI 1·31-1·55, p≤7·7 × 10-16). The adult weight trajectories were heritable (using 5% weight change as the cutoff: hSNP2 of 2·1%, 95% CI 0·9-3·3, for stable weight; 4·1%, 1·4-6·8, for weight gain; 5·5%, 2·8-8·2, for weight loss; and 4·7%, 2·3-7·1%, for weight cycle). Anorexia nervosa PRS was positively associated with weight loss trajectory among individuals without eating disorder diagnoses (OR1SD 1·16, 95% CI 1·07-1·26, per 1 SD higher PRS, p=0·011), and the association was not attenuated by obesity PRS. No association was found between depression PRS and weight trajectories after permutation tests. All main findings were replicated in the UK Biobank (p<0·05).

INTERPRETATION

Our findings suggest the importance of considering weight from a longitudinal aspect for its association with health and highlight a crucial role of weight management during disease development and progression.

FUNDING

Klarman Family Foundation, US National Institute of Mental Health (NIMH).

Gene networks under circadian control exhibit diurnal organization in primate organs

Mammalian organs are individually controlled by autonomous circadian clocks. At the molecular level, this process is defined by the cyclical co-expression of both core transcription factors and their downstream targets across time. While interactions between these molecular clocks are necessary for proper homeostasis, these features remain undefined. Here, we utilize integrative analysis of a baboon diurnal transcriptome atlas to characterize the properties of gene networks under circadian control. We found that 53.4% (8120) of baboon genes are oscillating body-wide. Additionally, two basic network modes were observed at the systems level: daytime and nighttime mode. Daytime networks were enriched for genes involved in metabolism, while nighttime networks were enriched for genes associated with growth and cellular signaling. A substantial number of diseases only form significant disease modules at either daytime or nighttime. In addition, a majority of SARS-CoV-2-related genes and modules are rhythmically expressed, which have significant network proximities with circadian regulators. Our data suggest that synchronization amongst circadian gene networks is necessary for proper homeostatic functions and circadian regulators have close interactions with SARS-CoV-2 infection.

Integrative analysis of the high-resolution baboon diurnal transcriptome, provides insights into the effect of circadian rhythm on the whole-body primate gene network.

Fibrinogen in Alzheimer's Disease, Parkinson's Disease and Lewy Body Dementia: A Mendelian Randomization Study

Fibrinogen is reportedly associated with neurodegenerative diseases (NDs), but the underlying causality remains controversial. Using Mendelian randomization (MR), this study aimed to assess the causal association between fibrinogen and Alzheimer’s disease (AD), Parkinson’s disease (PD), and Lewy body dementia (LBD). Genetic variants associated with fibrinogen and γ-fibrinogen were selected and used as instrumental variables. The effect estimates of the main analysis were obtained by inverse-variance weighting (IVW), complemented by sensitivity analyses to verify model assumptions, and multivariable MR was conducted to control for potential pleiotropic effect. Two-step MR was performed to assess the causal association through mediators. The main analysis suggested no causal association between genetically predicted plasma fibrinogen and γ-fibrinogen levels and the risk of AD, PD, and LBD. The effect estimates did not change in the follow-up sensitivity analyses and MVMR. However, the two-step MR analysis provides evidence that fibrinogen may contribute to the risk of AD via CRP levels. There was an inverse effect of adult height levels on the risk of AD. Our results support the effects of fibrinogen on the risk of AD through increasing plasma CRP levels. Our study found no evidence to support the effects of genetically determined fibrinogen and γ-fibrinogen levels on the risk of PD and LBD. Additionally, our findings suggested an inverse association between genetically determined adult height levels and the risk of AD. Future studies are needed to elucidate the underlying mechanisms and their clinical applications.

Prediction of type 2 diabetes mellitus onset using logistic regression-based scorecards

Background

Type 2 diabetes (T2D) accounts for ~90% of all cases of diabetes, resulting in an estimated 6.7 million deaths in 2021, according to the International Diabetes Federation. Early detection of patients with high risk of developing T2D can reduce the incidence of the disease through a change in lifestyle, diet, or medication. Since populations of lower socio-demographic status are more susceptible to T2D and might have limited resources or access to sophisticated computational resources, there is a need for accurate yet accessible prediction models.

Methods

In this study, we analyzed data from 44,709 nondiabetic UK Biobank participants aged 40-69, predicting the risk of T2D onset within a selected time frame (mean of 7.3 years with an SD of 2.3 years). We started with 798 features that we identified as potential predictors for T2D onset. We first analyzed the data using gradient boosting decision trees, survival analysis, and logistic regression methods. We devised one nonlaboratory model accessible to the general population and one more precise yet simple model that utilizes laboratory tests. We simplified both models to an accessible scorecard form, tested the models on normoglycemic and prediabetes subcohorts, and compared the results to the results of the general cohort. We established the nonlaboratory model using the following covariates: sex, age, weight, height, waist size, hip circumference, waist-to-hip ratio, and body mass index. For the laboratory model, we used age and sex together with four common blood tests: high-density lipoprotein (HDL), gamma-glutamyl transferase, glycated hemoglobin, and triglycerides. As an external validation dataset, we used the electronic medical record database of Clalit Health Services.

Results

The nonlaboratory scorecard model achieved an area under the receiver operating curve (auROC) of 0.81 (95% confidence interval [CI] 0.77-0.84) and an odds ratio (OR) between the upper and fifth prevalence deciles of 17.2 (95% CI 5-66). Using this model, we classified three risk groups, a group with 1% (0.8-1%), 5% (3-6%), and the third group with a 9% (7-12%) risk of developing T2D. We further analyzed the contribution of the laboratory-based model and devised a blood test model based on age, sex, and the four common blood tests noted above. In this scorecard model, we included age, sex, glycated hemoglobin (HbA1c%), gamma glutamyl-transferase, triglycerides, and HDL cholesterol. Using this model, we achieved an auROC of 0.87 (95% CI 0.85-0.90) and a deciles' OR of ×48 (95% CI 12-109). Using this model, we classified the cohort into four risk groups with the following risks: 0.5% (0.4-7%); 3% (2-4%); 10% (8-12%); and a high-risk group of 23% (10-37%) of developing T2D. When applying the blood tests model using the external validation cohort (Clalit), we achieved an auROC of 0.75 (95% CI 0.74-0.75). We analyzed several additional comprehensive models, which included genotyping data and other environmental factors. We found that these models did not provide cost-efficient benefits over the four blood test model. The commonly used German Diabetes Risk Score (GDRS) and Finnish Diabetes Risk Score (FINDRISC) models, trained using our data, achieved an auROC of 0.73 (0.69-0.76) and 0.66 (0.62-0.70), respectively, inferior to the results achieved by the four blood test model and by the anthropometry models.

Conclusions

The four blood test and anthropometric models outperformed the commonly used nonlaboratory models, the FINDRISC and the GDRS. We suggest that our models be used as tools for decision-makers to assess populations at elevated T2D risk and thus improve medical strategies. These models might also provide a personal catalyst for changing lifestyle, diet, or medication modifications to lower the risk of T2D onset.

Funding

The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.

Mendelian randomization analysis for attention deficit/hyperactivity disorder: studying a broad range of exposures and outcomes

BACKGROUND

Attention deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder caused by a combination of genetic and environmental factors and is often thought as an entry point into a negative life trajectory, including risk for comorbid disorders, poor educational achievement or low income. In the present study, we aimed to clarify the causal relationship between ADHD and a comprehensive range of related traits.

METHODS

We used genome-wide association study (GWAS) summary statistics for ADHD (n = 53 293) and 124 traits related to anthropometry, cognitive function and intelligence, early life exposures, education and employment, lifestyle and environment, longevity, neurological, and psychiatric and mental health or personality and psychosocial factors available in the MR-Base database (16 067 ≤n ≤766 345). To investigate their causal relationship with ADHD, we used two-sample Mendelian randomization (MR) with a range of sensitivity analyses, and validated MR findings using causal analysis using summary effect estimates (CAUSE), aiming to avoid potential false-positive results.

RESULTS

Our findings strengthen previous evidence of a causal effect of ADHD liability on smoking and major depression, and are consistent with a causal effect on odds of decreased average total household income [odds ratio (OR) = 0.966, 95% credible interval (CrI) = (0.954, 0.979)] and increased lifetime number of sexual partners [OR = 1.023, 95% CrI = (1.013, 1.033)]. We also found evidence for a causal effect on ADHD for liability of arm predicted mass and weight [OR = 1.452, 95% CrI = (1.307, 1.614) and OR = 1.430, 95% CrI = (1.326, 1.539), respectively] and time spent watching television [OR = 1.862, 95% CrI = (1.545, 2.246)], and evidence for a bidirectional effect for age of first sexual intercourse [beta = -0.058, 95% CrI = (-0.072, -0.044) and OR = 0.413, 95% CrI = (0.372, 0.457), respectively], odds of decreased age completed full-time education [OR = 0.972, 95% CrI = (0.962, 0.981) and OR = 0.435, 95% CrI = (0.356, 0.533), respectively] and years of schooling [beta = -0.036, 95% CrI = (-0.048, -0.024) and OR = 0.458, 95% CrI = (0.411, 0.511), respectively].

CONCLUSIONS

Our results may contribute to explain part of the widespread co-occurring traits and comorbid disorders across the lifespan of individuals with ADHD and may open new opportunities for developing preventive strategies for ADHD and for negative ADHD trajectories.

Genetically Predicted Obesity Causally Increased the Risk of Hypertension Disorders in Pregnancy

Aims

This study aimed to evaluate the causal association between obesity and hypertension disorders in pregnancy.

Methods

Two-sample Mendelian randomization (MR) study was conducted based on the data obtained from the GIANT (n = 98,697 participants) consortium and FinnGen (n = 96,449 participants) consortium to determine the causal effect of obesity on the risk of hypertension disorders in pregnancy. Based on a genome-wide significance, 14 single-nucleotide polymorphisms (SNPs) associated with obesity-related databases were used as instrumental variables. The random-effects inverse-variance weighted (IVW) method was adopted as the main analysis with a supplemented sensitive analysis of the MR-Egger and weighted median approaches.

Results

All three MR methods showed that genetically predicted obesity causally increased the risk of hypertension disorders in pregnancy. IVW analysis provided obesity as a risk factor for hypertension disorders in pregnancy with an odds ratio (OR) of 1.39 [95% confidence interval (CI) 1.21–1.59; P = 2.46 × 10⁻⁶]. Weighted median and MR Egger regression also showed directionally similar results [weighted median OR = 1.49 (95% CI, 1.24–1.79), P = 2.45 × 10⁻⁵; MR-Egger OR = 1.95 (95% CI, 1.35–2.82), P = 3.84 × 10⁻³]. No directional pleiotropic effects were found between obesity and hypertension disorders in pregnancy with both MR-Egger intercepts and funnel plots.

Conclusions

Our findings provided directed evidence that obesity was causally associated with a higher risk of hypertension disorders in pregnancy. Taking measures to reduce the proportion of obesity may help reduce the incidence of hypertension disorders in pregnancy.

Differences in thrombin and plasmin generation potential between East African and Western European adults: The role of genetic and non-genetic factors

BACKGROUND

Geographic variability in coagulation across populations and their determinants are poorly understood.

OBJECTIVE

To compare thrombin (TG) and plasmin (PG) generation parameters between healthy Tanzanian and Dutch individuals, and to study associations with inflammation and different genetic, host and environmental factors.

METHODS

TG and PG parameters were measured in 313 Tanzanians of African descent living in Tanzania and 392 Dutch of European descent living in the Netherlands and related to results of a dietary questionnaire, circulating inflammatory markers, genotyping, and plasma metabolomics.

RESULTS

Tanzanians exhibited an enhanced TG and PG capacity, compared to Dutch participants. A higher proportion of Tanzanians had a TG value in the upper quartile with a PG value in the lower/middle quartile, suggesting a relative pro-coagulant state. Tanzanians also displayed an increased normalized thrombomodulin sensitivity ratio, suggesting reduced sensitivity to protein C. In Tanzanians, PG parameters (lag time and TTP) were associated with seasonality and food-derived plasma metabolites. The Tanzanians had higher concentrations of pro-inflammatory cytokines, which correlated strongly with TG and PG parameters. There was limited overlap in genetic variation associated with TG and PG parameters between the two cohorts. Pathway analysis of genetic variants in the Tanzanian cohort revealed multiple immune pathways that were enriched with TG and PG traits, confirming the importance of co-regulation between coagulation and inflammation.

CONCLUSIONS

Tanzanians have an enhanced TG and PG potential compared to Dutch individuals, which may relate to differences in inflammation, genetics and diet. These observations highlight the importance of better understanding of the geographic variability in coagulation across populations.

The Role of Morning Plasma Cortisol in Obesity: A Bidirectional Mendelian Randomization Study

CONTEXT

Cortisol, an important hormone regulated by the hypothalamic-pituitary-adrenal axis, is associated with obesity. However, it is unclear whether the relationship between cortisol and obesity is causal or could be explained by reverse causality.

OBJECTIVE

This work aims to assess the role of morning plasma cortisol in clinical classes of obesity.

METHODS

In this bidirectional, 2-sample mendelian randomization (MR) study, cortisol-associated genetic variants were obtained from the CORtisol NETwork consortium (n = 12 597). The primary outcomes were obesity class I (body mass index [BMI] ≥ 30), class II (BMI ≥ 35), and class III (BMI ≥ 40). The inverse variance weighting method was used as the main analysis, with weighted median, MR-Egger, and MR pleiotropy residual sum and outlier (MR-PRESSO) as sensitivity analyses. Conversely, genetic variants predicting clinical classes of obesity were applied to the cortisol genome-wide association study.

RESULTS

Genetically predicted cortisol was associated with reduced risk of obesity class I (OR = 0.905; 95% CI, 0.865-0.946; P < .001). Evidence from bidirectional MR showed that obesity class II and class III were associated with lower cortisol levels ([class II-cortisol OR = 0.953; 95% CI, 0.923-0.983; P = .002]; [class III-cortisol OR = 0.955; 95% CI, 0.942-0.967; P < .001]), indicating reverse causality between cortisol and obesity.

CONCLUSION

This study demonstrates that cortisol is negatively associated with obesity and vice versa. Together, these findings suggest that blunted morning plasma cortisol secretion may be responsible for severe obesity. Regulating morning plasma cortisol secretion might be a prevention measure for obese people.

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

Mendelian randomization study of obesity and type 2 diabetes in hospitalized COVID-19 patients

BACKGROUND

Both obesity and type 2 diabetes (T2D) are reported to be highly enriched in hospitalized COVID-19 patients. Due to the close correlation between obesity and T2D, it is important to examine whether obesity and T2D are independently related to COVID-19 hospitalization.

OBJECTIVE

To examine the causal effect of obesity and T2D in hospitalized COVID-19 patients using Mendelian randomization (MR).

RESEARCH DESIGN AND METHODS

This two-sample MR analysis applied genetic markers of obesity identified in the genome wide association study (GWAS) by the GIANT Consortium as instrumental variables (IVs) of obesity; and genetic markers of T2D identified by the DIAGRAM Consortium as IVs of T2D. The MR analysis was performed in hospitalized COVID-19 patient by the COVID-19 Host Genetics Initiative using the MR-Base platform.

RESULTS

All 3 classes of obesity (Class 1/2/3) were shown as the causal risk factors of COVID-19 hospitalization; however, T2D doesn't increase the risk of hospitalization or critically ill COVID-19 as an independent factor.

CONCLUSIONS

Obesity, but not T2D, is a primary risk factor of COVID-19 hospitalization.

Physiological roles of mammalian transmembrane adenylyl cyclase isoforms

Adenylyl cyclases (ACs) catalyze the conversion of ATP to the ubiquitous second messenger cAMP. Mammals possess nine isoforms of transmembrane ACs, dubbed AC1-9, that serve as major effector enzymes of G protein-coupled receptors (GPCRs). The transmembrane ACs display varying expression patterns across tissues, giving the potential for them to have a wide array of physiological roles. Cells express multiple AC isoforms, implying that ACs have redundant functions. Furthermore, all transmembrane ACs are activated by Gαs, so it was long assumed that all ACs are activated by Gαs-coupled GPCRs. AC isoforms partition to different microdomains of the plasma membrane and form prearranged signaling complexes with specific GPCRs that contribute to cAMP signaling compartments. This compartmentation allows for a diversity of cellular and physiological responses by enabling unique signaling events to be triggered by different pools of cAMP. Isoform-specific pharmacological activators or inhibitors are lacking for most ACs, making knockdown and overexpression the primary tools for examining the physiological roles of a given isoform. Much progress has been made in understanding the physiological effects mediated through individual transmembrane ACs. GPCR-AC-cAMP signaling pathways play significant roles in regulating functions of every cell and tissue, so understanding each AC isoform's role holds potential for uncovering new approaches for treating a vast array of pathophysiological conditions.

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.

A Novel Hierarchical Clustering Approach for Joint Analysis of Multiple Phenotypes Uncovers Obesity Variants Based on ARIC

Genome-wide association studies (GWASs) have successfully discovered numerous variants underlying various diseases. Generally, one-phenotype one-variant association study in GWASs is not efficient in identifying variants with weak effects, indicating that more signals have not been identified yet. Nowadays, jointly analyzing multiple phenotypes has been recognized as an important approach to elevate the statistical power for identifying weak genetic variants on complex diseases, shedding new light on potential biological mechanisms. Therefore, hierarchical clustering based on different methods for calculating correlation coefficients (HCDC) is developed to synchronously analyze multiple phenotypes in association studies. There are two steps involved in HCDC. First, a clustering approach based on the similarity matrix between two groups of phenotypes is applied to choose a representative phenotype in each cluster. Then, we use existing methods to estimate the genetic associations with the representative phenotypes rather than the individual phenotypes in every cluster. A variety of simulations are conducted to demonstrate the capacity of HCDC for boosting power. As a consequence, existing methods embedding HCDC are either more powerful or comparable with those of without embedding HCDC in most scenarios. Additionally, the application of obesity-related phenotypes from Atherosclerosis Risk in Communities via existing methods with HCDC uncovered several associated variants. Among these, UQCC1-rs1570004 is reported as a significant obesity signal for the first time, whose differential expression in subcutaneous fat, visceral fat, and muscle tissue is worthy of further functional studies.