Identification of HKDC1 and BACE2 as genes influencing glycemic traits during pregnancy through genome-wide association studies

Metabolomic and genetic architecture of gestational diabetes subtypes

AIMS/HYPOTHESIS

Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes.

METHODS

This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM).

RESULTS

Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM.

CONCLUSIONS/INTERPRETATION

This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Caucasian and Latin American Pregnant Women

The pathophysiology of gestational diabetes mellitus (GDM) comprises clinical and genetic factors. In fact, GDM is associated with several single nucleotide polymorphisms (SNPs). This study aimed to build a prediction model of GDM combining clinical and genetic risk factors. A total of 1588 pregnant women from the San Carlos Cohort participated in the present study, including 1069 (67.3%) Caucasian (CAU) and 519 (32.7%) Latin American (LAT) individuals, and 255 (16.1%) had GDM. The incidence of GDM was similar in both groups (16.1% CAU and 16.0% LAT). Genotyping was performed via IPLEX Mass ARRAY PCR, selecting 110 SNPs based on literature references. SNPs showing the strongest likelihood of developing GDM were rs10830963, rs7651090, and rs1371614 in CAU and rs1387153 and rs9368222 in LAT. Clinical variables, including age, pre-pregnancy body mass index, and fasting plasma glucose (FPG) at 12 gestational weeks, predicted the risk of GDM (AUC 0.648, 95% CI 0.601-0.695 in CAU; AUC 0.688, 95% CI 0.628-9.748 in LAT), and adding SNPs modestly improved prediction (AUC 0.722, 95%CI 0.680-0.764 in CAU; AUC 0.769, 95% CI 0.711-0.826 in LAT). In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women.

New insights into the treatment of polycystic ovary syndrome: HKDC1 promotes the growth of ovarian granulocyte cells by regulating mitochondrial function and glycolysis

Polycystic ovary syndrome (PCOS) is an endocrine disease, and its pathogenesis and treatment are still unclear. Hexokinase domain component 1 (HKDC1) participates in regulating mitochondrial function and glycolysis. However, its role in PCOS development remains unrevealed. Here, female C57BL/6 mice were intraperitoneally injected with dehydroepiandrosterone (DHEA; 60 mg/kg body weight) to establish an in vivo model of PCOS. In vitro, KGN cells, a human ovarian granular cell line, were used to explore the potential mechanisms. DHEA-treated mice exhibited a disrupted estrus cycle, abnormal hormone levels, and insulin resistance. Dysfunction in mitochondria and glycolysis is the main reason for PCOS-related growth inhibition of ovarian granular cells. Here, we found that the structure of mitochondria was impaired, less ATP was generated and more mitochondrial Reactive Oxygen Species were produced in HKDC1-silenced KGN cells. Moreover, HKDC1 knockdown inhibited glucose consumption and decreased the production of glucose-6-phosphate and lactic acid. Conclusively, HKDC1 protects ovarian granulocyte cells from DHEA-related damage at least partly by preserving mitochondrial function and maintaining glycolysis.

HKDC1 enhances the proliferation, migration and glycolysis of pancreatic adenocarcinoma and is linked to immune infiltration

Background: Understanding the molecular mechanisms of pancreatic adenocarcinoma (PAAD) development is vital for treating this disease, as the current prognosis and treatment options are highly discouraging. Objective: This study aimed to examine the involvement of Hexokinase Domain Containing 1 (HKDC1) in the progression of PAAD. Methods: The study utilized bioinformatics techniques to evaluate the relationship between the expression of HKDC1 and clinical characteristics. In vitro experiments were conducted to investigate the molecular mechanisms and biological functions of HKDC1 in PAAD. Results: The findings of this research indicate that the expression of HKDC1 was increased in various types of human cancers, and a significant correlation was observed between elevated HKDC1 expression in PAAD and unfavorable prognosis. According to the findings from univariate and multivariate Cox regression analyses, HKDC1 could potentially serve as a standalone prognostic indicator for individuals diagnosed with PAAD. After performing calculations, we determined that the HKDC1 high-expression group exhibited lower immunologic score and higher ESTIMATE score, indicating a difference in immune infiltration score. In order to validate the expression of HKDC1 in PAAD cell lines, we analyzed the PAAD cell lines through qPCR and protein blotting. The expression of HKDC1 in human PAAD tissues was also detected by western blotting. Additionally, we explored the involvement of HKDC1 in PAAD by conducting experiments such as colony formation, 5-ethynyl-2'-deoxyuridine (EdU), transwell, and wound healing assays. In our study, we discovered that disruption of HKDC1 expression in PAAD cell types resulted in a decrease in cell growth rate and inhibited cell movement and invasion. Conclusion: To conclude, our findings indicate that HKDC1 has a significant impact on the tumor microenvironment (TME) of PAAD and could potentially be a promising target for PAAD treatment, offering fresh perspectives on the management of PAAD.

The Born in Guangzhou Cohort Study enables generational genetic discoveries

Genomic research that targets large-scale, prospective birth cohorts constitutes an essential strategy for understanding the influence of genetics and environment on human health1. Nonetheless, such studies remain scarce, particularly in Asia. Here we present the phase I genome study of the Born in Guangzhou Cohort Study2 (BIGCS), which encompasses the sequencing and analysis of 4,053 Chinese individuals, primarily composed of trios or mother-infant duos residing in South China. Our analysis reveals novel genetic variants, a high-quality reference panel, and fine-scale local genetic structure within BIGCS. Notably, we identify previously unreported East Asian-specific genetic associations with maternal total bile acid, gestational weight gain and infant cord blood traits. Additionally, we observe prevalent age-specific genetic effects on lipid levels in mothers and infants. In an exploratory intergenerational Mendelian randomization analysis, we estimate the maternal putatively causal and fetal genetic effects of seven adult phenotypes on seven fetal growth-related measurements. These findings illuminate the genetic links between maternal and early-life traits in an East Asian population and lay the groundwork for future research into the intricate interplay of genetics, intrauterine exposures and early-life experiences in shaping long-term health.

HKDC1, a target of TFEB, is essential to maintain both mitochondrial and lysosomal homeostasis, preventing cellular senescence

Mitochondrial and lysosomal functions are intimately linked and are critical for cellular homeostasis, as evidenced by the fact that cellular senescence, aging, and multiple prominent diseases are associated with concomitant dysfunction of both organelles. However, it is not well understood how the two important organelles are regulated. Transcription factor EB (TFEB) is the master regulator of lysosomal function and is also implicated in regulating mitochondrial function; however, the mechanism underlying the maintenance of both organelles remains to be fully elucidated. Here, by comprehensive transcriptome analysis and subsequent chromatin immunoprecipitation-qPCR, we identified hexokinase domain containing 1 (HKDC1), which is known to function in the glycolysis pathway as a direct TFEB target. Moreover, HKDC1 was upregulated in both mitochondrial and lysosomal stress in a TFEB-dependent manner, and its function was critical for the maintenance of both organelles under stress conditions. Mechanistically, the TFEB-HKDC1 axis was essential for PINK1 (PTEN-induced kinase 1)/Parkin-dependent mitophagy via its initial step, PINK1 stabilization. In addition, the functions of HKDC1 and voltage-dependent anion channels, with which HKDC1 interacts, were essential for the clearance of damaged lysosomes and maintaining mitochondria-lysosome contact. Interestingly, HKDC1 regulated mitophagy and lysosomal repair independently of its prospective function in glycolysis. Furthermore, loss function of HKDC1 accelerated DNA damage-induced cellular senescence with the accumulation of hyperfused mitochondria and damaged lysosomes. Our results show that HKDC1, a factor downstream of TFEB, maintains both mitochondrial and lysosomal homeostasis, which is critical to prevent cellular senescence.

Genome-wide analysis study of gestational diabetes mellitus and related pathogenic factors in a Chinese Han population

BACKGROUND

Gestational diabetes mellitus (GDM) affects the metabolism of both the mother and fetus during and after pregnancy. Genetic factors are important in the pathogenesis of GDM, and associations vary by ethnicity. However, related studies about the relationship between the susceptibility genes and glucose traits remain limited in China. This study aimed to identify genes associated with GDM susceptibility in Chinese Han women and validate those findings using clinical data during pregnancy and postpartum period.

METHODS

A genome-wide association study (GWAS) of 398 Chinese Han women (199 each with and without GDM) was conducted and associations between single nucleotide polymorphisms (SNPs) and glucose metabolism were identified by searching public databases. Relationships between filtered differential SNPs and glucose metabolism were verified using clinical data during pregnancy. The GDM group were followed up postpartum to evaluate the progression of glucose metabolism.

RESULTS

We identified five novel SNPs with genome-wide significant associations with GDM: rs62069863 in TRPV3 gene and rs2232016 in PRMT6 gene were positive correlated with 1 h plasma glucose (1hPG) and 2 h plasma glucose (2hPG), rs1112718 in HHEX/EXOC6 gene and rs10460009 in LPIN2 gene were positive associated with fasting plasma glucose, 1hPG and 2hPG, rs927316 in GLIS3 gene was negative correlated with 2hPG. Of the 166 GDM women followed up postpartum, rs62069863 in TRPV3 gene was positively associated with fasting insulin, homoeostasis model assessment of insulin resistance.

CONCLUSIONS

The variants of rs62069863 in TRPV3 gene, rs2232016 in PRMT6 gene, rs1112718 in HHEX/EXOC6 gene, rs927316 in GLIS3 gene, and rs10460009 in LPIN2 gene were newly-identified susceptibility loci for GDM in the Chinese Han population. TRPV3 was associated with worse insulin resistance postpartum.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trial Registry.

TRIAL REGISTRATION NUMBER

ChiCTR2100043762. Date of first registration: 28/02/2021.

Proteomics identifies the developmental regulation of HKDC1 in liver of pigs and mice

During the perinatal period, unique metabolic adaptations support energetic requirements for rapid growth. To gain insight into perinatal adaptations, quantitative proteomics was performed comparing the livers of Yorkshire pigs at postnatal day 7 and adult. These data revealed differences in the metabolic control of liver function including significant changes in lipid and carbohydrate metabolic pathways. Newborn livers showed an enrichment of proteins in lipid catabolism and gluconeogenesis concomitant with elevated liver carnitine and acylcarnitines levels. Sugar kinases were some of the most dramatically differentially enriched proteins compared with neonatal and adult pigs including galactokinase 1 (Galk1), ketohexokinase (KHK), hexokinase 1 (HK1), and hexokinase 4 (GCK). Interestingly, hexokinase domain containing 1 (HKDC1), a newly identified fifth hexokinase associated with glucose disturbances in pregnant women, was highly enriched in the liver during the prenatal and perinatal periods and continuously declined throughout postnatal development in pigs and mice. These changes were confirmed via Western blot and mRNA expression. These data provide new insights into the developmental and metabolic adaptations in the liver during the transition from the perinatal period to adulthood in multiple mammalian species.

Liver-specific overexpression of HKDC1 increases hepatocyte size and proliferative capacity

A primary role of the liver is to regulate whole body glucose homeostasis. Glucokinase (GCK) is the main hexokinase (HK) expressed in hepatocytes and functions to phosphorylate the glucose that enters via GLUT transporters to become glucose-6-phosphate (G6P), which subsequently commits glucose to enter downstream anabolic and catabolic pathways. In the recent years, hexokinase domain-containing-1 (HKDC1), a novel 5th HK, has been characterized by our group and others. Its expression profile varies but has been identified to have low basal expression in normal liver but increases during states of stress including pregnancy, nonalcoholic fatty liver disease (NAFLD), and liver cancer. Here, we have developed a stable overexpression model of hepatic HKDC1 in mice to examine its effect on metabolic regulation. We found that HKDC1 overexpression, over time, causes impaired glucose homeostasis in male mice and shifts glucose metabolism towards anabolic pathways with an increase in nucleotide synthesis. Furthermore, we observed these mice to have larger liver sizes due to greater hepatocyte proliferative potential and cell size, which in part, is mediated via yes-associated protein (YAP) signaling.

Aiding Cancer's "Sweet Tooth": Role of Hexokinases in Metabolic Reprogramming

Hexokinases (HKs) convert hexose sugars to hexose-6-phosphate, thus trapping them inside cells to meet the synthetic and energetic demands. HKs participate in various standard and altered physiological processes, including cancer, primarily through the reprogramming of cellular metabolism. Four canonical HKs have been identified with different expression patterns across tissues. HKs 1-3 play a role in glucose utilization, whereas HK 4 (glucokinase, GCK) also acts as a glucose sensor. Recently, a novel fifth HK, hexokinase domain containing 1 (HKDC1), has been identified, which plays a role in whole-body glucose utilization and insulin sensitivity. Beyond the metabolic functions, HKDC1 is differentially expressed in many forms of human cancer. This review focuses on the role of HKs, particularly HKDC1, in metabolic reprogramming and cancer progression.

Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms

INTRODUCTION

Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables.

RESEARCH DESIGN AND METHODS

Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort.

RESULTS

Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively.

CONCLUSIONS

We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

Association of Maternal Metabolites and Metabolite Networks with Newborn Outcomes in a Multi-Ancestry Cohort

The in utero environment is important for newborn size at birth, which is associated with childhood adiposity. We examined associations between maternal metabolite levels and newborn birthweight, sum of skinfolds (SSF), and cord C-peptide in a multinational and multi-ancestry cohort of 2337 mother–newborn dyads. Targeted and untargeted metabolomic assays were performed on fasting and 1 h maternal serum samples collected during an oral glucose tolerance test performed at 24–32 week gestation in women participating in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. Anthropometric measurements were obtained on newborns at birth. Following adjustment for maternal BMI and glucose, per-metabolite analyses demonstrated significant associations between maternal metabolite levels and birthweight, SSF, and cord C-peptide. In the fasting state, triglycerides were positively associated and several long-chain acylcarnitines were inversely associated with birthweight and SSF. At 1 h, additional metabolites including branched-chain amino acids, proline, and alanine were positively associated with newborn outcomes. Network analyses demonstrated distinct clusters of inter-connected metabolites significantly associated with newborn phenotypes. In conclusion, numerous maternal metabolites during pregnancy are significantly associated with newborn birthweight, SSF, and cord C-peptide independent of maternal BMI and glucose, suggesting that metabolites in addition to glucose contribute to newborn size at birth and adiposity.

A review of ancestrality and admixture in Latin America and the caribbean focusing on native American and African descendant populations

Genomics can reveal essential features about the demographic evolution of a population that may not be apparent from historical elements. In recent years, there has been a significant increase in the number of studies applying genomic epidemiological approaches to understand the genetic structure and diversity of human populations in the context of demographic history and for implementing precision medicine. These efforts have traditionally been applied predominantly to populations of European origin. More recently, initiatives in the United States and Africa are including more diverse populations, establishing new horizons for research in human populations with African and/or Native ancestries. Still, even in the most recent projects, the under-representation of genomic data from Latin America and the Caribbean (LAC) is remarkable. In addition, because the region presents the most recent global miscegenation, genomics data from LAC may add relevant information to understand population admixture better. Admixture in LAC started during the colonial period, in the 15th century, with intense miscegenation between European settlers, mainly from Portugal and Spain, with local indigenous and sub-Saharan Africans brought through the slave trade. Since, there are descendants of formerly enslaved and Native American populations in the LAC territory; they are considered vulnerable populations because of their history and current living conditions. In this context, studying LAC Native American and African descendant populations is important for several reasons. First, studying human populations from different origins makes it possible to understand the diversity of the human genome better. Second, it also has an immediate application to these populations, such as empowering communities with the knowledge of their ancestral origins. Furthermore, because knowledge of the population genomic structure is an essential requirement for implementing genomic medicine and precision health practices, population genomics studies may ensure that these communities have access to genomic information for risk assessment, prevention, and the delivery of optimized treatment; thus, helping to reduce inequalities in the Western Hemisphere. Hoping to set the stage for future studies, we review different aspects related to genetic and genomic research in vulnerable populations from LAC countries.

Insight into genetic, biological, and environmental determinants of sexual-dimorphism in type 2 diabetes and glucose-related traits

There is growing evidence that sex and gender differences play an important role in risk and pathophysiology of type 2 diabetes (T2D). Men develop T2D earlier than women, even though there is more obesity in young women than men. This difference in T2D prevalence is attenuated after the menopause. However, not all women are equally protected against T2D before the menopause, and gestational diabetes represents an important risk factor for future T2D. Biological mechanisms underlying sex and gender differences on T2D physiopathology are not yet fully understood. Sex hormones affect behavior and biological changes, and can have implications on lifestyle; thus, both sex-specific environmental and biological risk factors interact within a complex network to explain the differences in T2D risk and physiopathology in men and women. In addition, lifetime hormone fluctuations and body changes due to reproductive factors are generally more dramatic in women than men (ovarian cycle, pregnancy, and menopause). Progress in genetic studies and rodent models have significantly advanced our understanding of the biological pathways involved in the physiopathology of T2D. However, evidence of the sex-specific effects on genetic factors involved in T2D is still limited, and this gap of knowledge is even more important when investigating sex-specific differences during the life course. In this narrative review, we will focus on the current state of knowledge on the sex-specific effects of genetic factors associated with T2D over a lifetime, as well as the biological effects of these different hormonal stages on T2D risk. We will also discuss how biological insights from rodent models complement the genetic insights into the sex-dimorphism effects on T2D. Finally, we will suggest future directions to cover the knowledge gaps.

The genetic risk of gestational diabetes in South Asian women

South Asian women are at increased risk of developing gestational diabetes mellitus (GDM). Few studies have investigated the genetic contributions to GDM risk. We investigated the association of a type 2 diabetes (T2D) polygenic risk score (PRS), on its own, and with GDM risk factors, on GDM-related traits using data from two birth cohorts in which South Asian women were enrolled during pregnancy. 837 and 4372 pregnant South Asian women from the SouTh Asian BiRth CohorT (START) and Born in Bradford (BiB) cohort studies underwent a 75-g glucose tolerance test. PRSs were derived using genome-wide association study results from an independent multi-ethnic study (~18% South Asians). Associations with fasting plasma glucose (FPG); 2 hr post-load glucose (2hG); area under the curve glucose; and GDM were tested using linear and logistic regressions. The population attributable fraction (PAF) of the PRS was calculated. Every 1 SD increase in the PRS was associated with a 0.085 mmol/L increase in FPG ([95% confidence interval, CI=0.07-0.10], p=2.85×10^-20); 0.21 mmol/L increase in 2hG ([95% CI=0.16-0.26], p=5.49×10^-16); and a 45% increase in the risk of GDM ([95% CI=32-60%], p=2.27×10^-14), independent of parental history of diabetes and other GDM risk factors. PRS tertile 3 accounted for 12.5% of the population's GDM alone, and 21.7% when combined with family history. A few weak PRS and GDM risk factors interactions modulating FPG and GDM were observed. Taken together, these results show that a T2D PRS and family history of diabetes are strongly and independently associated with multiple GDM-related traits in women of South Asian descent, an effect that could be modulated by other environmental factors.

Genetic Risk Factors and Gene-Lifestyle Interactions in Gestational Diabetes

Paralleling the increasing trends of maternal obesity, gestational diabetes (GDM) has become a global health challenge with significant public health repercussions. In addition to short-term adverse outcomes, such as hypertensive pregnancy disorders and fetal macrosomia, in the long term, GDM results in excess cardiometabolic morbidity in both the mother and child. Recent data suggest that women with GDM are characterized by notable phenotypic and genotypic heterogeneity and that frequencies of adverse obstetric and perinatal outcomes are different between physiologic GDM subtypes. However, as of yet, GDM treatment protocols do not differentiate between these subtypes. Mapping the genetic architecture of GDM, as well as accurate phenotypic and genotypic definitions of GDM, could potentially help in the individualization of GDM treatment and assessment of long-term prognoses. In this narrative review, we outline recent studies exploring genetic risk factors of GDM and later type 2 diabetes (T2D) in women with prior GDM. Further, we discuss the current evidence on gene-lifestyle interactions in the development of these diseases. In addition, we point out specific research gaps that still need to be addressed to better understand the complex genetic and metabolic crosstalk within the mother-placenta-fetus triad that contributes to hyperglycemia in pregnancy.

Transcriptome and metabolome analyses reveal the regulatory effects of compound probiotics on cecal metabolism in heat-stressed broilers

The effect of compound probiotics on the caecum of broilers under heat stress was assessed in this study. A total of 400 twenty-eight-day-old AA male broilers were randomly divided into 4 treatment groups, where each group had 5 replicates of 20 broilers. The 4 treatment groups were a heat stress control group (broilers receiving a normal diet) and groups HP I, HP II, and HP Ⅲ, consisting of broilers receiving 1, 5, and 10 g of compound probiotics added to each kilogram of feed, respectively. Compound probiotics (L. casei, L. acidophilus, and B. lactis at a ratio of 1:1:2) were used to formulate a compound probiotic powder, with 1 × 10¹⁰ CFU/g of effective viable bacteria. Heat stress treatment was performed at 32 ± 1°C from 9:00 to 17:00 every day from 28 d to 42 d. In d 28 to 42, compared with the HC group, the ADG of broilers in the HP II and III groups was significantly increased (P < 0.05); the ADFI difference between groups was not significant (P > 0.05); the FCR of HP II and III broilers was significantly decreased (P < 0.05); and the FCR of the HP I group increased, but the difference was not significant (P > 0.05). Transcriptome results demonstrate that 665 differential genes were screened (DEGs; upregulated: 366, downregulated: 299). The DEGs were enriched in the B cell receptor signaling pathway, the intestinal immune network for IgA synthesis, the Fc epsilon RI signaling pathway, and other signaling pathways, according to KEGG enrichment analysis. Metabolome analysis identified 92 differential metabolites (DAMs; upregulated: 48, downregulated: 44). KEGG enrichment analysis indicated significant enrichment of Pantothenate and CoA biosynthesis and beta-Alanine metabolism. The combined transcriptome and metabolome analysis revealed that the DAMs and DEGs were mostly involved in beta-alanine metabolism, arginine biosynthesis, amino sugar and nucleotide sugar, and alanine, aspartate, and glutamate metabolism. The results of this study suggest that the addition of compound probiotics has a positive effect on intestinal metabolites, improving the growth performance and contributing to the overall health of broilers under heat stress.

Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

A Clinical Update on Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) traditionally refers to abnormal glucose tolerance with onset or first recognition during pregnancy. GDM has long been associated with obstetric and neonatal complications primarily relating to higher infant birthweight and is increasingly recognized as a risk factor for future maternal and offspring cardiometabolic disease. The prevalence of GDM continues to rise internationally due to epidemiological factors including the increase in background rates of obesity in women of reproductive age and rising maternal age and the implementation of the revised International Association of the Diabetes and Pregnancy Study Groups' criteria and diagnostic procedures for GDM. The current lack of international consensus for the diagnosis of GDM reflects its complex historical evolution and pragmatic antenatal resource considerations given GDM is now 1 of the most common complications of pregnancy. Regardless, the contemporary clinical approach to GDM should be informed not only by its short-term complications but also by its longer term prognosis. Recent data demonstrate the effect of early in utero exposure to maternal hyperglycemia, with evidence for fetal overgrowth present prior to the traditional diagnosis of GDM from 24 weeks' gestation, as well as the durable adverse impact of maternal hyperglycemia on child and adolescent metabolism. The major contribution of GDM to the global epidemic of intergenerational cardiometabolic disease highlights the importance of identifying GDM as an early risk factor for type 2 diabetes and cardiovascular disease, broadening the prevailing clinical approach to address longer term maternal and offspring complications following a diagnosis of GDM.

HIV-1 Tat and cocaine impact astrocytic energy reservoirs and epigenetic regulation by influencing the LINC01133-hsa-miR-4726-5p-NDUFA9 axis

Clinical research has proven that HIV-positive (HIV+) individuals with cocaine abuse show behavioral and neurocognitive disorders. Noncoding RNAs (ncRNAs), such as long ncRNAs (lncRNAs) and microRNAs (miRNAs), are known to regulate gene expression in the contexts of HIV infection and drug abuse. However, there are no specific lncRNA or miRNA biomarkers associated with HIV-1 Transactivator of transcription protein (Tat) and cocaine coexposure. In the central nervous system (CNS), astrocytes are the primary regulators of energy metabolism, and impairment of the astrocytic energy supply can trigger neurodegeneration. The aim of this study was to uncover the roles of lncRNAs and miRNAs in the regulation of messenger RNA (mRNA) targets affected by HIV infection and cocaine abuse. Integrative bioinformatics analysis revealed altered expression of 10 lncRNAs, 10 miRNAs, and 4 mRNA/gene targets in human primary astrocytes treated with cocaine and HIV-1 Tat. We assessed the alterations in the expression of two miRNAs, hsa-miR-2355 and hsa-miR-4726-5p; four lncRNAs, LINC01133, H19, HHIP-AS1, and NOP14-AS1; and four genes, NDUFA9, KYNU, HKDC1, and LIPG. The results revealed interactions in the LINC01133-hsa-miR-4726-5p-NDUFA9 axis that may eventually help us understand cocaine- and HIV-1 Tat-induced astrocyte dysfunction that may ultimately result in neurodegeneration.

The hexokinase "HKDC1" interaction with the mitochondria is essential for liver cancer progression

Liver cancer (LC) is the fourth leading cause of death from cancer malignancies. Recently, a putative fifth hexokinase, hexokinase domain containing 1 (HKDC1), was shown to have significant overexpression in LC compared to healthy liver tissue. Using a combination of in vitro and in vivo tools, we examined the role of HKDC1 in LC development and progression. Importantly, HKDC1 ablation stops LC development and progression via its action at the mitochondria by promoting metabolic reprogramming and a shift of glucose flux away from the TCA cycle. HKDC1 ablation leads to mitochondrial dysfunction resulting in less cellular energy, which cannot be compensated by enhanced glucose uptake. Moreover, we show that the interaction of HKDC1 with the mitochondria is essential for its role in LC progression, and without this interaction, mitochondrial dysfunction occurs. As HKDC1 is highly expressed in LC cells, but only to a minimal degree in hepatocytes under normal conditions, targeting HKDC1, specifically its interaction with the mitochondria, may represent a highly selective approach to target cancer cells in LC.

Network Approaches to Integrate Analyses of Genetics and Metabolomics Data with Applications to Fetal Programming Studies

The integration of genetics and metabolomics data demands careful accounting of complex dependencies, particularly when modelling familial omics data, e.g., to study fetal programming of related maternal–offspring phenotypes. Efforts to identify genetically determined metabotypes using classic genome wide association approaches have proven useful for characterizing complex disease, but conclusions are often limited to a series of variant–metabolite associations. We adapt Bayesian network models to integrate metabotypes with maternal–offspring genetic dependencies and metabolic profile correlations in order to investigate mechanisms underlying maternal–offspring phenotypic associations. Using data from the multiethnic Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, we demonstrate that the strategic specification of ordered dependencies, pre-filtering of candidate metabotypes, incorporation of metabolite dependencies, and penalized network estimation methods clarify potential mechanisms for fetal programming of newborn adiposity and metabolic outcomes. The exploration of Bayesian network growth over a range of penalty parameters, coupled with interactive plotting, facilitate the interpretation of network edges. These methods are broadly applicable to integration of diverse omics data for related individuals.

Enterocyte HKDC1 Modulates Intestinal Glucose Absorption in Male Mice Fed a High-fat Diet

Hexokinase domain containing protein-1, or HKDC1, is a widely expressed hexokinase that is genetically associated with elevated 2-hour gestational blood glucose levels during an oral glucose tolerance test, suggesting a role for HKDC1 in postprandial glucose regulation during pregnancy. Our earlier studies utilizing mice containing global HKDC1 knockdown, as well as hepatic HKDC1 overexpression and knockout, indicated that HKDC1 is important for whole-body glucose homeostasis in aging and pregnancy, through modulation of glucose tolerance, peripheral tissue glucose utilization, and hepatic energy storage. However, our knowledge of the precise role(s) of HKDC1 in regulating postprandial glucose homeostasis under normal and diabetic conditions is lacking. Since the intestine is the main entry portal for dietary glucose, here we have developed an intestine-specific HKDC1 knockout mouse model, HKDC1Int-/-, to determine the in vivo role of intestinal HKDC1 in regulating glucose homeostasis. While no overt glycemic phenotype was observed, aged HKDC1Int-/- mice fed a high-fat diet exhibited an increased glucose excursion following an oral glucose load compared with mice expressing intestinal HKDC1. This finding resulted from glucose entry via the intestinal epithelium and is not due to differences in insulin levels, enterocyte glucose utilization, or reduction in peripheral skeletal muscle glucose uptake. Assessment of intestinal glucose transporters in high-fat diet-fed HKDC1Int-/- mice suggested increased apical GLUT2 expression in the fasting state. Taken together, our results indicate that intestinal HKDC1 contributes to the modulation of postprandial dietary glucose transport across the intestinal epithelium under conditions of enhanced metabolic stress, such as high-fat diet.

Disentangling Signatures of Selection Before and After European Colonization in Latin Americans

Throughout human evolutionary history, large-scale migrations have led to intermixing (i.e., admixture) between previously separated human groups. Although classical and recent work have shown that studying admixture can yield novel historical insights, the extent to which this process contributed to adaptation remains underexplored. Here, we introduce a novel statistical model, specific to admixed populations, that identifies loci under selection while determining whether the selection likely occurred post-admixture or prior to admixture in one of the ancestral source populations. Through extensive simulations, we show that this method is able to detect selection, even in recently formed admixed populations, and to accurately differentiate between selection occurring in the ancestral or admixed population. We apply this method to genome-wide SNP data of ∼4,000 individuals in five admixed Latin American cohorts from Brazil, Chile, Colombia, Mexico, and Peru. Our approach replicates previous reports of selection in the human leukocyte antigen region that are consistent with selection post-admixture. We also report novel signals of selection in genomic regions spanning 47 genes, reinforcing many of these signals with an alternative, commonly used local-ancestry-inference approach. These signals include several genes involved in immunity, which may reflect responses to endemic pathogens of the Americas and to the challenge of infectious disease brought by European contact. In addition, some of the strongest signals inferred to be under selection in the Native American ancestral groups of modern Latin Americans overlap with genes implicated in energy metabolism phenotypes, plausibly reflecting adaptations to novel dietary sources available in the Americas.

Genomics and Epigenomics of Gestational Diabetes Mellitus: Understanding the Molecular Pathways of the Disease Pathogenesis

One of the most common complications during pregnancy is gestational diabetes mellitus (GDM), hyperglycemia that occurs for the first time during pregnancy. The condition is multifactorial, caused by an interaction between genetic, epigenetic, and environmental factors. However, the underlying mechanisms responsible for its pathogenesis remain elusive. Moreover, in contrast to several common metabolic disorders, molecular research in GDM is lagging. It is important to recognize that GDM is still commonly diagnosed during the second trimester of pregnancy using the oral glucose tolerance test (OGGT), at a time when both a fetal and maternal pathophysiology is already present, demonstrating the increased blood glucose levels associated with exacerbated insulin resistance. Therefore, early detection of metabolic changes and associated epigenetic and genetic factors that can lead to an improved prediction of adverse pregnancy outcomes and future cardio-metabolic pathologies in GDM women and their children is imperative. Several genomic and epigenetic approaches have been used to identify the genes, genetic variants, metabolic pathways, and epigenetic modifications involved in GDM to determine its etiology. In this article, we explore these factors as well as how their functional effects may contribute to immediate and future pathologies in women with GDM and their offspring from birth to adulthood. We also discuss how these approaches contribute to the changes in different molecular pathways that contribute to the GDM pathogenesis, with a special focus on the development of insulin resistance.

Whole exome analysis of patients in Japan with hearing loss reveals high heterogeneity among responsible and novel candidate genes

Background

Heterogeneous genetic loci contribute to hereditary hearing loss; more than 100 deafness genes have been identified, and the number is increasing. To detect pathogenic variants in multiple deafness genes, in addition to novel candidate genes associated with hearing loss, whole exome sequencing (WES), followed by analysis prioritizing genes categorized in four tiers, were applied.

Results

Trios from families with non-syndromic or syndromic hearing loss (n = 72) were subjected to WES. After segregation analysis and interpretation according to American College of Medical Genetics and Genomics guidelines, candidate pathogenic variants in 11 previously reported deafness genes (STRC, MYO15A, CDH23, PDZD7, PTPN11, SOX10, EYA1, MYO6, OTOF, OTOG, and ZNF335) were identified in 21 families. Discrepancy between pedigree inheritance and genetic inheritance was present in one family. In addition, eight genes (SLC12A2, BAIAP2L2, HKDC1, SVEP1, CACNG1, GTPBP4, PCNX2, and TBC1D8) were screened as single candidate genes in 10 families.

Conclusions

Our findings demonstrate that four-tier assessment of WES data is efficient and can detect novel candidate genes associated with hearing loss, in addition to pathogenic variants of known deafness genes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02262-4.

Genetic variants for prediction of gestational diabetes mellitus and modulation of susceptibility by a nutritional intervention based on a Mediterranean diet

HYPOTHESIS

Gestational diabetes mellitus (GDM) entails a complex underlying pathogenesis, with a specific genetic background and the effect of environmental factors. This study examines the link between a set of single nucleotide polymorphisms (SNPs) associated with diabetes and the development of GDM in pregnant women with different ethnicities, and evaluates its potential modulation with a clinical intervention based on a Mediterranean diet.

METHODS

2418 women from our hospital-based cohort of pregnant women screened for GDM from January 2015 to November 2017 (the San Carlos Cohort, randomized controlled trial for the prevention of GDM ISRCTN84389045 and real-world study ISRCTN13389832) were assessed for evaluation. Diagnosis of GDM was made according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Genotyping was performed by IPLEX MassARRAY PCR using the Agena platform (Agena Bioscience, SanDiego, CA). 110 SNPs were selected for analysis based on selected literature references. Statistical analyses regarding patients' characteristics were performed in SPSS (Chicago, IL, USA) version 24.0. Genetic association tests were performed using PLINK v.1.9 and 2.0 software. Bioinformatics analysis, with mapping of SNPs was performed using STRING, version 11.5.

RESULTS

Quality controls retrieved a total 98 SNPs and 1573 samples, 272 (17.3%) with GDM and 1301 (82.7%) without GDM. 1104 (70.2%) were Caucasian (CAU) and 469 (29.8%) Hispanic (HIS). 415 (26.4%) were from the control group (CG), 418 (26.6%) from the nutritional intervention group (IG) and 740 (47.0%) from the real-world group (RW). 40 SNPs (40.8%) presented some kind of significant association with GDM in at least one of the genetic tests considered. The nutritional intervention presented a significant association with GDM, regardless of the variant considered. In CAU, variants rs4402960, rs7651090, IGF2BP2; rs1387153, rs10830963, MTNR1B; rs17676067, GLP2R; rs1371614, DPYSL5; rs5215, KCNJ1; and rs2293941, PDX1 were significantly associated with an increased risk of GDM, whilst rs780094, GCKR; rs7607980, COBLL1; rs3746750, SLC17A9; rs6048205, FOXA2; rs7041847, rs7034200, rs10814916, GLIS3; rs3783347, WARS; and rs1805087, MTR, were significantly associated with a decreased risk of GDM, In HIS, variants significantly associated with increased risk of GDM were rs9368222, CDKAL1; rs2302593, GIPR; rs10885122, ADRA2A; rs1387153, MTNR1B; rs737288, BACE2; rs1371614, DPYSL5; and rs2293941, PDX1, whilst rs340874, PROX1; rs2943634, IRS1; rs7041847, GLIS3; rs780094, GCKR; rs563694, G6PC2; and rs11605924, CRY2 were significantly associated with decreased risk for GDM.

CONCLUSIONS

We identify a core set of SNPs in their association with diabetes and GDM in a large cohort of patients from two main ethnicities from a single center. Identification of these genetic variants, even in the setting of a nutritional intervention, deems useful to design preventive and therapeutic strategies.

Melatonin Receptor 1B Genetic Variants on Susceptibility to Gestational Diabetes Mellitus: A Hospital-Based Case-Control Study in Wuhan, Central China

PURPOSE

The aim of the study was to find out the associations of Melatonin receptor 1B (MTNR1B) genetic variants with gestational diabetes mellitus (GDM) in Wuhan of central China.

PATIENTS AND METHODS

A hospital-based case-control study that included 1679 women was carried out to explore the associations of MTNR1B single nucleotide polymorphisms (SNPs) with GDM risk, which were analyzed through logistic regression analysis by adjusting age, pre-pregnancy BMI and family history of diabetes. Multifactor dimensionality reduction was applied to determine gene-gene interactions between SNPs.

RESULTS

MTNR1B SNPs rs10830962, rs10830963, rs1387153, rs7936247 and rs4753426 were significantly associated with GDM risk (P<0.05). The rs10830962/G, rs10830963/G, rs1387153/T, and rs7936247/T were risk variants, whereas rs4753426/T was protective variant for GDM development. Fasting plasma glucose (FPG) and 1h-plasma glucose (PG) were significantly different among genotypes at rs10830962 and rs10830963, whereas 2h-PG levels were not. Gene-gene interactions were not found among the five SNPs on GDM risk.

CONCLUSION

MTNR1B genetic variants have significant associations but no gene-gene interactions with GDM risk in central Chinese population. Furthermore, MTNR1B SNPs have significant relationships with glycemic traits.

Hexokinase domain-containing protein-1 in metabolic diseases and beyond

Glucose phosphorylation by hexokinases (HKs) traps glucose in cells and facilitates its usage in metabolic processes dependent on cellular needs. HK domain-containing protein-1 (HKDC1) is a recently discovered protein with wide expression containing HK activity, first noted through a genome-wide association study (GWAS) to be linked with gestational glucose homeostasis during pregnancy. Since then, HKDC1 has been observed to be expressed in many human tissues. Moreover, studies have shown that HKDC1 plays a role in glucose homeostasis by which it may affect the progression of many pathophysiological conditions such as gestational diabetes mellitus (GDM), nonalcoholic steatohepatitis (NASH), and cancer. Here, we review the key studies contributing to our current understanding of the roles of HKDC1 in human pathophysiological conditions and potential therapeutic interventions.

The Human Islet: Mini-Organ With Mega-Impact

This review focuses on the human pancreatic islet-including its structure, cell composition, development, function, and dysfunction. After providing a historical timeline of key discoveries about human islets over the past century, we describe new research approaches and technologies that are being used to study human islets and how these are providing insight into human islet physiology and pathophysiology. We also describe changes or adaptations in human islets in response to physiologic challenges such as pregnancy, aging, and insulin resistance and discuss islet changes in human diabetes of many forms. We outline current and future interventions being developed to protect, restore, or replace human islets. The review also highlights unresolved questions about human islets and proposes areas where additional research on human islets is needed.

Gestational Diabetes Mellitus: The Genetic Susceptibility Behind the Disease

Gestational diabetes mellitus (GDM), a type of pregnancy-specific glucose intolerance or hyperglycemia, is one of the most common metabolic disorders in pregnant women with 16.9% of the global prevalence of gestational hyperglycemia. Not only are women with GDM likely to develop T2DM, but their children are also at risk for birth complications or metabolic disease in adulthood. Therefore, identifying the potential risk factors for GDM is very important in the prevention and treatment of GDM. Previous studies have shown that genetic predisposition is an essential component in the occurrence of GDM. In this narrative review, we describe the role of polymorphisms in different functional genes associated with increased risk for GDM, and available evidence on genetic factors in the risk of GDM is summarized and discussed.

GWAS of serum ALT and AST reveals an association of SLC30A10 Thr95Ile with hypermanganesemia symptoms

Understanding mechanisms of hepatocellular damage may lead to new treatments for liver disease, and genome-wide association studies (GWAS) of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) serum activities have proven useful for investigating liver biology. Here we report 100 loci associating with both enzymes, using GWAS across 411,048 subjects in the UK Biobank. The rare missense variant SLC30A10 Thr95Ile (rs188273166) associates with the largest elevation of both enzymes, and this association replicates in the DiscovEHR study. SLC30A10 excretes manganese from the liver to the bile duct, and rare homozygous loss of function causes the syndrome hypermanganesemia with dystonia-1 (HMNDYT1) which involves cirrhosis. Consistent with hematological symptoms of hypermanganesemia, SLC30A10 Thr95Ile carriers have increased hematocrit and risk of iron deficiency anemia. Carriers also have increased risk of extrahepatic bile duct cancer. These results suggest that genetic variation in SLC30A10 adversely affects more individuals than patients with diagnosed HMNDYT1.

The Role of Hexokinase Domain Containing Protein-1 in Glucose Regulation During Pregnancy

PURPOSE OF REVIEW

Gestational diabetes mellitus (GDM) is a common pregnancy complication conferring an increased risk to the individual of developing type 2 diabetes. As such, a thorough understanding of the pathophysiology of GDM is warranted. Hexokinase domain containing protein-1 (HKDC1) is a recently discovered protein containing hexokinase activity which has been shown to be associated with glucose metabolism during pregnancy. Here, we discuss recent evidence suggesting roles for the novel HKDC1 in gestational glucose homeostasis and the development of GDM and overt diabetes.

RECENT FINDINGS

Genome-wide association studies identified variants of the HKDC1 gene associated with maternal glucose metabolism. Studies modulating HKDC1 protein expression in pregnant mice demonstrate that HKDC1 has roles in whole-body glucose utilization and nutrient balance, with liver-specific HKDC1 influencing insulin sensitivity, glucose tolerance, gluconeogenesis, and ketone production. HKDC1 has important roles in maintaining maternal glucose homeostasis extending beyond traditional hexokinase functions and may serve as a potential therapeutic target.

Genetic discovery and risk characterization in type 2 diabetes across diverse populations

Genomic discovery and characterization of risk loci for type 2 diabetes (T2D) have been conducted primarily in individuals of European ancestry. We conducted a multiethnic genome-wide association study of T2D among 53,102 cases and 193,679 control subjects from African, Hispanic, Asian, Native Hawaiian, and European population groups in the Population Architecture Genomics and Epidemiology (PAGE) and Diabetes Genetics Replication and Meta-analysis (DIAGRAM) Consortia. In individuals of African ancestry, we discovered a risk variant in the TGFB1 gene (rs11466334, risk allele frequency (RAF) = 6.8%, odds ratio [OR] = 1.27, p = 2.06 × 10⁻⁸), which replicated in independent studies of African ancestry (p = 6.26 × 10⁻²³). We identified a multiethnic risk variant in the BACE2 gene (rs13052926, RAF = 14.1%, OR = 1.08, p = 5.75 × 10⁻⁹), which also replicated in independent studies (p = 3.45 × 10⁻⁴). We also observed a significant difference in the performance of a multiethnic genetic risk score (GRS) across population groups (p_{heterogeneity} = 3.85 × 10⁻²⁰). Comparing individuals in the top GRS risk category (40%–60%), the OR was highest in Asians (OR = 3.08) and European (OR = 2.94) ancestry populations, followed by Hispanic (OR = 2.39), Native Hawaiian (OR = 2.02), and African ancestry (OR = 1.57) populations. These findings underscore the importance of genetic discovery and risk characterization in diverse populations and the urgent need to further increase representation of non-European ancestry individuals in genetics research to improve genetic-based risk prediction across populations.

Integrated Multiomics Reveals Glucose Use Reprogramming and Identifies a Novel Hexokinase in Alcoholic Hepatitis

BACKGROUND & AIMS

We recently showed that alcoholic hepatitis (AH) is characterized by dedifferentiation of hepatocytes and loss of mature functions. Glucose metabolism is tightly regulated in healthy hepatocytes. We hypothesize that AH may lead to metabolic reprogramming of the liver, including dysregulation of glucose metabolism.

METHODS

We performed integrated metabolomic and transcriptomic analyses of liver tissue from patients with AH or alcoholic cirrhosis or normal liver tissue from hepatic resection. Focused analyses of chromatin immunoprecipitation coupled to DNA sequencing was performed. Functional in vitro studies were performed in primary rat and human hepatocytes and HepG2 cells.

RESULTS

Patients with AH exhibited specific changes in the levels of intermediates of glycolysis/gluconeogenesis, the tricarboxylic acid cycle, and monosaccharide and disaccharide metabolism. Integrated analysis of the transcriptome and metabolome showed the used of alternate energetic pathways, metabolite sinks and bottlenecks, and dysregulated glucose storage in patients with AH. Among genes involved in glucose metabolism, hexokinase domain containing 1 (HKDC1) was identified as the most up-regulated kinase in patients with AH. Histone active promoter and enhancer markers were increased in the HKDC1 genomic region. High HKDC1 levels were associated with the development of acute kidney injury and decreased survival. Increased HKDC1 activity contributed to the accumulation of glucose-6-P and glycogen in primary rat hepatocytes.

CONCLUSIONS

Altered metabolite levels and messenger RNA expression of metabolic enzymes suggest the existence of extensive reprogramming of glucose metabolism in AH. Increased HKDC1 expression may contribute to dysregulated glucose metabolism and represents a novel biomarker and therapeutic target for AH.

Exploring a Region on Chromosome 8p23.1 Displaying Positive Selection Signals in Brazilian Admixed Populations: Additional Insights Into Predisposition to Obesity and Related Disorders

We recently reported a deviation of local ancestry on the chromosome (ch) 8p23.1, which led to positive selection signals in a Brazilian population sample. The deviation suggested that the genetic variability of candidate genes located on ch 8p23.1 may have been evolutionarily advantageous in the early stages of the admixture process. In the present work, we aim to extend the previous work by studying additional Brazilian admixed individuals and examining DNA sequencing data from the ch 8p23.1 candidate region. Thus, we inferred the local ancestry of 125 exomes from individuals born in five towns within the Southeast region of Brazil (São Paulo, Campinas, Barretos, and Ribeirão Preto located in the state of São Paulo and Belo Horizonte, the capital of the state of Minas Gerais), and compared to data from two public Brazilian reference genomic databases, BIPMed and ABraOM, and with information from the 1000 Genomes Project phase 3 and gnomAD databases. Our results revealed that ancestry is similar among individuals born in the five Brazilian towns assessed; however, an increased proportion of sub-Saharan African ancestry was observed in individuals from Belo Horizonte. In addition, individuals from the five towns considered, as well as those from the ABRAOM dataset, had the same overrepresentation of Native-American ancestry on the ch 8p23.1 locus that was previously reported for the BIPMed reference sample. Sequencing analysis of ch 8p23.1 revealed the presence of 442 non-synonymous variants, including frameshift, inframe deletion, start loss, stop gain, stop loss, and splicing site variants, which occurred in 24 genes. Among these genes, 13 were associated with obesity, type II diabetes, lipid levels, and waist circumference (PRAG1, MFHAS1, PPP1R3B, TNKS, MSRA, PRSS55, RP1L1, PINX1, MTMR9, FAM167A, BLK, GATA4, and CTSB). These results strengthen the hypothesis that a set of variants located on ch 8p23.1 that result from positive selection during early admixture events may influence obesity-related disease predisposition in admixed individuals of the Brazilian population. Furthermore, we present evidence that the exploration of local ancestry deviation in admixed individuals may provide information with the potential to be translated into health care improvement.

All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes

Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.

Association of Common Genetic Risk Variants With Gestational Diabetes Mellitus and Their Role in GDM Prediction

OBJECTIVE

We aimed to explore the associations between common genetic risk variants with gestational diabetes mellitus (GDM) risk in Russian women and to assess their utility in the identification of GDM cases.

METHODS

We conducted a case-control study including 1,142 pregnant women (688 GDM cases and 454 controls) enrolled at Almazov National Medical Research Centre. The International Association of Diabetes and Pregnancy Study Groups criteria were used to diagnose GDM. A total of 11 single- nucleotide polymorphisms (SNPs), including those in HKDC1 (rs10762264), GCK (rs1799884), MTNR1B (rs10830963 and rs1387153), TCF7L2 (rs7903146 and rs12255372), KCNJ11 (rs5219), IGF2BP2 (rs4402960), IRS1 (rs1801278), FTO (rs9939609), and CDKAL1 (rs7754840) were genotyped using Taqman assays. A logistic regression model was used to calculate odds ratios (ORs) and their confidence intervals (CIs). A simple-count genetic risk score (GRS) was calculated using 6 SNPs. The area under the receiver operating characteristic curve (c-statistic) was calculated for the logistic regression model predicting the risk of GDM using clinical covariates, SNPs that had shown a significant association with GDM in our study, GRS, and their combinations.

RESULTS

Two variants in MTNR1B (rs1387153 and rs10830963) demonstrated a significant association with an increased risk of GDM. The association remained significant after adjustment for age, pre-gestational BMI, arterial hypertension, GDM in history, impaired glucose tolerance, polycystic ovary syndrome, family history of diabetes, and parity (P = 0.001 and P < 0.001, respectively). After being conditioned by each other, the effect of rs1387153 on GDM predisposition weakened while the effect of rs10830963 remained significant (P = 0.004). The risk of GDM was predicted by clinical variables (c-statistic 0.712, 95 % CI: 0.675 - 0.749), and the accuracy of prediction was modestly improved by adding GRS to the model (0.719, 95 % CI 0.682 - 0.755), and more by adding only rs10830963 (0.729, 95 % CI 0.693 - 0.764).

CONCLUSION

Among 11 SNPs associated with T2D and/or GDM in other populations, we confirmed significant association with GDM for two variants in MTNR1B in Russian women. However, these variants showed limited value in the identification of GDM cases.

Maternal GDM Status, Genetically Determined Blood Glucose, and Offspring Obesity Risk: An Observational Study

OBJECTIVE

The purpose of this study was to estimate the associations of genetically determined maternal blood glucose levels with obesity-related outcomes among children from pregnancies with and without gestational diabetes mellitus (GDM).

METHODS

A total of 1,114 mothers with (N = 560) and without (N = 554) GDM and their children were included in the present study. A maternal genetic risk score (GRS) for blood glucose was constructed on the basis of 17 single-nucleotide polymorphisms identified from a recent genome-wide association study.

RESULTS

It was found that maternal GRS for blood glucose showed different associations with offspring risk of overweight and obesity, as well as adiposity measures (all P _{for interaction}  < 0.05). Among mothers without GDM, genetically determined maternal blood glucose levels were associated with an 89% higher risk of overweight in their children (95% CI: 42%-152% per SD increase in GRS, P = 1.40 × 10^-5 ) and a 120% higher risk of obesity (44%-235%, P = 2.61 × 10^-4 ) after adjustment for covariates. In addition, higher maternal GRS for blood glucose was associated with children's increased obesity-related traits (all P < 0.05). However, no significant associations were observed among children of mothers with GDM.

CONCLUSIONS

This study indicates that GDM status may modify the relation between genetically determined glucose levels and obesity risk among children.

Genetic Loci and Physiologic Pathways Involved in Gestational Diabetes Mellitus Implicated Through Clustering

Hundreds of common genetic variants acting through distinguishable physiologic pathways influence the risk of type 2 diabetes (T2D). It is unknown to what extent the physiology underlying gestational diabetes mellitus (GDM) is distinct from that underlying T2D. In this study of >5,000 pregnant women from three cohorts, we aimed to identify physiologically related groups of maternal variants associated with GDM using two complementary approaches that were based on Bayesian nonnegative matrix factorization (bNMF) clustering. First, we tested five bNMF clusters of maternal T2D-associated variants grouped on the basis of physiology outside of pregnancy for association with GDM. We found that cluster polygenic scores representing genetic determinants of reduced β-cell function and abnormal hepatic lipid metabolism were associated with GDM; these clusters were not associated with infant birth weight. Second, we derived bNMF clusters of maternal variants on the basis of pregnancy physiology and tested these clusters for association with GDM. We identified a cluster that was strongly associated with GDM as well as associated with higher infant birth weight. The effect size for this cluster's association with GDM appeared greater than that for T2D. Our findings imply that the genetic and physiologic pathways that lead to GDM differ, at least in part, from those that lead to T2D.

Linker residues regulate the activity and stability of hexokinase 2, a promising anticancer target

Hexokinase (HK) catalyzes the first step in glucose metabolism, making it an exciting target for the inhibition of tumor initiation and progression due to their elevated glucose metabolism. The upregulation of hexokinase-2 (HK2) in many cancers and its limited expression in normal tissues make it a particularly attractive target for the selective inhibition of cancer growth and the eradication of tumors with limited side effects. The design of such safe and effective anticancer therapeutics requires the development of HK2-specific inhibitors that will not interfere with other HK isozymes. As HK2 is unique among HKs in having a catalytically active N-terminal domain (NTD), we have focused our attention on this region. We previously found that NTD activity is affected by the size of the linker helix-α₁₃ that connects the N- and C-terminal domains of HK2. Three nonactive site residues (D447, S449, and K451) at the beginning of the linker helix-α₁₃ have been found to regulate the NTD activity of HK2. Mutation of these residues led to increased dynamics, as shown via hydrogen deuterium exchange analysis and molecular dynamic simulations. D447A contributed the most to the enhanced dynamics of the NTD, with reduced calorimetric enthalpy of HK2. Similar residues exist in the C-terminal domain (CTD) but are unnecessary for HK1 and HK2 activity. Thus, we postulate these residues serve as a regulatory site for HK2 and may provide new directions for the design of anticancer therapeutics that reduce the rate of glycolysis in cancer through specific inhibition of HK2.

Genetic Studies of Gestational Diabetes and Glucose Metabolism in Pregnancy

PURPOSE OF REVIEW

In this review, we summarize studies investigating genetics of gestational diabetes mellitus (GDM) and glucose metabolism in pregnancy. We describe these studies in the context of the larger body of literature on type 2 diabetes (T2D) and glycemic trait genomics.

RECENT FINDINGS

We reviewed 23 genetic association studies for GDM and performed a meta-analysis, which revealed variants at eight T2D loci significantly associated with GDM after the Bonferroni correction. These studies suggest that GDM and T2D share a number of genetic risk loci. Only two unbiased genome-wide association studies (GWASs) have successfully revealed genetic associations for GDM and related glycemic traits in pregnancy. A GWAS for GDM in Korean women identified two loci (near CDKAL1 and MTNR1B) known to be associated with T2D, though the association of the MTNR1B locus with GDM appears to be stronger than that for T2D. A multi-ethnic GWAS for glycemic traits in pregnancy identified two novel loci (near HKDC1 and BACE2) which appear to be associated with post-load glucose and fasting c-peptide specifically in pregnant women. There are ongoing efforts to use this genetic information, in the form of polygenic scores, to predict risk of GDM and postpartum T2D. The body of literature examining genetic associations with GDM is limited, especially when compared to the available literature on T2D and glycemic trait genomics. Additional genetic discovery for glucose metabolism in pregnant women will require larger pregnancy cohorts and international collaborative efforts. Studies on the clinical implications of these findings are also warranted.

All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes

Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.

The impact of sex on gene expression across human tissues

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

Defining Heterogeneity Among Women With Gestational Diabetes Mellitus

Attention to precision medicine in type 2 diabetes (T2D) has provided two favored approaches to subclassifying affected individuals and parsing heterogeneity apparent in this condition: phenotype-based and genotype-based. Gestational diabetes mellitus (GDM) shares phenotypic characteristics with T2D. However, unlike T2D, GDM emerges in the setting of profound pregnancy-related physiologic changes in glucose metabolism. T2D and GDM also share common genetic architecture, but there are likely to be unique genetic influences on pregnancy glycemic regulation that contribute to GDM. In this Perspective, we describe efforts to decipher heterogeneity in T2D and detail how we and others are applying approaches developed for T2D to the study of heterogeneity in GDM. Emerging results reveal the potential of phenotype- and genotype-based subclassification of GDM to deliver the promise of precision medicine to the obstetric population.

Metabolomic and genetic associations with insulin resistance in pregnancy

AIMS/HYPOTHESIS

Our study aimed to integrate maternal metabolic and genetic data related to insulin sensitivity during pregnancy to provide novel insights into mechanisms underlying pregnancy-induced insulin resistance.

METHODS

Fasting and 1 h serum samples were collected from women in the Hyperglycemia and Adverse Pregnancy Outcome study who underwent an OGTT at ∼28 weeks' gestation. We obtained targeted and non-targeted metabolomics and genome-wide association data from 1600 and 4528 mothers, respectively, in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai); 1412 of the women had both metabolomics and genome-wide association data. Insulin sensitivity was calculated using a modified insulin sensitivity index that included fasting and 1 h glucose and C-peptide levels after a 75 g glucose load.

RESULTS

Per-metabolite and network analyses across the four ancestries identified numerous metabolites associated with maternal insulin sensitivity before and 1 h after a glucose load, ranging from amino acids and carbohydrates to fatty acids and lipids. Genome-wide association analyses identified 12 genetic variants in the glucokinase regulatory protein gene locus that were significantly associated with maternal insulin sensitivity, including a common functional missense mutation, rs1260326 (β = -0.2004, p = 4.67 × 10^-12 in a meta-analysis across the four ancestries). This SNP was also significantly associated with multiple fasting and 1 h metabolites during pregnancy, including fasting and 1 h triacylglycerols and 2-hydroxybutyrate and 1 h lactate, 2-ketoleucine/ketoisoleucine and palmitoleic acid. Mediation analysis suggested that 1 h palmitoleic acid contributes, in part, to the association of rs1260326 with maternal insulin sensitivity, explaining 13.7% (95% CI 4.0%, 23.3%) of the total effect.

CONCLUSIONS/INTERPRETATION

The present study demonstrates commonalities between metabolites and genetic variants associated with insulin sensitivity in the gravid and non-gravid states and provides insights into mechanisms underlying pregnancy-induced insulin resistance. Graphical abstract.

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

A Long Non-coding RNA, LOC157273, Is an Effector Transcript at the Chromosome 8p23.1-PPP1R3B Metabolic Traits and Type 2 Diabetes Risk Locus

AIMS

Causal transcripts at genomic loci associated with type 2 diabetes (T2D) are mostly unknown. The chr8p23.1 variant rs4841132, associated with an insulin-resistant diabetes risk phenotype, lies in the second exon of a long non-coding RNA (lncRNA) gene, LOC157273, located 175 kilobases from PPP1R3B, which encodes a key protein regulating insulin-mediated hepatic glycogen storage in humans. We hypothesized that LOC157273 regulates expression of PPP1R3B in human hepatocytes.

METHODS

We tested our hypothesis using Stellaris fluorescent in situ hybridization to assess subcellular localization of LOC157273; small interfering RNA (siRNA) knockdown of LOC157273, followed by RT-PCR to quantify LOC157273 and PPP1R3B expression; RNA-seq to quantify the whole-transcriptome gene expression response to LOC157273 knockdown; and an insulin-stimulated assay to measure hepatocyte glycogen deposition before and after knockdown.

RESULTS

We found that siRNA knockdown decreased LOC157273 transcript levels by approximately 80%, increased PPP1R3B mRNA levels by 1.7-fold, and increased glycogen deposition by >50% in primary human hepatocytes. An A/G heterozygous carrier (vs. three G/G carriers) had reduced LOC157273 abundance due to reduced transcription of the A allele and increased PPP1R3B expression and glycogen deposition.

CONCLUSION

We show that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and a causal transcript at an insulin-resistant T2D risk locus.

Precision Medicine in Diabetes: A Consensus Report From the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science, and technology has enabled the generation of new insights into the phenotype known as "diabetes." Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence, and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field, and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment), and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e., monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realize its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.