Novel genetic loci identified for the pathophysiology of childhood obesity in the Hispanic population

Molecular Imprints of Clinical Comorbidities in Hypothalamic Extracellular Vesicles at the Onset of Obesity

The onset of obesity is characterized by early physiological and molecular changes, including leptin resistance and hypothalamic dysfunction, preceding significant weight gain and metabolic complications. Extracellular vesicles (EVs) are key mediators of intercellular communication, reflecting early pathological shifts in metabolic disorders. This study investigates the role of hypothalamic EVs (hEVs) in early obesogenic insult and their potential implications for obesity-related comorbidities. Using a hamster model fed a high fat diet for 30 days, next-generation proteomics revealed altered hEV protein compositions linked to cellular metabolism, neuroinflammation, and metabolic dysfunction, mirroring early obesity-related dysfunction. These findings highlight the adaptive molecular profiles of hEVs during early obesogenic insult and their potential as biomarkers and molecular mediators in obesity progression and its comorbidities. In conclusion, this study provides new insights into the molecular mechanisms underlying the onset of obesity and highlights hEVs as promising targets for early detection and intervention.

Genome-wide association study identifying novel risk variants associated with glycaemic traits in the continental African AWI-Gen cohort

AIMS/HYPOTHESIS

Glycaemic traits such as high fasting glucose levels and insulin resistance are positively associated with the risk of type 2 diabetes and other cardiometabolic diseases. Genetic association studies have identified hundreds of associations for each glycaemic trait, yet very few studies have involved continental African populations. We report the results of genome-wide association studies (GWASs) in a pan-African cohort for four glycaemic traits, namely fasting glucose, fasting insulin, insulin resistance (HOMA-IR) and beta cell function (HOMA-B), which are quantitative variables that affect the risk of developing type 2 diabetes.

METHODS

GWASs for the four traits were conducted in approximately 10,000 individuals from the Africa Wits-INDEPTH Partnership for Genomics Studies (AWI-Gen) cohort, with participants from Burkina Faso, Ghana, Kenya and South Africa. Association testing was performed using linear mixed models implemented in BOLT-LMM, with age, sex, BMI and principal components as covariates. Replication, fine mapping and functional annotation were performed using standard approaches.

RESULTS

We identified a novel signal (rs574173815) in the intron of the ankyrin repeat domain 33B (ANKRD33B) gene associated with fasting glucose, and a novel signal (rs114029796) in the intronic region of the WD repeat domain 7 (WDR7) gene associated with fasting insulin. SNPs in WDR7 have been shown to be associated with type 2 diabetes. A variant (rs74806991) in the intron of ADAM metallopeptidase with thrombospondin type 1 motif 16 (ADAMTS16) and another variant (rs6506934) in the β-1,4-galactosyltransferase 6 gene (B4GALT6) are associated with HOMA-IR. Both ADAMTS16 and B4GALT6 are implicated in the development of type 2 diabetes. In addition, our study replicated several well-established fasting glucose signals in the GCK-YTK6, SLC2A2 and THORLNC gene regions.

CONCLUSIONS/INTERPRETATION

Our findings highlight the importance of performing GWASs for glycaemic traits in under-represented populations, especially continental African populations, to discover novel associated variants and broaden our knowledge of the genetic aetiology of glycaemic traits. The limited replication of well-known signals in this study hints at the possibility of a unique genetic architecture of these traits in African populations.

DATA AVAILABILITY

The dataset used in this study is available in the European Genome-Phenome Archive (EGA) database ( https://ega-archive.org/ ) under study accession code EGAS00001002482. The phenotype dataset accession code is EGAD00001006425 and the genotype dataset accession code is EGAD00010001996. The availability of these datasets is subject to controlled access by the Data and Biospecimen Access Committee of the H3Africa Consortium. GWAS summary statistics are accessible through the NHGRI-EBI GWAS Catalog ( https://www.ebi.ac.uk/gwas/ ).

Father's adolescent body silhouette is associated with offspring asthma, lung function and BMI through DNA methylation

Boys' pubertal overweight associates with future offspring's asthma and low lung function. To identify how paternal overweight is associated with offspring's DNA methylation (DNAm), we conducted an epigenome-wide association study of father's body silhouette (FBS) at three timepoints (age 8, voice break and 30) and change in FBS between these times, with offspring DNAm, in the RHINESSA cohort (N = 339). We identified 2005 differentially methylated cytosine-phosphate-guanine (dmCpG) sites (FDR < 0.05), including dmCpGs associated with offspring asthma (119), lung function (178) and BMI (291). Voice break FBS associated with dmCpGs in loci including KCNJ10, FERMT1, NCK2 and WWP1. Change in FBS across sexual maturation associated with DNAm at loci including NOP10, TRRAP, EFHD1, MRPL17 and NORD59A;ATP5B and showed strong correlation in reduced gene expression in loci NAP1L5, ATP5B, ZNF695, ZNF600, VTRNA2-1, SOAT2 and AGPAT2. We identified 24 imprinted genes including: VTRNA2-1, BLCAP, WT1, NAP1L5 and PTPRN2. Identified pathways relate to lipid and glucose metabolism and adipogenesis. Father's overweight at puberty and during reproductive maturation was strongly associated with offspring DNA, suggesting a key role for epigenetic mechanisms in intergenerational transfer from father to offspring in humans. The results support an important vulnerability window in male puberty for future offspring health.

Human genetic variation determines 24-hour rhythmic gene expression and disease risk

24-hour biological rhythms are essential to maintain physiological homeostasis. Disruption of these rhythms increases the risks of multiple diseases. Biological rhythms are known to have a genetic basis formed by core clock genes, but how individual genetic variation shapes the oscillating transcriptome and contributes to human chronophysiology and disease risk is largely unknown. Here, we mapped interactions between temporal gene expression and genotype to identify quantitative trait loci (QTLs) contributing to rhythmic gene expression. These newly identified QTLs were termed as rhythmic QTLs (rhyQTLs), which determine previously unappreciated rhythmic genes in human subpopulations with specific genotypes. Functionally, rhyQTLs and their associated rhythmic genes contribute extensively to essential chronophysiological processes, including bile acid and lipid metabolism. The identification of rhyQTLs sheds light on the genetic mechanisms of gene rhythmicity, offers mechanistic insights into variations in human disease risk, and enables precision chronotherapeutic approaches for patients.

Trans-ancestry genome-wide association study of childhood body mass index identifies novel loci and age-specific effects

Over the past 30 years, obesity prevalence has markedly increased globally, including among children. Although genome-wide association studies (GWASs) have identified over 1,000 genetic loci associated with obesity-related traits in adults, the genetic architecture of childhood obesity is less well characterized. Moreover, most childhood obesity GWASs have been restricted to severely obese children, in relatively small sample sizes, and in primarily European-ancestry populations. To identify genetic loci associated with early-childhood body mass index (BMI), we performed GWAS of BMI Z scores in eight ancestrally diverse cohorts: ZOE 2.0 cohort, the Santiago Longitudinal Study (SLS), the Vanderbilt University BioVU biobank, the Geisinger MyCode Health Initiative biobank, Study of Latino (SOL) Youth, Pelotas (Brazil) Birth Cohort, Cameron County Hispanic Cohort (CCHC), and Viva La Familia cohort. We subsequently performed inverse-variance-weighted fixed-effect meta-analysis of these results with previously published GWAS summary statistics of BMI Z scores of children in the Early Growth Genetics (EGG) Consortium and the Norwegian Mother and Child Cohort (MoBa), constituting a final total of 84,804 individuals. We identified 39 genome-wide significant loci associated with childhood BMI, including three putatively novel loci (EFNA5 and DTWD2, RP11-2N5.1 on chromosome 5, and LSM14A on chromosome 19). We also observed a dynamic nature of genetic loci-BMI associations across the life course, with distinct effects across childhood and adulthood, highlighting possible critical periods for early-childhood interventions. These findings strengthen calls for larger population-based studies of children across age strata and across diverse populations.

Mapping the landscape of childhood obesity: genomic insights and socioeconomic status in Indian school-going children

OBJECTIVE

Childhood obesity (OB) is influenced by complex gene-environmental interaction. While genetics of adult OB have been extensively studied, polygenic childhood OB in non-European populations is still underexplored. Furthermore, in a developing nation such as India, how the environmental component strongly modulated by the socioeconomic status (SES) shapes the genetic susceptibility is crucial to understand.

METHODS

A two-staged genome-wide association study (GWAS; N = 5673) and an independent exome-wide association study (ExWAS; N = 4963) were performed using a generalized linear model assuming additive effect to identify the common and rare genetic variants respectively associated with childhood OB. Rare-variant burden testing was also performed. We used the gene expression profiles and regulatory data from public databases to explain the novel associations. The implications of SES as a potential modifier of genetic susceptibility were evaluated.

RESULTS

GWAS identified novel associations in TCF7L2, IMMP2L, IPMK, CDC5L, SNTG1, and MX1, whereas ExWAS uncovered CNTN4, COQ4, TNFRSF10D, FLG-AS1, and BMP3. Both GWAS and ExWAS validated known associations in FTO and MC4R. Furthermore, rare-variant testing highlighted the role of 101 genes. We also observed that SES can modulate the inherent susceptibility to OB.

CONCLUSIONS

Our study identified genetic variants associated with childhood OB and highlighted the gene-environmental interaction in childhood OB.

Plasma Proteins Associated with the Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) Diet and Incident Dementia

BACKGROUND

The Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) diet slows cognitive decline and protects brain health, but the mechanisms are poorly understood.

OBJECTIVES

We aimed to determine the plasma proteins associated with the MIND diet score and their ability to predict incident dementia in the Atherosclerosis Risk in Communities study.

METHODS

We analyzed 10,230 Black and White participants at visit 3 (1993-1995) with food frequency questionnaire and proteomics data and randomly divided them into discovery (n = 6850) and replication (n = 3380) samples. We examined associations between the MIND diet score and 4955 proteins using multivariable linear regression and elastic net regression. C-statistics were calculated to assess if proteins improved the prediction of high MIND diet adherence beyond participant characteristics. Cox proportional hazards models were used to assess associations between significant diet-related proteins and incident dementia over 2 decades. C-statistics assessed the ability of significant proteins to improve dementia prediction beyond known risk factors.

RESULTS

Of 316 proteins associated with the MIND diet score in the discovery sample at a false discovery rate <0.05, 62 were internally replicated. Of these, 21 proteins selected by the elastic net individually improved MIND diet score prediction. After a median follow-up of 21 y, there were 2311 dementia cases. Five diet-related proteins, thrombospondin-2 [hazard ratio (HR): 1.19; 95% confidence interval (CI): 1.11, 1.29], protein ABHD14A (HR: 1.23; 95% CI: 1.11, 1.37), structural maintenance of chromosomes protein 3 (HR: 1.19; 95% CI: 1.08, 1.31), epidermal growth factor receptor (HR: 0.68; 95% CI: 0.53, 0.86), and interleukin-12 subunit beta (HR: 1.14; 95% CI: 1.05, 1.25) were significantly associated with incident dementia. All 5 proteins individually and together improved the prediction of dementia risk.

CONCLUSIONS

Using high-throughput proteomics, we identified candidate biomarkers of the MIND diet score and incident dementia, which are implicated in neural signaling, angiogenesis, and anti-inflammatory pathways.

The metabolic hypothesis for restrictive eating behaviors: A computational and evolutionary approach

BackgroundRestrictive eating behaviors, widespread in humans and animals, are often conceptualized as maladaptive, but may serve adaptive purposes under specific circumstances.AimTo investigate the adaptive potential of restrictive eating behaviors.MethodsComputational models explored the relationship between food availability, basal metabolic rate, and restrictive eating behaviors. The evolutionary conservation of genes associated with both basal metabolic rate and restrictive eating behaviors was evaluated.ResultsThe propensity to engage in restrictive eating behaviors protected against negative energy balances at times of food volatility, implying ecological fitness potential. A high degree of conservation across species was observed in retrieved genes, implying selective evolutionary constraints.ConclusionRestrictive eating behaviors may represent a maladaptive outcome of evolutionary constraints on protective metabolic mechanisms. The higher prevalence of restrictive eating in women could stem from a greater reliance on protective strategies, highlighting the need for further exploration of sex-specific genetic and environmental interactions.

Genomic correlation, shared loci, and causal association between obesity, periodontitis and tooth loss

Observational studies have reported an association of obesity with periodontitis and tooth loss, yet findings remain inconsistent. We aim to investigate the genetic link underlying obesity-related traits (BMI [body mass index], WHR [waist-to-hip ratio], WHRadjBMI and childhood BMI), periodontitis and tooth loss. Leveraging summary statistics from large-scale genome-wide association studies, we comprehensively investigated the pair-wise genetic correlation using linkage disequilibrium score regression (LDSC) and SUPERGNOVA, identified shared loci using cross-phenotype association analysis (CPASSOC), and estimated causal association using Mendelian randomization. We identified a significant genetic correlation of obesity with tooth loss, but not with periodontitis. Partitioning the genome into LD-independent regions revealed 10 significantly shared local signals across six regions. Genome-wide cross-trait analysis uncovered 14 shared loci, four of which were colocalized: rs2064044 (PP4 = 0.94), rs6000329 (PP4 = 0.86), rs7134628 (PP4 = 0.86), and rs1286769 (PP4 = 0.90). Notably, rs1286769, identified via CPASSOC and validated through colocalization analysis, is located near RARβ, a gene associated with both BMI and denture use. Mendelian randomization revealed a nominally-significant causal association of obesity with periodontitis (P = 0.045) but a robust causal association with tooth loss represented by number of teeth (BMI: beta = [Formula: see text]0.20, 95%CI = [Formula: see text]0.26 to [Formula: see text]0.14, P = 5.27 × 10-11; WHR: beta = [Formula: see text]0.16, 95%CI = [Formula: see text]0.24 to [Formula: see text]0.08, P = 3.71 × 10-5). Results of CAUSE were consistent with main findings. From a genetic perspective, our work highlights an intrinsic link between obesity, periodontitis and tooth loss, which may add new lines of evidence and provide insights for clinical and public oral health applications.

Genetic insights into CRP levels in Indian adolescents: confirming adult genetic associations

CRP is a biomarker of acute inflammation linked to metabolic complications. Given the rising prevalence of these conditions in India, we investigated the genetic basis of CRP levels in Indian adolescents, an underrepresented group in genetic studies, to identify early markers of metabolic risk. We performed a two-phased genome-wide association study (GWAS; N = 5052) and an independent Exome-wide association study (ExWAS; N = 4547), to identify both common and rare genetic variants associated with CRP levels. The study identified intergenic variants near CRP and CRPP1 genes, and APOC1 gene as the key regulators of CRP levels establishing the universality of these associations. The GWAS identified the variant rs4247360 (PITPNC1) to be associated at a suggestive significance. The ExWAS single variant association identified novel associations in genes FGL1 (rs35431851), C19orf45 (rs608144, rs475923, rs484870), TRAPPC12 (rs11686212) and KIAA0087 (rs17153822). The SKATO analysis of the rare variants highlighted the role of loss of function and missense variants in genes EPS15, CCDC15, ZNF286A, ELF1, B3GNT8, ZNF850, MAP2, and PSG2. The GWAS and ExWAS in the present study validated the association of 56 variants previously reported for CRP levels. The meta-analysis with the CRP GWAS earlier reported in Indian adults revealed the shared genetic architecture of CRP levels across age groups. The gene-set enrichment analysis highlighted the role of CRP-associated genes in inflammatory and cardiometabolic pathways. The study enhances understanding of genetic predispositions to inflammation and metabolic disorders confirming known associations, identifying novel loci, and validating shared genetic architecture across age-groups, guiding targeted prevention for at-risk youth.

Integrative analysis of single-cell and transcriptome sequencing with experimental validation reveals PKHD1L1 as a novel biomarker in lung adenocarcinoma

Polycystic kidney and hepatic disease 1-like protein 1 (PKHD1L1) is predicted to encode a large type I transmembrane protein involved in hearing transmission and mediating cellular immunity under physiological conditions. However, its role in cancer progression, especially in lung adenocarcinoma (LUAD), has not been fully elucidated. In this study, we observed significantly lower expression of PKHD1L1 in LUAD tissues than in normal lung tissues on the basis of the integration of public datasets from the TCGA and GEO cohorts. Furthermore, we found that low PKHD1L1 expression was a strong predictor of poor prognosis in patients with LUAD. Pathway enrichment analyses revealed that PKHD1L1 is associated primarily with asthma and multiple immune processes. Through meticulous analysis of immune cell infiltrates and single-cell datasets, we discerned a notable correlation between the expression of PKHD1L1 and the presence of B cells, with a particularly strong association observed in plasma cells. This finding led us to believe that the role of PKHD1L1 may extend beyond its previously reported involvement in cellular immunity, potentially impacting humoral immunity as well. In vitro experiments revealed that the over-expression of PKHD1L1 significantly inhibited the proliferation and migration ability of LUAD cell lines. These findings suggest that PKHD1L1 is an important prognostic indicator and a potential therapeutic target for LUAD.

A genome-wide association study identified candidate regions and genes for commercial traits in a Landrace population

Backfat thickness (BFT) and feed conversion ratio (FCR) are important commercial traits in the pig industry. With the increasing demand for human health and meat production, identifying functional genomic regions and genes associated with these commercial traits is critical for enhancing production efficiency. In this research, we conducted a genome-wide association study (GWAS) on a Landrace population comprising 4,295 individuals with chip data for BFT and FCR. Our analysis revealed a total of 118 genome-wide significant signals located on chromosomes SSC1, SSC2, SSC7, SSC12, and SSC13, respectively. Furthermore, we identified 10 potential regions associated with the two traits and annotated the genes within these regions. In addition, enrichment analysis was also performed. Notably, candidate genes such as SHANK2, KCNQ1, and ABL1 were found to be associated with BFT, whereas NAP1L4, LSP1, and PPFIA1 genes were related to the FCR. Our findings provide valuable insights into the genetic architecture of these two traits and offer guidance for future pig breeding efforts.

DNA methylation in cord blood partially mediates the effects of prepregnancy BMI on early childhood offspring BMI

OBJECTIVE

We investigated whether prepregnancy BMI (prePregBMI) in women with obesity was associated with differential DNA methylation (DNAm) in cord blood (CB) and whether DNAm may mediate the association of prePregBMI and early childhood BMI z score (BMIz).

METHODS

From the Treatment of Obese Pregnant Women (TOP) study, 232 mother-child pairs were included. We conducted an epigenome-wide association study on prePregBMI and CB DNAm (450k array), followed by causal mediation analyses to test whether DNAm may mediate effects of prePregBMI on  BMIz at age 36 months (BMIz36).

RESULTS

DNAm at 5345 CpG sites annotated to 2842 genes, which were overrepresented in biological processes linked to carbohydrate metabolism and plasma lipoprotein particle clearance, was associated with prePregBMI (false discovery rate < 10%). Causal mediation analyses of 168 methylation sites associated with BMIz36 (p < 0.05) and overlapping with the 5345 prePregBMI-associated sites identified two sites on SYT7 and DEAF1, partially mediating the effect of prePregBMI on BMIz36 (p ≤ 0.01). After cross-validation, a methylation risk score including these two sites could predict the highest quartile of BMIz36 and fat mass (in grams) with area under the curve = 0.72 (95% CI: 0.58-0.85) and area under the curve = 0.71 (95% CI: 0.58-0.85), respectively.

CONCLUSIONS

CB DNAm at birth may partially mediate effects of prePregBMI on early childhood BMIz36, supporting its plausible role in influencing individual future obesity risk.

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.

Ancestrally diverse genome-wide association analysis highlights ancestry-specific differences in genetic regulation of plasma protein levels

Fully characterizing the genetic architecture of circulating proteins in multi-ancestry populations provides an unprecedented opportunity to gain insights into the etiology of complex diseases. We characterized and contrasted the genetic associations of plasma proteomes in 9,455 participants of European and African (19.8%) ancestry from the Atherosclerosis Risk in Communities Study. Of 4,651 proteins, 1,408 and 2,565 proteins had protein-quantitative trait loci (pQTLs) identified in African and European ancestry respectively, and twelve unreported potentially causal protein-disease relationships were identified. Shared pQTLs across the two ancestries were detected in 1,113 aptamer-region pairs pQTLs, where 53 of them were not previously reported (all trans pQTLs). Sixteen unique protein-cardiovascular trait pairs were colocalized in both European and African ancestry with the same candidate causal variants. Our systematic cross-ancestry comparison provided a reliable set of pQTLs, highlighted the shared and distinct genetic architecture of proteome in two ancestries, and demonstrated possible biological mechanisms underlying complex diseases.

Population structure and selective signature of Kirghiz sheep by Illumina Ovine SNP50 BeadChip

Objective

By assessing the genetic diversity and associated selective traits of Kirghiz sheep (KIR), we aim to uncover the mechanisms that contribute to sheep's adaptability to the Pamir Plateau environment.

Methods

This study utilized Illumina Ovine SNP50 BeadChip data from KIR residing in the Pamir Plateau, Qira Black sheep (QBS) inhabiting the Taklamakan Desert, and commonly introduced breeds including Dorper sheep (DOR), Suffolk sheep (SUF), and Hu sheep (HU). The data was analyzed using principal component analysis, phylogenetic analysis, population admixture analysis, kinship matrix analysis, linkage disequilibrium analysis, and selective signature analysis. We employed four methods for selective signature analysis: fixation index (Fst), cross-population extended homozygosity (XP-EHH), integrated haplotype score (iHS), and nucleotide diversity (Pi). These methods aim to uncover the genetic mechanisms underlying the germplasm resources of Kirghiz sheep, enhance their production traits, and explore their adaptation to challenging environmental conditions.

Results

The test results unveiled potential selective signals associated with adaptive traits and growth characteristics in sheep under harsh environmental conditions, and annotated the corresponding genes accordingly. These genes encompass various functionalities such as adaptations associated with plateau, cold, and arid environment (ETAA1, UBE3D, TLE4, NXPH1, MAT2B, PPARGC1A, VEGFA, TBX15 and PLXNA4), wool traits (LMO3, TRPS1, EPHA5), body size traits (PLXNA2, EFNA5), reproductive traits (PPP3CA, PDHA2, NTRK2), and immunity (GATA3).

Conclusion

Our study identified candidate genes associated with the production traits and adaptation to the harsh environment of the Pamir Plateau in Kirghiz sheep. These findings provide valuable resources for local sheep breeding programs. The objective of this study is to offer valuable insights for the sustainable development of the Kirghiz sheep industry.

The dual role of SUSD2 in cancer development

Sushi domain-containing protein 2 (SUSD2, also known as the complement control protein domain) is a representative and vital protein in the SUSD protein family involved in many physiological and pathological processes beyond complement regulation. Cancer is one of the leading causes of death worldwide. The complex role of SUSD2 in tumorigenesis and cancer progression has raised increasing concerns. Studies suggest that SUSD2 has different regulatory tendencies among different tumors and exerts its biological effects in a cancer type-specific manner; for instance, it has oncogenic effects on breast cancer, gastric cancer, and glioma and has tumor-suppression effects on lung cancer, bladder cancer, and colon cancer. Moreover, SUSD2 can be regulated by noncoding RNAs, its promoter methylation and other molecules, such as Galectin-1 (Gal-1), tropomyosin alpha-4 chain (TPM4), and p63. The therapeutic implications of targeting SUSD2 have already been preliminarily revealed in some malignancies, including melanoma, colon cancer, and breast cancer. This article reviews the role and regulatory mechanisms of SUSD2 in cancer development, as well as its structure and distribution. We hope that this review will advance the understanding of SUSD2 as a diagnostic and/or prognostic biomarker and provide new avenues for the development of novel cancer therapies.

Human genetic variation determines 24-hour rhythmic gene expression and disease risk

24-hour biological rhythms are essential to maintain physiological homeostasis. Disruption of these rhythms increases the risks of multiple diseases. The biological rhythms are known to have a genetic basis formed by core clock genes, but how individual genetic variation shapes the oscillating transcriptome and contributes to human chronophysiology and disease risk is largely unknown. Here, we mapped interactions between temporal gene expression and genotype to identify quantitative trait loci (QTLs) contributing to rhythmic gene expression. These newly identified QTLs were termed as rhythmic QTLs (rhyQTLs), which determine previously unappreciated rhythmic genes in human subpopulations with specific genotypes. Functionally, rhyQTLs and their associated rhythmic genes contribute extensively to essential chronophysiological processes, including bile acid and lipid metabolism. The identification of rhyQTLs sheds light on the genetic mechanisms of gene rhythmicity, offers mechanistic insights into variations in human disease risk, and enables precision chronotherapeutic approaches for patients.

Association of DNA Methylation with Infant Birth Weight in Women with Gestational Diabetes

Offspring exposed to gestational diabetes mellitus (GDM) exhibit greater adiposity at birth. This early-life phenotype may increase offspring risk of developing obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease later in life. Infants born to women with GDM have a dysregulation of several hormones, cytokines, and growth factors related to fetal fat mass growth. One of the molecular mechanisms of GDM influencing these factors is epigenetic alterations, such as DNA methylation (DNAm). This review will examine the role of DNAm as a potential biomarker for monitoring fetal growth during pregnancy in women with GDM. This information is relevant since it may provide useful new biomarkers for the diagnosis, prognosis, and treatment of fetal growth and its later-life health consequences.

Genetic Associations with Placental Proteins in Maternal Serum Identify Biomarkers for Hypertension in Pregnancy

Background

Preeclampsia is a complex syndrome that accounts for considerable maternal and perinatal morbidity and mortality. Despite its prevalence, no effective disease-modifying therapies are available. Maternal serum placenta-derived proteins have been in longstanding use as markers of risk for aneuploidy and placental dysfunction, but whether they have a causal contribution to preeclampsia is unknown.

Objective

We aimed to investigate the genetic regulation of serum placental proteins in early pregnancy and their potential causal links with preeclampsia and gestational hypertension.

Study design

This study used a nested case-control design with nulliparous women enrolled in the nuMoM2b study from eight clinical sites across the United States between 2010 and 2013. The first- and second-trimester serum samples were collected, and nine proteins were measured, including vascular endothelial growth factor (VEGF), placental growth factor, endoglin, soluble fms-like tyrosine kinase-1 (sFlt-1), a disintegrin and metalloproteinase domain-containing protein 12 (ADAM-12), pregnancy-associated plasma protein A, free beta-human chorionic gonadotropin, inhibin A, and alpha-fetoprotein. This study used genome-wide association studies to discern genetic influences on these protein levels, treating proteins as outcomes. Furthermore, Mendelian randomization was used to evaluate the causal effects of these proteins on preeclampsia and gestational hypertension, and their further causal relationship with long-term hypertension, treating proteins as exposures.

Results

A total of 2,352 participants were analyzed. We discovered significant associations between the pregnancy zone protein locus and concentrations of ADAM-12 (rs6487735, P= 3.03×10 -22 ), as well as between the vascular endothelial growth factor A locus and concentrations of both VEGF (rs6921438, P= 7.94×10 -30 ) and sFlt-1 (rs4349809, P= 2.89×10 -12 ). Our Mendelian randomization analyses suggested a potential causal association between first-trimester ADAM-12 levels and gestational hypertension (odds ratio=0.78, P= 8.6×10 -4 ). We also found evidence for a potential causal effect of preeclampsia (odds ratio=1.75, P =8.3×10 -3 ) and gestational hypertension (odds ratio=1.84, P =4.7×10 -3 ) during the index pregnancy on the onset of hypertension 2-7 years later. The additional mediation analysis indicated that the impact of ADAM-12 on postpartum hypertension could be explained in part by its indirect effect through gestational hypertension (mediated effect=-0.15, P= 0.03).

Conclusions

Our study discovered significant genetic associations with placental proteins ADAM-12, VEGF, and sFlt-1, offering insights into their regulation during pregnancy. Mendelian randomization analyses demonstrated evidence of potential causal relationships between the serum levels of placental proteins, particularly ADAM-12, and gestational hypertension, potentially informing future prevention and treatment investigations.

A genome-wide association study on growth traits of Korean commercial pig breeds using Bayesian methods

OBJECTIVE

This study aims to identify the significant regions and candidate genes of growth-related traits (adjusted backfat thickness [ABF], average daily gain [ADG], and days to 90 kg [DAYS90]) in Korean commercial GGP pig (Duroc, Landrace, and Yorkshire) populations.

METHODS

A genome-wide association study (GWAS) was performed using single-nucleotide polymorphism (SNP) markers for imputation to Illumina PorcineSNP60. The BayesB method was applied to calculate thresholds for the significance of SNP markers. The identified windows were considered significant if they explained ≥1% genetic variance.

RESULTS

A total of 28 window regions were related to genetic growth effects. Bayesian GWAS revealed 28 significant genetic regions including 52 informative SNPs associated with growth traits (ABF, ADG, DAYS90) in Duroc, Landrace, and Yorkshire pigs, with genetic variance ranging from 1.00% to 5.46%. Additionally, 14 candidate genes with previous functional validation were identified for these traits.

CONCLUSION

The identified SNPs within these regions hold potential value for future markerassisted or genomic selection in pig breeding programs. Consequently, they contribute to an improved understanding of genetic architecture and our ability to genetically enhance pigs. SNPs within the identified regions could prove valuable for future marker-assisted or genomic selection in pig breeding programs.

Dissecting the shared genetic architecture between Alzheimer's disease and frailty: a cross-trait meta-analyses of genome-wide association studies

Introduction: Frailty is the most common medical condition affecting the aging population, and its prevalence increases in the population aged 65 or more. Frailty is commonly diagnosed using the frailty index (FI) or frailty phenotype (FP) assessments. Observational studies have indicated the association of frailty with Alzheimer's disease (AD). However, the shared genetic and biological mechanism of these comorbidity has not been studied. Methods: To assess the genetic relationship between AD and frailty, we examined it at single nucleotide polymorphism (SNP), gene, and pathway levels. Results: Overall, 16 genome-wide significant loci (15 unique loci) (p meta-analysis < 5 × 10-8) and 22 genes (21 unique genes) were identified between AD and frailty using cross-trait meta-analysis. The 8 shared loci implicated 11 genes: CLRN1-AS1, CRHR1, FERMT2, GRK4, LINC01929, LRFN2, MADD, RP11-368P15.1, RP11-166N6.2, RNA5SP459, and ZNF652 between AD and FI, and 8 shared loci between AD and FFS implicated 11 genes: AFF3, C1QTNF4, CLEC16A, FAM180B, FBXL19, GRK4, LINC01104, MAD1L1, RGS12, ZDHHC5, and ZNF521. The loci 4p16.3 (GRK4) was identified in both meta-analyses. The colocalization analysis supported the results of our meta-analysis in these loci. The gene-based analysis revealed 80 genes between AD and frailty, and 4 genes were initially identified in our meta-analyses: C1QTNF4, CRHR1, MAD1L1, and RGS12. The pathway analysis showed enrichment for lipoprotein particle plasma, amyloid fibril formation, protein kinase regulator, and tau protein binding. Conclusion: Overall, our results provide new insights into the genetics of AD and frailty, suggesting the existence of non-causal shared genetic mechanisms between these conditions.

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.

A mammalian-specific Alex3/Gαq protein complex regulates mitochondrial trafficking, dendritic complexity, and neuronal survival

Mitochondrial dynamics and trafficking are essential to provide the energy required for neurotransmission and neural activity. We investigated how G protein-coupled receptors (GPCRs) and G proteins control mitochondrial dynamics and trafficking. The activation of Gαq inhibited mitochondrial trafficking in neurons through a mechanism that was independent of the canonical downstream PLCβ pathway. Mitoproteome analysis revealed that Gαq interacted with the Eutherian-specific mitochondrial protein armadillo repeat-containing X-linked protein 3 (Alex3) and the Miro1/Trak2 complex, which acts as an adaptor for motor proteins involved in mitochondrial trafficking along dendrites and axons. By generating a CNS-specific Alex3 knockout mouse line, we demonstrated that Alex3 was required for the effects of Gαq on mitochondrial trafficking and dendritic growth in neurons. Alex3-deficient mice had altered amounts of ER stress response proteins, increased neuronal death, motor neuron loss, and severe motor deficits. These data revealed a mammalian-specific Alex3/Gαq mitochondrial complex, which enables control of mitochondrial trafficking and neuronal death by GPCRs.

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

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

Uncovering the architecture of selection in two Bos taurus cattle breeds

Directional selection alters the genome via hard sweeps, soft sweeps, and polygenic selection. However, mapping polygenic selection is difficult because it does not leave clear signatures on the genome like a selective sweep. In populations with temporally stratified genotypes, the Generation Proxy Selection Mapping (GPSM) method identifies variants associated with generation number (or appropriate proxy) and thus variants undergoing directional allele frequency changes. Here, we use GPSM on two large datasets of beef cattle to detect associations between an animal's generation and 11 million imputed SNPs. Using these datasets with high power and dense mapping resolution, GPSM detected a total of 294 unique loci actively under selection in two cattle breeds. We observed that GPSM has a high power to detect selection in the very recent past (<10 years), even when allele frequency changes are small. Variants identified by GPSM reside in genomic regions associated with known breed-specific selection objectives, such as fertility and maternal ability in Red Angus, and carcass merit and coat color in Simmental. Over 60% of the selected loci reside in or near (<50 kb) annotated genes. Using haplotype-based and composite selective sweep statistics, we identify hundreds of putative selective sweeps that likely occurred earlier in the evolution of these breeds; however, these sweeps have little overlap with recent polygenic selection. This makes GPSM a complementary approach to sweep detection methods when temporal genotype data are available. The selected loci that we identify across methods demonstrate the complex architecture of selection in domesticated cattle.

Overexpression of Plg-RKT protects against adipose dysfunction and dysregulation of glucose homeostasis in diet-induced obese mice

The plasminogen receptor, Plg-RKT, is a unique cell surface receptor that is broadly expressed in cells and tissues throughout the body. Plg-RKT localizes plasminogen on cell surfaces and promotes its activation to the broad-spectrum serine protease, plasmin. In this study, we show that overexpression of Plg-RKT protects mice from high fat diet (HFD)-induced adipose and metabolic dysfunction. During the first 10 weeks on the HFD, the body weights of mice that overexpressed Plg-RKT (Plg-RKT-OEX) were lower than those of control mice (CagRosaPlgRKT). After 10 weeks on the HFD, CagRosaPlgRKT and Plg-RKT-OEX mice had similar body weights. However, Plg-RKT-OEX mice showed a more metabolically favourable body composition phenotype. Plg-RKT-OEX mice also showed improved glucose tolerance and increased insulin sensitivity. We found that the improved metabolic functions of Plg-RKT-OEX mice were mechanistically associated with increased energy expenditure and activity, decreased proinflammatory adipose macrophages and decreased inflammation, elevated brown fat thermogenesis, and higher expression of adipose PPARγ and adiponectin. These findings suggest that Plg-RKT signalling promotes healthy adipose function via multiple mechanisms to defend against obesity-associated adverse metabolic phenotypes.

Development of genome-wide association studies on childhood obesity and its indicators: A scoping review and enrichment analysis

BACKGROUND

The progress of genome-wide association studies (GWAS) in childhood obesity and its indicators is challenging and there are differences in genetic studies in children and adults.

OBJECTIVE

To illustrate the history of the development of GWAS in childhood obesity and its indicators and summarize the GWAS loci.

METHODS

PubMed, Web of Science, Embase and GWAS Catalog databases were systematically searched from 1 January 2005 to 19 October 2022 for literature related to GWAS of childhood BMI, body fatness and obesity. The nearest genes were used as positional genes to perform gene set analyses including the enrichment of pathways, tissues and diseases.

RESULTS

Twenty articles published between 2007 and 2021 were included in this scoping review, which identified 116 SNPs reaching genome-wide significance with childhood BMI (n = 50), body fatness (n = 31) and obesity (n = 35). The study populations were European in 16 studies, non-European in three studies (1 East Asian; 1 American; 1 Mexican) and trans-ancestry in one study. Several enriched pathways, tissues and diseases were identified through enrichment analysis of genes associated with childhood obesity and its indicators.

CONCLUSIONS

The innovations in tools and methods enable GWAS to better explore the genetic characteristics of obesity in children and adolescents. However, the number of GWAS in American, Asian and African populations is limited compared to the European population.

Transcriptome Changes and Metabolic Outcomes After Bariatric Surgery in Adults With Obesity and Type 2 Diabetes

Context

Bariatric surgery has been shown to be effective in inducing complete remission of type 2 diabetes in adults with obesity. However, its efficacy in achieving complete diabetes remission remains variable and difficult to predict before surgery.

Objective

We aimed to characterize bariatric surgery-induced transcriptome changes associated with diabetes remission and the predictive role of the baseline transcriptome.

Methods

We performed a whole-genome microarray in peripheral mononuclear cells at baseline (before surgery) and 2 and 12 months after bariatric surgery in a prospective cohort of 26 adults with obesity and type 2 diabetes. We applied machine learning to the baseline transcriptome to identify genes that predict metabolic outcomes. We validated the microarray expression profile using a real-time polymerase chain reaction.

Results

Sixteen patients entered diabetes remission at 12 months and 10 did not. The gene-expression analysis showed similarities and differences between responders and nonresponders. The difference included the expression of critical genes (SKT4, SIRT1, and TNF superfamily), metabolic and signaling pathways (Hippo, Sirtuin, ARE-mediated messenger RNA degradation, MSP-RON, and Huntington), and predicted biological functions (β-cell growth and proliferation, insulin and glucose metabolism, energy balance, inflammation, and neurodegeneration). Modeling the baseline transcriptome identified 10 genes that could hypothetically predict the metabolic outcome before bariatric surgery.

Conclusion

The changes in the transcriptome after bariatric surgery distinguish patients in whom diabetes enters complete remission from those who do not. The baseline transcriptome can contribute to the prediction of bariatric surgery-induced diabetes remission preoperatively.

The influence of gut microbiota on circulating inflammatory cytokines and host: A Mendelian randomization study with meta-analysis

AIMS

The gut microbiota has been found to be altered in different inflammatory disorders, but its involvement in the regulation of inflammatory cytokines remains unclear. Therefore, this study aimed to investigate the impacts of gut microbiota on circulating inflammatory cytokines and their potential roles in host diseases.

MAIN METHODS

Two-sample Mendelian randomization (MR) analyses were conducted using summary-level data from genome-wide association studies (GWAS) to identify significant causal associations between 196 gut microbiota and 41 inflammatory cytokines. Meta-analysis was applied to test the robustness of the results. Enrichment analyses of identified cytokines were further utilized to infer the effects of gut microbiota on the host.

KEY FINDINGS

The MR analyses and meta-analyses identified the following significant causal associations: phylum Euryarchaeota on interleukin-2 (IL-2) (βIVW = 0.085, P = 1.5 × 10-2) and interleukin-8 (IL-8) (βIVW = 0.065, P = 4.1 × 10-2), phylum Tenericutes and class Mollicutes on macrophage inflammatory protein 1a (MIP1a) (βIVW = -0.142, P = 7.0 × 10-3), class Bacilli on hepatocyte growth factor (HGF) (βIVW = -0.106, P = 2.5 × 10-2), order Enterobacteriales on monocyte chemoattractant protein-1 (MCP1) (βIVW = 0.182, P = 1.8 × 10-2), and genus Lachnospiraceae NC2004 group on TNF-related apoptosis-inducing ligand (TRAIL) (βIVW = -0.207, P = 6.0 × 10-4). Enrichment analyses suggested that phylum Euryarchaeota and order Enterobacteriales might be risk factors for certain autoimmune diseases and neoplasms, while the phylum Tenericutes may have a protective effect.

SIGNIFICANCE

This study represents the first evidence confirming the causal effect of specific gut microbial taxa on circulating inflammatory cytokines and sheds light on their potential roles in the development and progression of various host diseases.

A longitudinal genome-wide association study of bone mineral density mean and variability in the UK Biobank

Bone mineral density (BMD) is an essential predictor of osteoporosis and fracture. We conducted a genome-wide trajectory analysis of BMD and analyzed the BMD change.

PURPOSE

This study aimed to identify the genetic architecture and potential biomarkers of BMD.

METHODS

Our analysis included 141,261 white participants from the UK Biobank with heel BMD phenotype data. We used a genome-wide trajectory analysis tool, TrajGWAS, to conduct a genome-wide association study (GWAS) of BMD. Then, we validated our findings in previously reported BMD genetic associations and performed replication analysis in the Asian participants. Finally, gene-set enrichment analysis (GSEA) of the identified candidate genes was conducted using the FUMA platform.

RESULTS

A total of 52 genes associated with BMD trajectory mean were identified, of which the top three significant genes were WNT16 (P = 1.31 × 10-126), FAM3C (P = 4.18 × 10-108), and CPED1 (P = 8.48 × 10-106). In addition, 114 genes associated with BMD within-subject variability were also identified, such as AC092079.1 (P = 2.72 × 10-13) and RGS7 (P = 4.72 × 10-10). The associations for these candidate genes were confirmed in the previous GWASs and replicated successfully in the Asian participants. GSEA results of BMD change identified multiple GO terms related to skeletal development, such as SKELETAL SYSTEM DEVELOPMENT (Padjusted = 2.45 × 10-3) and REGULATION OF OSSIFICATION (Padjusted = 2.45 × 10-3). KEGG enrichment analysis showed that these genes were mainly enriched in WNT SIGNALING PATHWAY.

CONCLUSIONS

Our findings indicated that the CPED1-WNT16-FAM3C locus plays a significant role in BMD mean trajectories and identified several novel candidate genes contributing to BMD within-subject variability, facilitating the understanding of the genetic architecture of BMD.

A new SPRING in lipid metabolism

PURPOSE OF REVIEW

The SREBP transcription factors are master regulators of lipid homeostasis owing to their role in controlling cholesterol and fatty acid metabolism. The core machinery required to promote their trafficking and proteolytic activation has been established close to 20 years ago. In this review, we summarize the current understanding of a newly identified regulator of SREBP signaling, SPRING (formerly C12ORF49), its proposed mechanism of action, and its role in lipid metabolism.

RECENT FINDINGS

Using whole-genome functional genetic screens we, and others, have recently identified SPRING as a novel regulator of SREBP signaling. SPRING is a Golgi-resident single-pass transmembrane protein that is required for proteolytic activation of SREBPs in this compartment. Mechanistic studies identified regulation of S1P, the protease that cleaves SREBPs, and control of retrograde trafficking of the SREBP chaperone SCAP from the Golgi to the ER as processes requiring SPRING. Emerging studies suggest an important role for SPRING in regulating circulating and hepatic lipid levels in mice and potentially in humans.

SUMMARY

Current studies support the notion that SPRING is a novel component of the core SREBP-activating machinery. Additional studies are warranted to elucidate its role in cellular and systemic lipid metabolism.

Dietary Sugar Research in Preschoolers: Methodological, Genetic, and Cardiometabolic Considerations

Excess dietary sugar intake increases the risk of unhealthy weight gain, an important cardiometabolic risk factor in children. To further our understanding of this relationship, we performed a narrative review using two approaches. First, research examining dietary sugar intake, its associations with cardiometabolic health, impact of genetics on sweet taste perception and intake, and how genetics moderates the association of dietary sugar intake and cardiometabolic risk factors in preschool-aged children 1.5-5 years old is reviewed. Second, methodological considerations for collecting and analyzing dietary intake of sugar, genetic information, and markers of cardiometabolic health among young children are provided. Our key recommendations include the following for researchers: (1) Further longitudinal research on sugar intake and cardiometabolic risk factors is warranted to inform policy decisions and guidelines for healthy eating in preschool-aged children. (2) Consistency in sugar definitions is needed across research studies to aid with comparisons of results. (3) Select dietary collection tools specific to each study's aim and sugar definition(s). (4) Limit subjectivity of dietary assessment tools as this impacts interpretation of study results. (5) Choose non-invasive biomarkers of cardiometabolic disease until the strengths and limitations of available biomarkers in preschool-aged children are clarified. (6) Select approaches that account for the polygenic nature of cardiometabolic disease such as genome risk scores and genome wide association studies to assess how genetics moderates the relationship between dietary sugar intake and cardiometabolic risk. This review highlights potential recommendations that will support a research environment to help inform policy decisions and healthy eating policies to reduce cardiometabolic risk in young children.

Genomic Scan for Runs of Homozygosity and Selective Signature Analysis to Identify Candidate Genes in Large White Pigs

Large White pigs are extensively utilized in China for their remarkable characteristics of rapid growth and the high proportion of lean meat. The economic traits of pigs, comprising reproductive and meat quality traits, play a vital role in swine production. In this study, 2295 individuals, representing three different genetic backgrounds Large White pig populations were used: 500 from the Canadian line, 295 from the Danish line, and 1500 from the American line. The GeneSeek 50K GGP porcine HD array was employed to genotype the three pig populations. Firstly, genomic selective signature regions were identified using the pairwise fixation index (FST) and locus-specific branch length (LSBL). By applying a top 1% threshold for both parameters, a total of 888 candidate selective windows were identified, harbouring 1571 genes. Secondly, the investigation of regions of homozygosity (ROH) was performed utilizing the PLINK software. In total, 25 genomic regions exhibiting a high frequency of ROHs were detected, leading to the identification of 1216 genes. Finally, the identified potential functional genes from candidate genomic regions were annotated, and several important candidate genes associated with reproductive traits (ADCYAP1, U2, U6, CETN1, Thoc1, Usp14, GREB1L, FGF12) and meat quality traits (MiR-133, PLEKHO1, LPIN2, SHANK2, FLVCR1, MYL4, SFRP1, miR-486, MYH3, STYX) were identified. The findings of this study provide valuable insights into the genetic basis of economic traits in Large White pigs and may have potential use in future pig breeding programs.

Development and verification of a combined diagnostic model for primary Sjögren's syndrome by integrated bioinformatics analysis and machine learning

Primary Sjögren's syndrome (pSS) is a chronic, systemic autoimmune disease mostly affecting the exocrine glands. This debilitating condition is complex and specific treatments remain unavailable. There is a need for the development of novel diagnostic models for early screening. Four gene profiling datasets were downloaded from the Gene Expression Omnibus database. The 'limma' software package was used to identify differentially expressed genes (DEGs). A random forest-supervised classification algorithm was used to screen disease-specific genes, and three machine learning algorithms, including artificial neural networks (ANN), random forest (RF), and support vector machines (SVM), were used to build a pSS diagnostic model. The performance of the model was measured using its area under the receiver operating characteristic curve. Immune cell infiltration was investigated using the CIBERSORT algorithm. A total of 96 DEGs were identified. By utilizing a RF classifier, a set of 14 signature genes that are pivotal in transcription regulation and disease progression in pSS were identified. Through the utilization of training and testing datasets, diagnostic models for pSS were successfully designed using ANN, RF, and SVM, resulting in AUCs of 0.972, 1.00, and 0.9742, respectively. The validation set yielded AUCs of 0.766, 0.8321, and 0.8223. It was the RF model that produced the best prediction performance out of the three models tested. As a result, an early predictive model for pSS was successfully developed with high diagnostic performance, providing a valuable resource for the screening and early diagnosis of pSS.

The genomics of visuospatial neurocognition in obsessive-compulsive disorder: A preliminary GWAS

BACKGROUND

The study of Obsessive-Compulsive Disorder (OCD) genomics has primarily been tackled by Genome-wide association studies (GWAS), which have encountered troubles in identifying replicable single nucleotide polymorphisms (SNPs). Endophenotypes have emerged as a promising avenue of study in trying to elucidate the genomic bases of complex traits such as OCD.

METHODS

We analyzed the association of SNPs across the whole genome with the construction of visuospatial information and executive performance through four neurocognitive variables assessed by the Rey-Osterrieth Complex Figure Test (ROCFT) in a sample of 133 OCD probands. Analyses were performed at SNP- and gene-level.

RESULTS

No SNP reached genome-wide significance, although there was one SNP almost reaching significant association with copy organization (rs60360940; P = 9.98E-08). Suggestive signals were found for the four variables at both SNP- (P < 1E-05) and gene-levels (P < 1E-04). Most of the suggestive signals pointed to genes and genomic regions previously associated with neurological function and neuropsychological traits.

LIMITATIONS

Our main limitations were the sample size, which was limited to identify associated signals at a genome-wide level, and the composition of the sample, more representative of rather severe OCD cases than a population-based OCD sample with a broad severity spectrum.

CONCLUSIONS

Our results suggest that studying neurocognitive variables in GWAS would be more informative on the genetic basis of OCD than the classical case/control GWAS, facilitating the genetic characterization of OCD and its different clinical profiles, the development of individualized treatment approaches, and the improvement of prognosis and treatment response.

Omics biomarkers and an approach for their practical implementation to delineate health status for personalized nutrition strategies

Personalized nutrition (PN) has gained much attention as a tool for empowerment of consumers to promote changes in dietary behavior, optimizing health status and preventing diet related diseases. Generalized implementation of PN faces different obstacles, one of the most relevant being metabolic characterization of the individual. Although omics technologies allow for assessment the dynamics of metabolism with unprecedented detail, its translatability as affordable and simple PN protocols is still difficult due to the complexity of metabolic regulation and to different technical and economical constrains. In this work, we propose a conceptual framework that considers the dysregulation of a few overarching processes, namely Carbohydrate metabolism, lipid metabolism, inflammation, oxidative stress and microbiota-derived metabolites, as the basis of the onset of several non-communicable diseases. These processes can be assessed and characterized by specific sets of proteomic, metabolomic and genetic markers that minimize operational constrains and maximize the information obtained at the individual level. Current machine learning and data analysis methodologies allow the development of algorithms to integrate omics and genetic markers. Reduction of dimensionality of variables facilitates the implementation of omics and genetic information in digital tools. This framework is exemplified by presenting the EU-Funded project PREVENTOMICS as a use case.

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.

A genome-wide association study identifies a possible role for cannabinoid signalling in the pathogenesis of diabetic kidney disease

Diabetic kidney disease (DKD), also known as diabetic nephropathy, is the leading cause of renal impairment and end-stage renal disease. Patients with diabetes are at risk for DKD because of poor control of their blood glucose, as well as nonmodifiable risk factors including age, ethnicity, and genetics. This genome-wide association study (GWAS) was conducted for the first time in the Emirati population to investigate possible genetic factors associated with the development and progression of DKD. We included data on 7,921,925 single nucleotide polymorphism (SNPs) in 258 cases of type 2 diabetes mellitus (T2DM) who developed DKD and 938 control subjects with T2DM who did not develop DKD. GWAS suggestive results (P < 1 × 10-5) were further replicated using summary statistics from three cohorts with T2DM-induced DKD (Bio Bank Japan data, UK Biobank, and FinnGen Project data) and T1DM-induced DKD (UK-ROI cohort data from Belfast, UK). When conducting a multiple linear regression model for gene-set analyses, the CNR2 gene demonstrated genome-wide significance at 1.46 × 10-6. SNPs in CNR2 gene, encodes cannabinoid receptor 2 or CB2, were replicated in Japanese samples with the leading SNP rs2501391 showing a Pcombined = 9.3 × 10-7, and odds ratio = 0.67 in association with DKD associated with T2DM, but not with T1DM, without any significant association with T2DM itself. The allele frequencies of our cohort and those of the replication cohorts were in most cases markedly different. In addition, we replicated the association between rs1564939 in the GLRA3 gene and DKD in T2DM (P = 0.016, odds ratio = 0.54 per allele C). Our findings suggest evidence that cannabinoid signalling may be involved in the development of DKD through CB2, which is expressed in different kidney regions and known to be involved in insulin resistance, inflammation, and the development of kidney fibrosis.

The Association of the Polymorphisms in the FUT8-Related Locus with the Plasma Glycosylation in Post-Traumatic Stress Disorder

The molecular underpinnings of post-traumatic stress disorder (PTSD) are still unclear due to the complex interactions of genetic, psychological, and environmental factors. Glycosylation is a common post-translational modification of proteins, and different pathophysiological states, such as inflammation, autoimmune diseases, and mental disorders including PTSD, show altered N-glycome. Fucosyltransferase 8 (FUT8) is the enzyme that catalyzes the addition of core fucose on glycoproteins, and mutations in the FUT8 gene are associated with defects in glycosylation and functional abnormalities. This is the first study that investigated the associations of plasma N-glycan levels with FUT8-related rs6573604, rs11621121, rs10483776, and rs4073416 polymorphisms and their haplotypes in 541 PTSD patients and control participants. The results demonstrated that the rs6573604 T allele was more frequent in the PTSD than in the control participants. Significant associations of plasma N-glycan levels with PTSD and FUT8-related polymorphisms were observed. We also detected associations of rs11621121 and rs10483776 polymorphisms and their haplotypes with plasma levels of specific N-glycan species in both the control and PTSD groups. In carriers of different rs6573604 and rs4073416 genotypes and alleles, differences in plasma N-glycan levels were only found in the control group. These molecular findings suggest a possible regulatory role of FUT8-related polymorphisms in glycosylation, the alternations of which could partially explain the development and clinical manifestation of PTSD.

A critical update on the leptin-melanocortin system

The discovery of leptin in 1994 was an "eureka moment" in the field of neurometabolism that provided new opportunities to better understand the central control of energy balance and glucose metabolism. Rapidly, a prevalent model in the field emerged that pro-opiomelanocortin (POMC) neurons were key in promoting leptin's anorexigenic effects and that the arcuate nucleus of the hypothalamus (ARC) was a key region for the regulation of energy homeostasis. While this model inspired many important discoveries, a growing body of literature indicates that this model is now outdated. In this review, we re-evaluate the hypothalamic leptin-melanocortin model in light of recent advances that directly tackle previous assumptions, with a particular focus on the ARC. We discuss how segregated and heterogeneous these neurons are, and examine how the development of modern approaches allowing spatiotemporal, intersectional, and chemogenetic manipulations of melanocortin neurons has allowed a better definition of the complexity of the leptin-melanocortin system. We review the importance of leptin in regulating glucose homeostasis, but not food intake, through direct actions on ARC POMC neurons. We further highlight how non-POMC, GABAergic neurons mediate leptin's direct effects on energy balance and influence POMC neurons.

Precision Nutrition: Recent Advances in Obesity

"Precision nutrition" is an emerging area of nutrition research that focuses on understanding metabolic variability within and between individuals and helps develop customized dietary plans and interventions to maintain optimal individual health. It encompasses nutritional genomic (gene-nutrient interactions), epigenetic, microbiome, and environmental factors. Obesity is a complex disease that is affected by genetic and environmental factors and thus a relevant target of precision nutrition-based approaches. Recent studies have shown significant associations between obesity phenotypes (body weight, body mass index, waist circumference, and central and regional adiposity) and genetic variants, epigenetic factors (DNA methylation and noncoding RNA), microbial species, and environment (sociodemographics and physical activity). Additionally, studies have also shown that the interactions between genetic variants, microbial metabolites, and epigenetic factors affect energy balance and adiposity. These include variants in FTO, MC4R, PPAR, APOA, and FADS genes, DNA methylation in CpG island regions, and specific miRNAs and microbial species such as Firmicutes, Bacteriodes, Clostridiales, etc. Similarly, studies have shown that microbial metabolites, folate, B-vitamins, and short-chain fatty acids interact with miRNAs to influence obesity phenotypes. With the advent of next-generation sequencing and analytical approaches, the advances in precision nutrition have the potential to lead to new paradigms, which can further lead to interventions or customized treatments specific to individuals or susceptible groups of individuals. This review highlights the recent advances in precision nutrition as applied to obesity and projects the importance of precision nutrition in obesity and weight management.

Effects of Pre-Pregnancy Overweight/Obesity on the Pattern of Association of Hypertension Susceptibility Genes with Preeclampsia

The aim of this study was to explore the effects of pre-pregnancy overweight/obesity on the pattern of association of hypertension susceptibility genes with preeclampsia (PE). Ten single-nucleotide polymorphisms (SNPs) of the 10 genome-wide association studies (GWAS)-significant hypertension/blood pressure (BP) candidate genes were genotyped in 950 pregnant women divided into two cohorts according to their pre-pregnancy body mass index (preBMI): preBMI ≥ 25 (162 with PE and 159 control) and preBMI < 25 (290 with PE and 339 control). The PLINK software package was utilized to study the association (analyzed four genetic models using logistic regression). The functionality of PE-correlated loci was analyzed by performing an in silico database analysis. Two SNP hypertension/BP genes, rs805303 BAG6 (OR: 0.36−0.66) and rs167479 RGL3 (OR: 1.86), in subjects with preBMI ≥ 25 were associated with PE. No association between the studied SNPs and PE in the preBMI < 25 group was determined. Further analysis showed that two PE-associated SNPs are functional (have weighty eQTL, sQTL, regulatory, and missense values) and could be potentially implicated in PE development. In conclusion, this study was the first to discover the modifying influence of overweight/obesity on the pattern of association of GWAS-significant hypertension/BP susceptibility genes with PE: these genes are linked with PE in preBMI ≥ 25 pregnant women and are not PE-involved in the preBMI < 25 group.

Gamma-glutamyl-leucine levels are causally associated with elevated cardio-metabolic risks

Objective

Gamma-glutamyl dipeptides are bioactive peptides involved in inflammation, oxidative stress, and glucose regulation. Gamma-glutamyl-leucine (Gamma-Glu-Leu) has been extensively reported to be associated with the risk of cardio-metabolic diseases, such as obesity, metabolic syndrome, and type 2 diabetes. However, the causality remains to be uncovered. The aim of this study was to explore the causal-effect relationships between Gamma-Glu-Leu and metabolic risk.

Materials and methods

In this study, 1,289 subjects were included from a cross-sectional survey on metabolic syndrome (MetS) in eastern China. Serum Gamma-Glu-Leu levels were measured by untargeted metabolomics. Using linear regressions, a two-stage genome-wide association study (GWAS) for Gamma-Glu-Leu was conducted to seek its instrumental single nucleotide polymorphisms (SNPs). One-sample Mendelian randomization (MR) analyses were performed to evaluate the causality between Gamma-Glu-Leu and the metabolic risk.

Results

Four SNPs are associated with serum Gamma-Glu-Leu levels, including rs12476238, rs56146133, rs2479714, and rs12229654. Out of them, rs12476238 exhibits the strongest association (Beta = -0.38, S.E. = 0.07 in discovery stage, Beta = -0.29, S.E. = 0.14 in validation stage, combined P-value = 1.04 × 10^-8). Each of the four SNPs has a nominal association with at least one metabolic risk factor. Both rs12229654 and rs56146133 are associated with body mass index, waist circumference (WC), the ratio of WC to hip circumference, blood pressure, and triglyceride (5 × 10^-5 < P < 0.05). rs56146133 also has nominal associations with fasting insulin, glucose, and insulin resistance index (5 × 10^-5 < P < 0.05). Using the four SNPs serving as the instrumental SNPs of Gamma-Glu-Leu, the MR analyses revealed that higher Gamma-Glu-Leu levels are causally associated with elevated risks of multiple cardio-metabolic factors except for high-density lipoprotein cholesterol and low-density lipoprotein cholesterol (P > 0.05).

Conclusion

Four SNPs (rs12476238, rs56146133, rs2479714, and rs12229654) may regulate the levels of serum Gamma-Glu-Leu. Higher Gamma-Glu-Leu levels are causally linked to cardio-metabolic risks. Future prospective studies on Gamma-Glu-Leu are required to explain its role in metabolic disorders.

Next-Generation Sequencing and Bioinformatics-Based Protocol for the Full-Length CYP2E1 Gene Polymorphism Analysis

INTRODUCTION

Pharmacogenetics studies provide clinically relevant information on the identified associations between genetic variants and individual variability in drug response, which, in turn, offers great promise for guiding personalized drug therapy and clinical trial design. However, there is a lack of information concerning the evidence-based clinical annotations of specific CYP2E1 genetic variants.

AIM

To design and evaluate the next-generation sequencing-based method for full-length CYP2E1 gene polymorphism analysis.

MATERIALS AND METHODS

Seven gene-specific oligonucleotide primer pairs targeting overlapping CYP2E1 gene fragments spanning all nine gene exons with interleaving introns, untranslated (UTR) and intergenic regions were designed. Human DNA samples (n = 3) were used as a training set to check the primer performance and to optimize the PCR conditions. The effectiveness of the developed target amplification and sequencing protocol was evaluated using the test set comprising human DNA samples (n = 3) obtained from tuberculosis patients. Sequencing data analysis was performed on the Galaxy online-based platform.

RESULTS

The sequencing data quality was sufficient for the detection of genetic variants dispersed throughout the CYP2E1 gene with a high degree of confidence in fully covered regions achieving optimal reading depth of the targeted fragment with high base call accuracy.

CONCLUSION

Developed protocol can be applied in subpopulation-level association studies to determine whether single nucleotide variants (SNVs) or variant combinations from multiple regions of the CYP2E1 gene are of clinical significance.

Polymorphisms of hypertension susceptibility genes as a risk factors of preeclampsia in the Caucasian population of central Russia

INTRODUCTION

The study was designed to assess the effects of hypertension (HT) susceptibility genes polymorphisms in the development of preeclampsia (PE) in Caucasians from Central Russia.

METHODS

PE patients (n = 452) and women control group (n = 498) were genotyped for 10 polymorphisms of HT/blood pressure (BP) susceptibility genes (according to the previously published GWAS in Caucasian populations) including AC026703.1 (rs1173771), HFE (rs1799945), BAG6 (rs805303), PLCE1 (rs932764), OBFC1 (rs4387287), ARHGAP42 (rs633185), CERS5 (rs7302981), ATP2B1 (rs2681472), TBX2 (rs8068318) and RGL3 (rs167479). A logistic regression method was applied to search for associations between SNPs and PE. The relationship between SNP-SNP interactions and PE risk was analyzed by performing MB-MDR.

RESULTS

The rs1799945 gene in HFE significantly independently increased the risk of developing PE (OR = 2.24) and rs805303 in BAG6 was associated with a reduced risk in the occurrence of PE (OR = 0.55-0.78). Among the 10 SNPs examined, nine SNPs were associated with PEs within the 10 most significant SNP-SNP interaction models. Loci rs7302981 CERS5, rs805303 BAG6 and rs932764 PLCE1 contributed to the largest number of epistatic models (50% or more).

DISCUSSION

The present study is the first to report an association between polymorphisms of HT/BP susceptibility genes important for GWAS and the risk of PE in Caucasians from Central Russia. Our pathway-based functional annotation of the PE risk variants highlights the potential regulatory function (epigenetic/eQTL/sQTL/non-synonymous) that nine genetic risk markers and their 115 highly correlated variants exert on 155 genes. The study shows that these genes may function cooperatively in key signaling pathways in PE biology.

A tree-based gene-environment interaction analysis with rare features

Gene-environment (G-E) interaction analysis plays a critical role in understanding and modeling complex diseases. Compared to main-effect-only analysis, it is more seriously challenged by higher dimensionality, weaker signals, and the unique "main effects, interactions" variable selection hierarchy. In joint G-E interaction analysis under which a large number of G factors are analysed in a single model, effort tailored to rare features (e.g., SNPs with low minor allele frequencies) has been limited. Existing investigations on rare features have been mostly focused on marginal analysis, where various data aggregation techniques have been developed, and hypothesis testings have been conducted to identify significant aggregated features. However, such techniques cannot be extended to joint G-E interaction analysis. In this study, building on a very recent tree-based data aggregation technique, which has been developed for main-effect-only analysis, we develop a new G-E interaction analysis approach tailored to rare features. The adopted data aggregation technique allows for more efficient information borrowing from neighboring rare features. Similar to some existing state-of-the-art ones, the proposed approach adopts penalization for variable selection, regularized estimation, and respect of the variable selection hierarchy. Simulation shows that it has more accurate identification of important interactions and main effects than several competing alternatives. In the analysis of NFBC1966 study, the proposed approach leads to findings different from the alternatives and with satisfactory prediction and stability performance.

DNA Methylation in Gestational Diabetes and its Predictive Value for Postpartum Glucose Disturbances

CONTEXT

DNA methylation in the diagnosis of gestational diabetes.

OBJECTIVE

To assess the value of DNA methylation in the diagnosis of gestational diabetes (GDM) and in the prediction of maternal postpartum glucose disturbances.

METHODS

Two-stage observational study performed between July 2006 and December 2010, at University Hospital. Forty-eight randomly selected pregnant women formed the discovery cohort (24 with GDM and 24 controls) and 252 pregnant women (94 with GDM and 158 controls) formed the replication cohort. GDM women were re-evaluated 4 years postpartum. The main outcome measures were GDM, type 2 diabetes or prediabetes at 4 years postpartum.

RESULTS

We identified 3 CpG sites related to LINC00917, TRAPPC9, and LEF1 that were differentially methylated in women with GDM and abnormal glucose tolerance; and sites associated with LINC00917 and TRAPPC9 were independently associated with an abnormal glucose tolerance status 4 years postpartum after controlling for clinical variables. Moreover, the site associated with LINC00917 and the combination of the 3 sites had the highest predictive values.

CONCLUSION

Our results suggest that some of these sites may be implicated in the development of GDM and postpartum abnormal glucose tolerance.

Deciphering signatures of natural selection via deep learning

Identifying genomic regions influenced by natural selection provides fundamental insights into the genetic basis of local adaptation. However, it remains challenging to detect loci under complex spatially varying selection. We propose a deep learning-based framework, DeepGenomeScan, which can detect signatures of spatially varying selection. We demonstrate that DeepGenomeScan outperformed principal component analysis- and redundancy analysis-based genome scans in identifying loci underlying quantitative traits subject to complex spatial patterns of selection. Noticeably, DeepGenomeScan increases statistical power by up to 47.25% under nonlinear environmental selection patterns. We applied DeepGenomeScan to a European human genetic dataset and identified some well-known genes under selection and a substantial number of clinically important genes that were not identified by SPA, iHS, Fst and Bayenv when applied to the same dataset.

The pseudogenes of eukaryotic translation elongation factors (EEFs): Role in cancer and other human diseases

The eukaryotic translation elongation factors (EEFs), i.e. EEF1A1, EEF1A2, EEF1B2, EEF1D, EEF1G, EEF1E1 and EEF2, are coding-genes that play a central role in the elongation step of translation but are often altered in cancer. Less investigated are their pseudogenes. Recently, it was demonstrated that pseudogenes have a key regulatory role in the cell, especially via non-coding RNAs, and that the aberrant expression of ncRNAs has an important role in cancer development and progression. The present review paper, for the first time, collects all that published about the EEFs pseudogenes to create a base for future investigations. For most of them, the studies are in their infancy, while for others the studies suggest their involvement in normal cell physiology but also in various human diseases. However, more investigations are needed to understand their functions in both normal and cancer cells and to define which can be useful biomarkers or therapeutic targets.