Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Causal Relations between Exposome and Stroke: A Mendelian Randomization Study

BACKGROUND AND PURPOSE

To explore the causal relationships of elements of the exposome with ischemic stroke and its subtypes at the omics level and to provide evidence for stroke prevention.

METHODS

We conducted a Mendelian randomization study between exposure and any ischemic stroke (AIS) and its subtypes (large-artery atherosclerotic disease [LAD], cardioembolic stroke [CE], and small vessel disease [SVD]). The exposure dataset was the UK Biobank involving 361,194 subjects, and the outcome dataset was the MEGASTROKE consortium including 52,000 participants.

RESULTS

We found that higher blood pressure (BP) (systolic BP: odds ratio [OR], 1.02; 95% confidence interval [CI], 1.01 to 1.04; diastolic BP: OR, 1.03; 95% CI, 1.01 to 1.05; pulse pressure: OR, 1.03; 95% CI, 1.00 to 1.06), atrial fibrillation (OR, 1.18; 95% CI, 1.13 to 1.25), and diabetes (OR, 1.13; 95% CI, 1.07 to 1.18) were significantly associated with ischemic stroke. Importantly, higher education (OR, 0.69; 95% CI, 0.60 to 0.79) decreased the risk of ischemic stroke. Higher systolic BP (OR, 1.06; 95% CI, 1.02 to 1.10), pulse pressure (OR, 1.08; 95% CI, 1.02 to 1.14), diabetes (OR, 1.28; 95% CI, 1.13 to 1.45), and coronary artery disease (OR, 1.58; 95% CI, 1.25 to 2.00) could cause LAD. Atrial fibrillation could cause CE (OR, 1.90; 95% CI, 1.71 to 2.11). For SVD, higher systolic BP (OR, 1.04; 95% CI, 1.00 to 1.07), diastolic BP (OR, 1.06; 95% CI, 1.01 to 1.12), and diabetes (OR, 1.22; 95% CI, 1.10 to 1.36) were causal factors.

CONCLUSIONS

The study revealed elements of the exposome causally linked to ischemic stroke and its subtypes, including conventional causal risk factors and novel protective factors such as higher education.

First genome-wide association study of 99 body measures derived from 3-dimensional body scans

Body height, body mass index, hip and waist circumference are important risk factors or outcome variables in clinical and epidemiological research with complex underlying genetics. However, these classical anthropometric traits represent only a very limited view on the human body and other traits with potentially higher functional specificity are not yet studied to a larger extent. Participants of LIFE-Adult were assessed by three-dimensional body scanner VITUS XXL determining 99 high-quality anthropometric traits in parallel. Genotyping was performed by Axiom Genome-Wide CEU 1 Array Plate microarray technology and imputation was done using 1000 Genomes phase 3 reference panel. Combined phenotype and genetic information are available for a total of 7,562 participants. Largest heritabilities were estimated for height traits (maximum heritability with h² = 44% for neck height) and 61 traits achieved values larger than 20%. By genome-wide analyses, we identified 16 loci associated with at least one of the 99 traits. Ten of these loci were not described for association with classical anthropometric traits so far. The strongest novel association was observed for 7p14.3 (rs11979006, P = 2.12 × 10⁻⁹) for the trait Back Width with ZNRF2 as the most plausible candidate gene. Loci established for association with classical anthropometric traits were subjected to anthropometric phenome-wide association analysis. From the reported 709 loci, 211 are co-associated with body scanner traits (enrichment: OR = 1.96, P = 1.08 × 10⁻⁶¹). We conclude that genetics of 3D laser-based anthropometry is promising to identify novel loci and to improve the functional understanding of established ones.

Evidence of a Causal Link Between the Well-Being Spectrum and the Risk of Myocardial Infarction: A Mendelian Randomization Study

Epidemiological studies have provided extensive evidence regarding the role of psychological risk factors in the pathogenesis of cardiovascular disease (CVD), but whether these associations are causal in nature is still unknown. We aimed to investigate whether the association between the wellbeing spectrum (WBS; derived from four psychological traits including life satisfaction, positive affect, neuroticism, and depressive symptoms) and CVD risk is causal. By employing a two-sample Mendelian randomization (MR) approach, the effect of the WBS on four CVD outcomes, including atrial fibrillation, heart failure, myocardial infarction, and ischemic stroke, was investigated. The genetically predicted WBS was associated with 38% lower risk for heart failure (odds ratio (OR): 0.62; 95% confidence interval [CI]: 0.50–0.78; P: 2.2 × 10⁻⁵) and 40% reduced risk of myocardial infarction (OR: 0.60; 95% CI: 0.47–0.78; P: 1.1 × 10⁻⁴). Of the WBS constituent traits, only depressive symptoms showed a positive causal association with heart failure and myocardial infarction. Neither WBS nor WBS constituent traits were associated with atrial fibrillation and ischemic stroke. In multivariable MR analyses, when genetic instruments for traditional CVD risk factors were also taken into consideration, the WBS was causally associated with a reduced risk for heart failure (OR: 0.72; 95% CI: 0.58–0.88; P: 0.001) and myocardial infarction (OR: 0.67; 95% CI: 0.52–0.86; P: 0.002). This study provides evidence that a higher WBS is causally associated with a decreased risk of developing CVD and, more specifically, myocardial infarction; moreover, the association is mainly driven by depressive symptoms. These results support current guidelines that suggest improving psychological wellbeing may help in reducing the burden of cardiovascular disease.

Generation of human islet cell type-specific identity genesets

Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits.

Factors That Contribute to hIAPP Amyloidosis in Type 2 Diabetes Mellitus

Cases of Type 2 Diabetes Mellitus (T2DM) are increasing at an alarming rate due to the rise in obesity, sedentary lifestyles, glucose-rich diets and other factors. Numerous studies have increasingly illustrated the pivotal role that human islet amyloid polypeptide (hIAPP) plays in the pathology of T2DM through damage and subsequent loss of pancreatic β-cell mass. HIAPP can misfold and form amyloid fibrils which are preceded by pre-fibrillar oligomers and monomers, all of which have been linked, to a certain extent, to β-cell cytotoxicity through a range of proposed mechanisms. This review provides an up-to-date summary of recent progress in the field, highlighting factors that contribute to hIAPP misfolding and aggregation such as hIAPP protein concentration, cell stress, molecular chaperones, the immune system response and cross-seeding with other amyloidogenic proteins. Understanding the structure of hIAPP and how these factors affect amyloid formation will help us better understand how hIAPP misfolds and aggregates and, importantly, help identify potential therapeutic targets for inhibiting amyloidosis so alternate and more effective treatments for T2DM can be developed.

Identification of genetic effects underlying type 2 diabetes in South Asian and European populations

South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.

NS encodes an auxin transporter that regulates the 'numerous spines' trait in cucumber (Cucumis sativus) fruit

Fruit spine is an important agronomic trait in cucumber and the "numerous spines (ns)" cucumber varieties are popular in Europe and West Asia. Although the classical genetic locus of ns was reported more than two decades ago, the NS gene has not been cloned yet. In this study, nine genetic loci for the different densities of fruit spines were identified by a genome-wide association study. Among the nine loci, fsdG2.1 was closely associated with the classical genetic locus ns, which harbors a candidate gene Csa2G264590. Overexpression of Csa2G264590 resulted in lower fruit spine density, and the knockout mutant generated by CRISPR/Cas9 displayed an increased spine density, demonstrating that the Csa2G264590 gene is NS. NS is specifically expressed in the fruit peel and spine. Genetic analysis showed that NS regulates fruit spine development independently of the tuberculate gene, Tu, which regulates spine development on tubercules; the cucumber glabrous mutants csgl1 and csgl3 are epistatic to ns. Furthermore, we found that auxin levels in the fruit peel and spine were significantly lower in the knockout mutant ns-cr. Moreover, RNA-sequencing showed that the plant hormone signal transduction pathway was enriched. Notably, most of the auxin responsive Aux/IAA family genes were downregulated in ns-cr. Haplotype analysis showed that the non-functional haplotype of NS exists exclusively in the Eurasian cucumber backgrounds. Taken together, the cloning of NS gene provides new insights into the regulatory network of fruit spine development.

An integrated framework for local genetic correlation analysis

Genetic correlation (r_g) analysis is used to identify phenotypes that may have a shared genetic basis. Traditionally, r_g is studied globally, considering only the average of the shared signal across the genome, although this approach may fail when the r_g is confined to particular genomic regions or in opposing directions at different loci. Current tools for local r_g analysis are restricted to analysis of two phenotypes. Here we introduce LAVA, an integrated framework for local r_g analysis that, in addition to testing the standard bivariate local r_gs between two phenotypes, can evaluate local heritabilities and analyze conditional genetic relations between several phenotypes using partial correlation and multiple regression. Applied to 25 behavioral and health phenotypes, we show considerable heterogeneity in the bivariate local r_gs across the genome, which is often masked by the global r_g patterns, and demonstrate how our conditional approaches can elucidate more complex, multivariate genetic relations.

Integration of genetic colocalizations with physiological and pharmacological perturbations identifies cardiometabolic disease genes

BACKGROUND

Identification of causal genes for polygenic human diseases has been extremely challenging, and our understanding of how physiological and pharmacological stimuli modulate genetic risk at disease-associated loci is limited. Specifically, insulin resistance (IR), a common feature of cardiometabolic disease, including type 2 diabetes, obesity, and dyslipidemia, lacks well-powered genome-wide association studies (GWAS), and therefore, few associated loci and causal genes have been identified.

METHODS

Here, we perform and integrate linkage disequilibrium (LD)-adjusted colocalization analyses across nine cardiometabolic traits (fasting insulin, fasting glucose, insulin sensitivity, insulin sensitivity index, type 2 diabetes, triglycerides, high-density lipoprotein, body mass index, and waist-hip ratio) combined with expression and splicing quantitative trait loci (eQTLs and sQTLs) from five metabolically relevant human tissues (subcutaneous and visceral adipose, skeletal muscle, liver, and pancreas). To elucidate the upstream regulators and functional mechanisms for these genes, we integrate their transcriptional responses to 21 relevant physiological and pharmacological perturbations in human adipocytes, hepatocytes, and skeletal muscle cells and map their protein-protein interactions.

RESULTS

We identify 470 colocalized loci and prioritize 207 loci with a single colocalized gene. Patterns of shared colocalizations across traits and tissues highlight different potential roles for colocalized genes in cardiometabolic disease and distinguish several genes involved in pancreatic β-cell function from others with a more direct role in skeletal muscle, liver, and adipose tissues. At the loci with a single colocalized gene, 42 of these genes were regulated by insulin and 35 by glucose in perturbation experiments, including 17 regulated by both. Other metabolic perturbations regulated the expression of 30 more genes not regulated by glucose or insulin, pointing to other potential upstream regulators of candidate causal genes.

CONCLUSIONS

Our use of transcriptional responses under metabolic perturbations to contextualize genetic associations from our custom colocalization approach provides a list of likely causal genes and their upstream regulators in the context of IR-associated cardiometabolic risk.

Genetically-Guided Medical Nutrition Therapy in Type 2 Diabetes Mellitus and Pre-diabetes: A Series of n-of-1 Superiority Trials

Type 2 diabetes mellitus (T2DM) is a heterogeneous metabolic disorder of multifactorial etiology that includes genetic and dietary influences. By addressing the latter, medical nutrition therapy (MNT) contributes to the management of T2DM or pre-diabetes toward achieving glycaemic control and improved insulin sensitivity. However, the clinical outcomes of MNT vary and may further benefit from personalized nutritional plans that take into consideration genetic variations associated with individual responses to macronutrients. The aim of the present series of n-of-1 trials was to assess the effects of genetically-guided vs. conventional MNT on patients with pre-diabetes or T2DM. A quasi-experimental, cross-over design was adopted in three Caucasian adult men with either diagnosis. Complete diet, bioclinical and anthropometric assessment was performed and a conventional MNT, based on the clinical practice guidelines was applied for 8 weeks. After a week of “wash-out,” a precision MNT was prescribed for an additional 8-week period, based on the genetic characteristics of each patient. Outcomes of interest included changes in body weight (BW), fasting plasma glucose (FPG), and blood pressure (BP). Collectively, the trials indicated improvements in BW, FPG, BP, and glycosylated hemoglobin (HbA1c) following the genetically-guided precision MNT intervention. Moreover, both patients with pre-diabetes experienced remission of the condition. We conclude that improved BW loss and glycemic control can be achieved in patients with pre-diabetes/T2DM, by coupling MNT to their genetic makeup, guiding optimal diet, macronutrient composition, exercise and oral nutrient supplementation in a personalized manner.

Co‑expressed microRNAs, target genes and pathways related to metabolism, inflammation and endocrine function in individuals at risk for type 2 diabetes

MicroRNAs (miRNAs) may be considered important regulators of risk for type 2 diabetes (T2D). The aim of the present study was to identify novel sets of miRNAs associated with T2D risk, as well as their gene and pathway targets. Circulating miRNAs (n=59) were measured in plasma from participants in a previously completed clinical trial (n=82). An agnostic statistical approach was applied to identify novel sets of miRNAs with optimal co-expression patterns. In silico analyses were used to identify the messenger RNA and biological pathway targets of the miRNAs within each factor. A total of three factors of miRNAs were identified, containing 18, seven and two miRNAs each. Eight biological pathways were revealed to contain genes targeted by the miRNAs in all three factors, 38 pathways contained genes targeted by the miRNAs in two factors, and 55, 18 and two pathways were targeted by the miRNAs in a single factor, respectively (all q<0.05). The pathways containing genes targeted by miRNAs in the largest factor shared a common theme of biological processes related to metabolism and inflammation. By contrast, the pathways containing genes targeted by miRNAs in the second largest factor were related to endocrine function and hormone activity. The present study focused on the pathways uniquely targeted by each factor of miRNAs in order to identify unique mechanisms that may be associated with a subset of individuals. Further exploration of the genes and pathways related to these biological themes may provide insights about the subtypes of T2D and lead to the identification of novel therapeutic targets.

Evidence for causal effects of sleep disturbances on risk for osteoarthritis: a univariable and multivariable Mendelian randomization study

OBJECTIVE

To disentangle whether sleep disturbances have a causal effect on the risk of osteoarthritis (OA) using genetically based approaches.

METHOD

We performed univariable and multivariable Mendelian randomization (MR) analyses using publicly released genome-wide association studies summary statistics to estimate the causal associations of sleep disturbances with OA risk. The inverse-variance weighted (IVW) method was utilized as primary MR analysis, whereas complementary methods including weighted median, weighted mode, MR-Egger regression, and MR pleiotropy residual sum and outlier (MR-PRESSO) were applied to detect and correct for the presence of pleiotropy.

RESULTS

There were 228 independent instrumental variables (IVs) for insomnia and 78, 27 and 8 IVs for sleep duration, short sleep duration and long sleep duration, respectively. Univariable MR analysis suggested that genetically determined insomnia or short sleep duration exerted a causal effect on overall OA in an unfavorable manner (Insomnia: OR = 1.22, 95%CI = 1.15-1.30, P = 8.05 × 10^-10; Short sleep duration: OR = 1.04, 95%CI = 1.02-1.07, P = 2.20 × 10^-3). More compelling, increasing genetic liability to insomnia or short sleep duration was also associated with OA risk, after accounting for effects of insomnia or short sleep duration on body mass index, type 2 diabetes and depression individually, and in a combined model considering all three confounders.

CONCLUSIONS

Findings suggested consisted evidence for an adverse effect of increased insomnia or short sleep duration on OA risk. Strategies to mitigate sleep disturbances may be one of the cornerstones protects against OA.

Celebrities in the heart, strangers in the pancreatic beta cell: Voltage-gated potassium channels Kv 7.1 and Kv 11.1 bridge long QT syndrome with hyperinsulinaemia as well as type 2 diabetes

Voltage‐gated potassium (K_v) channels play an important role in the repolarization of a variety of excitable tissues, including in the cardiomyocyte and the pancreatic beta cell. Recently, individuals carrying loss‐of‐function (LoF) mutations in KCNQ1, encoding K_v7.1, and KCNH2 (hERG), encoding K_v11.1, were found to exhibit post‐prandial hyperinsulinaemia and episodes of hypoglycaemia. These LoF mutations also cause the cardiac disorder long QT syndrome (LQTS), which can be aggravated by hypoglycaemia. Interestingly, patients with LQTS also have a higher burden of diabetes compared to the background population, an apparent paradox in relation to the hyperinsulinaemic phenotype, and KCNQ1 has been identified as a type 2 diabetes risk gene. This review article summarizes the involvement of delayed rectifier K⁺ channels in pancreatic beta cell function, with emphasis on K_v7.1 and K_v11.1, using the cardiomyocyte for context. The functional and clinical consequences of LoF mutations and polymorphisms in these channels on blood glucose homeostasis are explored using evidence from pre‐clinical, clinical and genome‐wide association studies, thereby evaluating the link between LQTS, hyperinsulinaemia and type 2 diabetes.

Anti-obesity drug discovery: advances and challenges

Enormous progress has been made in the last half-century in the management of diseases closely integrated with excess body weight, such as hypertension, adult-onset diabetes and elevated cholesterol. However, the treatment of obesity itself has proven largely resistant to therapy, with anti-obesity medications (AOMs) often delivering insufficient efficacy and dubious safety. Here, we provide an overview of the history of AOM development, focusing on lessons learned and ongoing obstacles. Recent advances, including increased understanding of the molecular gut-brain communication, are inspiring the pursuit of next-generation AOMs that appear capable of safely achieving sizeable and sustained body weight loss.

Roles of Cardiometabolic Factors in Mediating the Causal Effect of Type 2 Diabetes on Cardiovascular Diseases: A Two-Step, Two-Sample Multivariable Mendelian Randomization Study

Objective

The objective of this study is to investigate the roles of cardiometabolic factors (including blood pressure, blood lipids, thyroid function, body mass, and insulin sensitivity) in mediating the causal effect of type 2 diabetes (T2DM) on cardiovascular disease (CVD) outcomes.

Design

Two-step, two-sample multivariable Mendelian randomization (MVMR) study.

Setting

International genome-wide association study (GWAS) consortia data.

Exposure

Type 2 diabetes, blood pressure: systolic blood pressure (SBP), diastolic blood pressure (DBP); blood lipids: low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC), triglycerides (TG); thyroid function: hyperthyroidism, hypothyroidism; body mass index (BMI), waist-hip-ratio (WHR), and insulin sensitivity.

Main Outcomes

Cardiovascular disease includes coronary heart disease (CHD), myocardial infarction (MI), and stroke.

Methods

Summary-level data for exposures and main outcomes were extracted from GWAS consortia. We used two-sample MR to illustrate the causal effect of T2DM on CVD subtypes and regression-based MVMR to quantify the possible mediation effects of cardiometabolic factors on CVD.

Results

Each additional unit of log odds of T2DM increased 16% risk of CHD [odds ratio (OR): 1.16, 95% CI: 1.12–1.21], 15% risk of myocardial infarction (MI) (OR: 1.15, 95% CI: 1.10–1.20), and 10% risk of stroke (OR: 1.10, 95% CI: 1.06–1.13). In mediation analysis, SBP, DBP, and TG were found as main mediators, while the mediation effects of other cardiometabolic factors were not significant. The proportion of total effect of T2DM on CHD mediated by SBP, DBP, and TG was 16% (95% CI: 8–24%), 7% (95% CI: 1–13%) and 10% (95% CI: 2–18%), respectively. Mediation effect of SBP and DBP on MI and stroke, TG on MI was also prominent, while mediation effect of TG on stroke was not significant. The combined mediation effect of all the three mediators accounted for 29%, 26%, and 13% of the total effect of T2DM on CHD, MI, and stroke, respectively.

Conclusion

Systolic blood pressure, DBP, and TG mediate a substantial proportion of the causal effect of T2DM on CVD and thus interventions on these factors might reduce the considerable excess risk of CVD among patients with T2DM.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

Background

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging.

Results

In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants.

Conclusions

Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01021-x.

Association between type 2 diabetes and amyotrophic lateral sclerosis

Type 2 diabetes (T2D) and amyotrophic lateral sclerosis (ALS) are associated consistently. However, it is currently unknown whether this association is causal. We aimed to estimate the unconfounded, causal association between T2D on ALS using a two-sample Mendelian randomization approach both in European and East Asian ancestry. Genetic variants strongly associated with T2D and each T2D markers were used to investigate the effect of T2D on ALS risk in European (involving 20,806 ALS cases and 59,804 controls) and East Asian (involving 1234 ALS cases and 2850 controls) ancestry. We found that the OR of ALS per 1 SD increase in T2D was estimated to be 0.96 [95% confidence interval (CI) 0.92–0.996; p = 0.03] in European populations. Similarly, all 8 SNPs were associated with T2D in East Asian ancestry, the OR of ALS per 1 SD increase in T2D was estimated to be 0.83 [95% CI 0.70–0.992; p = 0.04] in East Asian populations. Examining the intercept estimates from MR-Egger regression also leads to the same conclusion, in that horizontal pleiotropy unlikely influences the results in either population. We found that genetically predicted T2D was associated with significantly lower odds of amyotrophic lateral sclerosis both in European and East Asian populations. It is now critical to identify a clear molecular explanation for this association between T2D and ALS and to focus on its potential therapeutic implications.

A Final Frontier in Environment-Genome Interactions? Integrated, Multi-Omic Approaches to Predictions of Non-Communicable Disease Risk

Epidemiological and associative research from humans and animals identifies correlations between the environment and health impacts. The environment-health inter-relationship is effected through an individual's underlying genetic variation and mediated by mechanisms that include the changes to gene regulation that are associated with the diversity of phenotypes we exhibit. However, the causal relationships have yet to be established, in part because the associations are reduced to individual interactions and the combinatorial effects are rarely studied. This problem is exacerbated by the fact that our genomes are highly dynamic; they integrate information across multiple levels (from linear sequence, to structural organisation, to temporal variation) each of which is open to and responds to environmental influence. To unravel the complexities of the genomic basis of human disease, and in particular non-communicable diseases that are also influenced by the environment (e.g., obesity, type II diabetes, cancer, multiple sclerosis, some neurodegenerative diseases, inflammatory bowel disease, rheumatoid arthritis) it is imperative that we fully integrate multiple layers of genomic data. Here we review current progress in integrated genomic data analysis, and discuss cases where data integration would lead to significant advances in our ability to predict how the environment may impact on our health. We also outline limitations which should form the basis of future research questions. In so doing, this review will lay the foundations for future research into the impact of the environment on our health.

Mechanisms underlying the pathophysiology of type 2 diabetes: From risk factors to oxidative stress, metabolic dysfunction, and hyperglycemia

Type 2 diabetes (T2D) is a complex multifactorial disease that emerges from the combination of genetic and environmental factors, and obesity, lifestyle, and aging are the most relevant risk factors. Hyperglycemia is the main metabolic feature of T2D as a consequence of insulin resistance and β-cell dysfunction. Among the cellular alterations induced by hyperglycemia, the overproduction of reactive oxygen species (ROS) and consequently oxidative stress, accompanied by a reduced antioxidant response and impaired DNA repair pathways, represent essential mechanisms underlying the pathophysiology of T2D and the development of late complications. Mitochondrial dysfunction, endoplasmic reticulum (ER) stress, and inflammation are also closely correlated with insulin resistance and β-cell dysfunction. This review focus on the mechanisms by which oxidative stress, mitochondrial dysfunction, ER stress, and inflammation are involved in the pathophysiology of T2D, highlighting the importance of the antioxidant response and DNA repair mechanisms counteracting the development of the disease. Moreover, we indicate evidence on how nutritional interventions effectively improve diabetes care. Additionally, we address key molecular characteristics and signaling pathways shared between T2D and Alzheimer's disease (AD), which might probably be implicated in the risk of T2D patients to develop AD.

The Effect of SOCS2 Polymorphisms on Type 2 Diabetes Mellitus Susceptibility and Diabetic Complications in the Chinese Han Population

BACKGROUND

SOCS2 is downregulated in diabetes, which might be related to diabetes. We explored the effect of SOCS2 polymorphisms on the development of type 2 diabetes mellitus (T2DM) and diabetic complications.

METHODS

The subjects consisted of 500 patients with T2DM and 501 healthy controls. Five variants in SOCS2 were genotyped by Agena MassARRAY system. RT-qPCR profiling was performed to detect the expression of SOCS2 mRNA. Logistic regression analysis was utilized to calculate odds ratio (OR) and 95% confidence intervals (95% CIs).

RESULTS

Rs3825199 (OR = 1.44, p = 0.007), rs11107116 (OR = 1.39, p = 0.014) and rs10492321 (OR = 1.48, p = 0.004) had an increased T2DM risk of T2DM. Moreover, the contribution of SOCS2 polymorphisms to T2DM risk was associated with age, gender, smoking, drinking, and BMI. SOCS2 variants also had a reduced risk for T2DM patients with diabetic nephropathy, diabetic retinopathy and coronary heart disease. SOCS2 rs10492321 was the best single locus model. SOCS2 mRNA was downregulated in patients with T2DM compared to healthy controls (p = 0.029).

CONCLUSION

This study firstly reported that rs3825199, rs11107116 and rs10492321 in SOCS2 conferred to an increased risk for the occurrence of T2DM in the Chinese Han population. Moreover, SOCS2 mRNA was downregulated in patients with T2DM, suggesting that SOCS2 might have an important role in the occurrence of T2DM.

Determinants in Tailoring Antidiabetic Therapies: A Personalized Approach

Diabetes has become a pandemic as the number of diabetic people continues to rise globally. Being a heterogeneous disease, it has different manifestations and associated complications in different individuals like diabetic nephropathy, neuropathy, retinopathy, and others. With the advent of science and technology, this era desperately requires increasing the pace of embracing precision medicine and tailoring of drug treatment based on the genetic composition of individuals. It has been previously established that response to antidiabetic drugs, like biguanides, sulfonylureas, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide 1 (GLP-1) agonists, and others, depending on variations in their transporter genes, metabolizing genes, genes involved in their action, etc. Responsiveness of these drugs also relies on epigenetic factors, including histone modifications, miRNAs, and DNA methylation, as well as environmental factors and the lifestyle of an individual. For precision medicine to make its way into clinical procedures and come into execution, all these factors must be reckoned with. This review provides an insight into several factors oscillating around the idea of precision medicine in type-2 diabetes mellitus.

Narcolepsy in Parkinson's disease with insulin resistance

Background: Parkinson’s disease (PD) is characterized by its progression of motor-related symptoms such as tremors, rigidity, slowness of movement, and difficulty with walking and balance. Comorbid conditions in PD individuals include insulin resistance (IR) and narcolepsy-like sleep patterns. The intersecting sleep symptoms of both conditions include excessive daytime sleepiness, hallucinations, insomnia, and falling into REM sleep more quickly than an average person. Understanding of the biological basis and relationship of these comorbid disorders with PD may help with early detection and intervention strategies to improve quality of life. Methods: In this study, an integrative genomics and systems biology approach was used to analyze gene expression patterns associated with PD, IR, and narcolepsy in order to identify genes and pathways that may shed light on how these disorders are interrelated. A correlation analysis with known genes associated with these disorders (LRRK2, HLA-DQB1, and HCRT) was used to query microarray data corresponding to brain regions known to be involved in PD and narcolepsy. This includes the hypothalamus, dorsal thalamus, pons, and subcoeruleus nucleus. Risk factor genes for PD, IR, and narcolepsy were also incorporated into the analysis. Results: The PD and narcolepsy signaling networks are connected through insulin and immune system pathways. Important genes and pathways that link PD, narcolepsy, and IR are CACNA1C, CAMK1D, BHLHE41, HMGB1, and AGE-RAGE. Conclusions: We have identified the genetic signatures that link PD with its comorbid disorders, narcolepsy and insulin resistance, from the convergence and intersection of dopaminergic, insulin, and immune system related signaling pathways. These findings may aid in the design of early intervention strategies and treatment regimes for non-motor symptoms in PD patients as well as individuals with diabetes and narcolepsy.

Admixture mapping of anthropometric traits in the Black Women's Health Study: evidence of a shared African ancestry component with birth weight and type 2 diabetes

Prevalence of obesity, type 2 diabetes (T2D), and being born with low birth weight are much higher in African American women compared to U.S. white women. Genetic factors may contribute to the excess risk of these conditions. We conducted admixture mapping of body mass index (BMI) at age 18, adult BMI, and adult waist circumference and waist-to-hip ratio adjusted for BMI using 2918 ancestral informative markers in 2596 participants of the Black Women's Health Study. We also searched for evidence of shared African genetic ancestry components among the four examined anthropometric traits and among birth weight and T2D. We found that global percent African ancestry was associated with higher adult BMI. We also found that African ancestry at 9q34 was associated with lower BMI at age 18. Our shared ancestry analysis identified ten genomic regions with local African ancestry associated with multiple traits. Seven out of these ten genomic loci were related to T2D risk. Of special interest is the 12q14-21 region where local African ancestry was associated with low birth weight, low BMI, high BMI-adjusted waist-to-hip ratio, and high T2D risk. Findings in the 12q14-21 genomic locus are consistent with the fetal insulin hypothesis that postulates that low birth weight and T2D have a common genetic basis, and they support the hypothesis of a shared African genetic ancestry component linking low birth weight and T2D in African Americans. Future studies should identify the actual genetic variants responsible for the clustering of these conditions in African Americans.

Mendelian randomization study reveals a population-specific putative causal effect of type 2 diabetes in risk of cataract

BACKGROUND

The epidemiological association between type 2 diabetes and cataract has been well established. However, it remains unclear whether the two diseases share a genetic basis, and if so, whether this reflects a putative causal relationship.

METHODS

We used East Asian population-based genome-wide association studies (GWAS) summary statistics of type 2 diabetes (Ncase = 36 614, Ncontrol = 155 150) and cataract (Ncase = 24 622, Ncontrol = 187 831) to comprehensively investigate the shared genetics between the two diseases. We performed: (i) linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (ρ-HESS) to estimate the genetic correlation and local genetic correlation pattern between type 2 diabetes and cataract; (ii) multiple Mendelian randomization (MR) analyses to infer the putative causality between type 2 diabetes and cataract; and (iii) summary-data-based Mendelian randomization (SMR) to identify candidate risk genes underling the putative causality. Moreover, to investigate the extent of the population-specific genetic effect size underlying the shared genetics between type 2 diabetes and cataract, we applied the same analytical pipeline to perform a comparative analysis on European population-based GWAS of type 2 diabetes (Ncase = 62 892, Ncontrol = 596 424) and cataract (Ncase = 5045, Ncontrol = 356 096).

RESULTS

Using East Asian population-based GWAS summary data, we observed a strong genetic correlation [rg = 0.58, 95% confidence interval (CI) = 0.33, 0.83), P-value = 5.60 × 10-6] between type 2 diabetes and cataract. Both ρ-HESS and multiple MR methods consistently showed a putative causal effect of type 2 diabetes on cataract, with estimated liability-scale MR odds ratios (ORs) at around 1.10 (95% CI = 1.06, 1.17). In contrast, no evidence supports a causal effect of cataract on type 2 diabetes. SMR analysis identified two novel genes MIR4453HG (βSMR = -0.34, 95% CI = -0.46, -0.22, P-value = 6.41 × 10-8) and KCNK17 (βSMR = -0.07, 95% CI = -0.09, -0.05, P-value = 2.49 × 10-10), whose expression levels were likely involved in the putative causality of type 2 diabetes on cataract. On the contrary, our comparative analysis on European population provided universally weak evidence on the genetic correlation and causal relationship between the two diseases.

CONCLUSIONS

Our results provided robust evidence supporting a putative causal effect of type 2 diabetes on the risk of cataract in East Asians, and revealed potential genetic heterogeneity in the shared genetics underlying type 2 diabetes and cataract between East Asians and Europeans. These findings posed new paths on guiding the prevention and early-stage diagnosis of cataract in type 2 diabetes patients.

Genetics of common cerebral small vessel disease

Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI but does not manifest as clinical stroke, is highly prevalent in the general population, particularly with increasing age. Advances in technologies and collaborative work have led to substantial progress in the identification of common genetic variants that are associated with cSVD-related stroke (ischaemic and haemorrhagic) and MRI-defined covert cSVD. In this Review, we provide an overview of collaborative studies - mostly genome-wide association studies (GWAS) - that have identified >50 independent genetic loci associated with the risk of cSVD. We describe how these associations have provided novel insights into the biological mechanisms involved in cSVD, revealed patterns of shared genetic variation across cSVD traits, and shed new light on the continuum between rare, monogenic and common, multifactorial cSVD. We consider how GWAS summary statistics have been leveraged for Mendelian randomization studies to explore causal pathways in cSVD and provide genetic evidence for drug effects, and how the combination of findings from GWAS with gene expression resources and drug target databases has enabled identification of putative causal genes and provided proof-of-concept for drug repositioning potential. We also discuss opportunities for polygenic risk prediction, multi-ancestry approaches and integration with other omics data.

Stem Cell-Derived β Cells: A Versatile Research Platform to Interrogate the Genetic Basis of β Cell Dysfunction

Pancreatic β cell dysfunction is a central component of diabetes progression. During the last decades, the genetic basis of several monogenic forms of diabetes has been recognized. Genome-wide association studies (GWAS) have also facilitated the identification of common genetic variants associated with an increased risk of diabetes. These studies highlight the importance of impaired β cell function in all forms of diabetes. However, how most of these risk variants confer disease risk, remains unanswered. Understanding the specific contribution of genetic variants and the precise role of their molecular effectors is the next step toward developing treatments that target β cell dysfunction in the era of personalized medicine. Protocols that allow derivation of β cells from pluripotent stem cells, represent a powerful research tool that allows modeling of human development and versatile experimental designs that can be used to shed some light on diabetes pathophysiology. This article reviews different models to study the genetic basis of β cell dysfunction, focusing on the recent advances made possible by stem cell applications in the field of diabetes research.

Network Mendelian randomization study: exploring the causal pathway from insomnia to type 2 diabetes

INTRODUCTION

Insomnia is a novel pathogen for type 2 diabetes mellitus (T2DM). However, mechanisms linking insomnia and T2DM are poorly understood. In this study, we apply a network Mendelian randomization (MR) framework to determine the causal association between insomnia and T2DM and identify the potential mediators, including overweight (body mass index (BMI), waist-to-hip ratio, and body fat percentage) and glycometabolism (HbA1c, fasting blood glucose, and fasting blood insulin).

RESEARCH DESIGN AND METHODS

We use the MR framework to detect effect estimates of the insomnia-T2DM, insomnia-mediator, and mediator-T2DM associations. A mediator between insomnia and T2DM is established if MR studies in all 3 steps prove causal associations.

RESULTS

In the Inverse variance weighted method, the results show that insomnia will increase the T2DM risk (OR 1.142; 95% CI 1.072 to 1.216; p=0.000), without heterogeneity nor horizontal pleiotropy, strongly suggesting that genetically predicted insomnia has a causal association with T2DM. Besides, our MR analysis provides strong evidence that insomnia is causally associated with BMI and body fat percentage. There is also suggestive evidence of an association between insomnia and the waist-to-hip ratio. At the same time, our results indicate that insomnia is not causally associated with glycometabolism. Higher BMI, waist-to-hip ratio, and body fat percentage levels are strongly associated with increased risk of T2DM.

CONCLUSIONS

Genetically predicted insomnia has a causal association with T2DM. Being overweight (especially BMI and body fat percentage) mediates the causal pathway from insomnia to T2DM.

Genetically Predicted Causality of 28 Gut Microbiome Families and Type 2 Diabetes Mellitus Risk

Mounting evidence indicates that gut microbiome may be involved in the pathogenesis of type 2 diabetes mellitus (T2DM). However, there is no consensus on whether there is a causal link between gut microbiome and T2DM risk. In the present study, the Mendelian randomization (MR) analysis was performed to investigate whether gut microbiome was causally linked to T2DM risk. The single nucleotide polymorphisms (SNPs) that were significantly related to exposure from published available genome-wide association study (GWAS) were selected as instrumental variables (IVs). The robust methods including inverse variance weighting (IVW), MR Egger, and weighted median were conducted to infer the causal links. Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression were used to test whether there was horizontal pleiotropy and identify outlier SNPs. The estimates of IVW suggested that Streptococcaceae (odds ratio (OR) = 1.17, 95% confidence interval (CI), 1.04-1.31, p = 0.009) was associated with higher risk of T2DM in European population. In Asian population, the MR IVW estimates revealed that there was a causal link between Acidaminococcaceae and T2DM risk (OR = 1.17, 95% CI, 1.04-1.31, p = 0.008). There was no evidence of notable heterogeneity and horizontal pleiotropy. However, after false discovery rate (FDR) correction, the causal link between gut microbiome and T2DM was absent (FDR, p > 0.05). In summary, using genetic instruments, this study does not find evidence of association between the 28 gut microbiome families and T2DM risk. However, Streptococcaceae and Acidaminococcaceae may have a borderline positive correlation with T2DM risk.

OUP accepted manuscript

Type 2 diabetes is a complex, systemic disease affected by both genetic and environmental factors. Previous research has identified genetic variants associated with type 2 diabetes risk; however, gene regulatory changes underlying progression to metabolic dysfunction are still largely unknown. We investigated RNA expression changes that occur during diabetes progression using a two-stage approach. In our discovery stage, we compared changes in gene expression using two longitudinally collected blood samples from subjects whose fasting blood glucose transitioned to a level consistent with type 2 diabetes diagnosis between the time points against those who did not with a novel analytical network approach. Our network methodology identified 17 networks, one of which was significantly associated with transition status. This 822-gene network harbors many genes novel to the type 2 diabetes literature but is also significantly enriched for genes previously associated with type 2 diabetes. In the validation stage, we queried associations of genetically determined expression with diabetes-related traits in a large biobank with linked electronic health records. We observed a significant enrichment of genes in our identified network whose genetically determined expression is associated with type 2 diabetes and other metabolic traits and validated 31 genes that are not near previously reported type 2 diabetes loci. Finally, we provide additional functional support, which suggests that the genes in this network are regulated by enhancers that operate in human pancreatic islet cells. We present an innovative and systematic approach that identified and validated key gene expression changes associated with type 2 diabetes transition status and demonstrated their translational relevance in a large clinical resource.

Association between exposure to earthquake in early life and diabetes mellitus incidence in adulthood with the modification of lifestyles: Results from the Kailuan study

BACKGROUND

Exposure to disasters in early life may induce lifetime health risk, but investigation on earthquake exposure and DM in later life is still limited. The aim of the current study is to evaluate the association between exposure to the Tangshan Earthquake in early life and diabetes mellitus (DM) incidence in adulthood, and explore the modification of lifestyles on DM development.

METHODS

Participants who were free of DM at baseline from the Kailuan Study were included in this study. All participants were divided into fetal-exposed, infant-exposed, early childhood-exposed and nonexposed group. The effect of earthquake exposure on DM and modification of lifestyles were examined by multivariable-adjusted Cox proportional hazard model.

RESULTS

The exposed group had a higher risk of DM than nonexposed group, especially in infant-exposed and early childhood-exposed group, with hazard ratio (HR) of 1.62 [95% confidence intervals (CI), 1.21-2.17] and 1.46 (95% CI, 1.06-1.99), respectively. After stratifying by lifestyles, a significant modification was observed in alcohol consumption.

CONCLUSION

Exposing to earthquake in early life could increase DM incidence in later life, and alcohol consumption might modify the effect of earthquake exposure on DM development. More attention should be paid on the preventions of DM among adults who exposed to earthquake in their early life.

Effects of Gut Microbiota and Metabolites on Heart Failure and Its Risk Factors: A Two-Sample Mendelian Randomization Study

Introduction

Previous observational studies have indicated that gut microbiota and metabolites may contribute to heart failure and its risk factors. However, with the limitation of reverse causality and confounder in observational studies, such relationship remains unclear. This study aims to reveal the causal effect of gut microbiota and metabolites on heart failure and its risk factors.

Methods

This study collected summary statistics regarding gut microbiota and metabolites, heart failure, diabetes, hypertension, chronic kidney disease, myocardial infarction, atrial fibrillation, hypertrophic cardiomyopathy, dilated cardiomyopathy, coronary heart disease, valvular heart disease, and myocarditis. Two-sample Mendelian randomization analysis was performed using MR-Egger, inverse variance weighted (IVW), MR-PRESSO, maximum likelihood, and weighted median.

Results

Results from gene prediction showed that among all gut microbiota, candida, shigella, and campylobacter were not associated with higher incidence of heart failure. However, genetic prediction suggested that for every 1 unit increase in shigella concentration, the relative risk increased by 38.1% for myocarditis and 13.3% for hypertrophic cardiomyopathy. Besides, for every 1 unit increased in candida concentration, the relative risk of chronic kidney disease increased by 7.1%. As for intestinal metabolites, genetic prediction results suggested that for every 1 unit increase in betaine, the relative risk of heart failure and myocardial infarction increased by 1.4% and 1.7%, separately.

Conclusions

This study suggested new evidence of the relationship between gut microbiota and heart failure and its risk factors, which may shed light on designing microbiome- and microbiome-dependent metabolite interventions on heart failure and its risk factors in clinical trials in the future.

Causal Associations of Obesity With Achilles Tendinopathy: A Two-Sample Mendelian Randomization Study

BACKGROUND

Achilles tendinopathy (AT) is associated with severe pain and is the cause of dysfunction and disability that are associated with significant reduction in social and economic benefits. Several potential risk factors have been proposed to be responsible for AT development; however, the results of observational epidemiological studies remain controversial, presumably because the designs of these studies are subject to residual confounding and reverse causality. Mendelian randomization (MR) can infer the causality between exposure and disease outcomes using genetic variants as instrumental variables, and identification of the causal risk factors for AT is beneficial for early intervention. Thus, we employed the MR strategy to evaluate the causal associations between previously reported risk factors (anthropometric parameters, lifestyle factors, blood biomarkers, and systemic diseases) and the risk of AT.

METHODS

Univariable MR was performed to screen for potential causal associations between the putative risk factors and AT. Bidirectional MR was used to infer reverse causality. Multivariable MR was conducted to investigate the body mass index (BMI)-independent causal effect of other obesity-related traits, such as the waist-hip ratio, on AT.

RESULTS

Univariable MR analyses with the inverse-variance weighted method indicated that the genetically predicted BMI was significantly associated with the risk of AT (P=2.0×10^-3), and the odds ratios (95% confidence intervals) is 1.44 (1.14-1.81) per 1-SD increase in BMI. For the other tested risk factors, no causality with AT was identified using any of the MR methods. Bidirectional MR suggested that AT was not causally associated with BMI, and multivariable MR indicated that other anthropometric parameters included in this study were not likely to causally associate with the risk of AT after adjusting for BMI.

CONCLUSIONS

The causal association between BMI and AT risk suggests that weight control is a promising strategy for preventing AT and alleviating the corresponding disease burden.

Association of ADIPOQ Single-Nucleotide Polymorphisms with the Two Clinical Phenotypes Type 2 Diabetes Mellitus and Metabolic Syndrome in a Kinh Vietnamese Population

PURPOSE

Genetic factors play an important role in the development of type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS). However, few genetic association studies related to these disorders have been performed with Vietnamese subjects. In this study, the potential associations of ADIPOQ single nucleotide polymorphisms (SNPs) with T2DM and MetS in a Kinh Vietnamese population were investigated.

PATIENTS AND METHODS

A study with 768 subjects was conducted to examine the associations of four ADIPOQ SNPs (rs266729, rs1501299, rs3774261, and rs822393) primarily with T2DM and secondarily with MetS. The TaqMan SNP genotyping assay was used to determine genotypes from subjects' DNA samples.

RESULTS

After statistical adjustment for age, sex, and body mass index, the ADIPOQ SNP rs266729 was found to be associated with increased risk of T2DM under multiple inheritance models: codominant (OR = 2.30, 95% CI = 1.16-4.58), recessive (OR = 2.17, 95% CI = 1.11-4.26), and log-additive (OR = 1.32, 95% CI = 1.02-1.70). However, rs1501299, rs3774261, and rs822393 were not associated with risk for T2DM. Additionally, rs266729, rs3774261, and rs822393 were statistically associated with MetS, while rs1501299 was not. Haplotype analysis showed a strong linkage disequilibrium between the SNP pairs rs266729/rs822393 and rs1501299/rs3774261, and the haplotype rs266729(G)/rs822393(T) was not statistically associated with MetS.

CONCLUSION

The results show that rs266729 is a lead candidate SNP associated with increased risk of developing T2DM and MetS in a Kinh Vietnamese population, while rs3774261 is associated with MetS only. Further functional characterization is needed to uncover the mechanism underlying the potential genotype-phenotype associations.

Physical activity, sedentary behavior, and the risk of type 2 diabetes: A two-sample Mendelian Randomization analysis in the European population

Physical activity (PA) and sedentary behaviors (SB) have been linked to the risk of type 2 diabetes (T2DM) in observational studies; however, it is unclear whether these associations are causative or confounded. This study intends to use summary genetic data from the UK Biobank and other consortiums in conjunction with the two-sample Mendelian Randomization (MR) approach to solve this problem. The inverse variance weighted (IVW) technique was utilized as the primary analysis, with sensitivity analyses using the MR-Egger, weighted-median, and MR-Pleiotropy RESidual Sum and Outlier (PRESSO) techniques. Inverse associations between self-reported moderate PA (OR: 0.3096, 95% CI: 0.1782-0.5380) and vigorous PA (OR: 0.2747, 95% CI: 0.1390-0.5428) with T2DM risk were found, respectively. However, accelerometer-based PA measurement (average acceleration) was not associated with T2DM risk (OR: 1.0284, 95% CI: 0.9831-1.0758). The time (hours/day) spent watching TV was associated with T2DM risk (OR: 2.3490, 95% CI: 1.9084-2.8915), while the time (hours/day) spent using the computer (OR: 0.8496, 95% CI: 0.7178-1.0056), and driving (OR: 3.0679, 95% CI: 0.8448-11.1415) were not associated with T2DM risk. The sensitivity analysis revealed relationships of a similar magnitude. Our study revealed that more PA and less TV viewing were related to a decreased T2DM risk, and provided genetic support for a causal relationship between PA, TV viewing, and T2DM risk.

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Analysis of rare coding variants in 200,000 exome-sequenced subjects reveals novel genetic risk factors for type 2 diabetes

AIMS

The study aimed to elucidate the effects of rare genetic variants on the risk of type 2 diabetes (T2D).

MATERIALS AND METHODS

Weighted burden analysis of rare variants was applied to a sample of 200,000 exome-sequenced participants in the UK Biobank project, of whom over 13,000 were identified as having T2D. Variant weights were allocated based on allele frequency and predicted effect, as informed by a previous analysis of hyperlipidaemia.

RESULTS

There was an exome-wide significant increased burden of rare, functional variants in three genes, GCK, HNF4A and GIGYF1. GIGYF1 has not previously been identified as a diabetes risk gene and its product appears to be involved in the modification of insulin signalling. A number of other genes did not attain exome-wide significance but were highly ranked and potentially of interest, including ALAD, PPARG, GYG1 and GHRL. Loss of function (LOF) variants were associated with T2D in GCK and GIGYF1 whereas nonsynonymous variants annotated as probably damaging were associated in GCK and HNF4A. Overall, fewer than 1% of T2D cases carried one of these variants. In HNF1A and HNF1B there was an excess of LOF variants among cases but the small numbers of these fell short of statistical significance.

CONCLUSIONS

Rare genetic variants make an identifiable contribution to T2D in a small number of cases but these may provide valuable insights into disease mechanisms. As larger samples become available it is likely that additional genetic factors will be identified.

The role of obesity, type 2 diabetes, and metabolic factors in gout: A Mendelian randomization study

BACKGROUND

Several epidemiological studies have reported a possible correlation between risk of gout and metabolic disorders including type 2 diabetes, insulin resistance, obesity, dyslipidemia, and hypertension. However, it is unclear if this association is causal.

METHODS

We used Mendelian randomization (MR) to evaluate the causal relation between metabolic conditions and gout or serum urate concentration by inverse-variance-weighted (conventional) and weighted median methods. Furthermore, MR-Egger regression and MR-pleiotropy residual sum and outlier (PRESSO) method were used to explore pleiotropy. Genetic instruments for metabolic disorders and outcome (gout and serum urate) were obtained from several genome-wide association studies on individuals of mainly European ancestry.

RESULTS

Conventional MR analysis showed a robust causal association of increasing obesity measured by body mass index (BMI), high-density lipoprotein cholesterol (HDL), and systolic blood pressure (SBP) with risk of gout. A causal relationship between fasting insulin, BMI, HDL, triglycerides (TG), SBP, alanine aminotransferase (ALT), and serum urate was also observed. These results were consistent in weighted median method and MR-PRESSO after removing outliers identified. Our analysis also indicated that HDL and serum urate as well as gout have a bidirectional causal effect on each other.

CONCLUSIONS

Our study suggested causal effects between glycemic traits, obesity, dyslipidemia, blood pressure, liver function, and serum urate as well as gout, which implies that metabolic factors contribute to the development of gout via serum urate, as well as potential benefit of sound management of increased serum urate in patients with obesity, dyslipidemia, hypertension, and liver dysfunction.

Mendelian randomization supports the causal role of fasting glucose on periodontitis

PURPOSE

The effect of hyperglycemia on periodontitis is mainly based on observational studies, and inconsistent results were found whether periodontal treatment favors glycemic control. The two-way relationship between periodontitis and hyperglycemia needs to be further elucidated. This study aims to evaluate the causal association of periodontitis with glycemic traits using bi-directional Mendelian randomization (MR) approach.

METHODS

Summary statistics were sourced from large-scale genome-wide association study conducted for fasting glucose (N = 133,010), HbA1c (N = 123,665), type 2 diabetes (T2D, N = 659,316), and periodontitis (N = 506,594) among European ancestry. The causal relationship was estimated using the inverse-variance weighted (IVW) model and further validated through extensive complementary and sensitivity analyses.

RESULTS

Overall, IVW showed that a genetically higher level of fasting glucose was significantly associated with periodontitis (OR = 1.119; 95% CI = 1.045-1.197; P_FDR= 0.007) after removing the outlying instruments. Such association was robust and consistent through other MR models. Limited evidence was found suggesting the association of HbA1C with periodontitis after excluding the outliers (IVW OR = 1.123; 95% CI = 1.026-1.229; P_FDR= 0.048). These linkages remained statistically significant in multivariate MR analyses, after adjusting for body mass index. The reverse direction MR analyses did not exhibit the causal association of genetic liability to periodontitis with any of the glycemic trait tested.

CONCLUSIONS

Our MR study reaffirms previous findings and extends evidence to substantiate the causal effect of hyperglycemia on periodontitis. Future studies with robust genetic instruments are needed to confirm the causal association of periodontitis with glycemic traits.

Lifestyle Modifies the Diabetes-Related Metabolic Risk, Conditional on Individual Genetic Differences

Metabolic syndrome is a group of heritable metabolic traits that are highly associated with type 2 diabetes (T2DM). Classical interventions to T2DM include individual self-management of environmental risk factors, such as improving diet quality, increasing physical activity, and reducing smoking and alcohol consumption, which decreases the risk of developing metabolic syndrome. However, it is poorly understood how the phenotypes of diabetes-related metabolic traits change with respect to lifestyle modifications at the individual level. In the analysis, we used 12 diabetes-related metabolic traits and eight lifestyle covariates from the UK Biobank comprising 288,837 white British participants genotyped for 1,133,273 genome-wide single nucleotide polymorphisms. We found 16 GxE interactions. Modulation of genetic effects by physical activity was seen for four traits (glucose, HbA1c, C-reactive protein, systolic blood pressure) and by alcohol and smoking for three (BMI, glucose, waist-hip ratio and BMI and diastolic and systolic blood pressure, respectively). We also found a number of significant phenotypic modulations by the lifestyle covariates, which were not attributed to the genetic effects in the model. Overall, modulation in the metabolic risk in response to the level of lifestyle covariates was clearly observed, and its direction and magnitude were varied depending on individual differences. We also showed that the metabolic risk inferred by our model was notably higher in T2DM prospective cases than controls. Our findings highlight the importance of individual genetic differences in the prevention and management of diabetes and suggest that the one-size-fits-all approach may not benefit all.

The Association between Fasting Glucose and Sugar Sweetened Beverages Intake Is Greater in Latin Americans with a High Polygenic Risk Score for Type 2 Diabetes Mellitus

Chile is one of the largest consumers of sugar-sweetened beverages (SSB) world-wide. However, it is unknown whether the effects from this highly industrialized food will mimic those reported in industrialized countries or whether they will be modified by local lifestyle or population genetics. Our goal is to evaluate the interaction effect between SSB intake and T2D susceptibility on fasting glucose. We calculated a weighted genetic risk score (GRSw) based on 16 T2D risk SNPs in 2828 non-diabetic participants of the MAUCO cohort. SSB intake was categorized in four levels using a food frequency questionnaire. Log-fasting glucose was regressed on SSB and GRSw tertiles while accounting for socio-demography, lifestyle, obesity, and Amerindian ancestry. Fasting glucose increased systematically per unit of GRSw (β = 0.02 ± 0.006, p = 0.00002) and by SSB intake (β[cat4] = 0.04 ± 0.01, p = 0.0001), showing a significant interaction, where the strongest effect was observed in the highest GRSw-tertile and in the highest SSB consumption category (β = 0.05 ± 0.02, p = 0.02). SNP-wise, SSB interacted with additive effects of rs7903146 (TCF7L2) (β = 0.05 ± 0.01, p = 0.002) and with the G/G genotype of rs10830963 (MTNRB1B) (β = 0.19 ± 0.05, p = 0.001). Conclusions: The association between SSB intake and fasting glucose in the Chilean population without diabetes is modified by T2D genetic susceptibility.

A Core Omnigenic Non-coding Trait Governing Dex-Induced Osteoporotic Effects Identified Without DEXA

Iatrogenic glucocorticoid (GC)-induced osteoporosis (GIO) is an idiosyncratic form of secondary osteoporosis. Genetic predisposition among individuals may give rise to variant degree of phenotypic changes but there has yet been a documented unified pathway to explain the idiosyncrasy. In this study, we argue that the susceptibility to epigenetic changes governing molecular cross talks along the BMP and PI3K/Akt pathway may underline how genetic background dictate GC-induced bone loss. Concordantly, osteoblasts from BALB/c or C57BL/6 neonatal mice were treated with dexamethasone for transcriptome profiling. Furthermore, we also confirmed that GC-pre-conditioned mesenchymal stem cells (MSCs) would give rise to defective osteogenesis by instigating epigenetic changes which affected the accessibility of enhancer marks. In line with these epigenetic changes, we propose that GC modulates a key regulatory network involving the scavenger receptor Cd36 in osteoblasts pre-conditioning pharmacological idiosyncrasy in GIO.

Sex differences in the genetic regulation of the blood transcriptome response to glucocorticoid receptor activation

Substantial sex differences have been reported in the physiological response to stress at multiple levels, including the release of the stress hormone, cortisol. Here, we explore the genomic variants in 93 females and 196 males regulating the initial transcriptional response to cortisol via glucocorticoid receptor (GR) activation. Gene expression levels in peripheral blood were obtained before and after GR-stimulation with the selective GR agonist dexamethasone to identify differential expression following GR-activation. Sex stratified analyses revealed that while the transcripts responsive to GR-stimulation were mostly overlapping between males and females, the quantitative trait loci (eQTLs) regulation differential transcription to GR-stimulation was distinct. Sex-stratified eQTL SNPs (eSNPs) were located in different functional genomic elements and sex-stratified transcripts were enriched within postmortem brain transcriptional profiles associated with Major Depressive Disorder (MDD) specifically in males and females in the cingulate cortex. Female eSNPs were enriched among SNPs linked to MDD in genome-wide association studies. Finally, transcriptional sensitive genetic profile scores derived from sex-stratified eSNPS regulating differential transcription to GR-stimulation were predictive of depression status and depressive symptoms in a sex-concordant manner in a child and adolescent cohort (n = 584). These results suggest the potential of eQTLs regulating differential transcription to GR-stimulation as biomarkers of sex-specific biological risk for stress-related psychiatric disorders.

Genetic Liability to Cannabis Use Disorder and COVID-19 Hospitalization

BACKGROUND

Vulnerability to COVID-19 hospitalization has been linked to behavioral risk factors, including combustible psychoactive substance use (e.g., tobacco smoking). Paralleling the COVID-19 pandemic crisis have been increasingly permissive laws for recreational cannabis use. Cannabis use disorder (CUD) is a psychiatric disorder that is heritable and genetically correlated with respiratory disease, independent of tobacco smoking. We examined the genetic relationship between CUD and COVID-19 hospitalization.

METHODS

We estimated the genetic correlation between CUD (case: n = 14,080; control: n = 343,726) and COVID-19 hospitalization (case: n = 9373; control: n = 1,197,256) using summary statistics from genome-wide association studies. Using independent genome-wide association studies conducted before the pandemic, we controlled for several covariates (i.e., tobacco use phenotypes, problematic alcohol use, body mass index, fasting glucose, forced expiratory volume, education attainment, risk taking, attention-deficit/hyperactivity disorder, Townsend deprivation index, chronic obstructive pulmonary disease, hypertension, and type 2 diabetes) using genomic structural equation modeling. Genetic causality between CUD and COVID-19 hospitalization was estimated using latent causal variable models.

RESULTS

Genetic vulnerability to COVID-19 was correlated with genetic liability to CUD (r G  = 0.423 [SE = 0.0965], p = 1.33 × 10-6); this association remained when accounting for genetic liability to related risk factors and covariates (b = 0.381-0.539, p = .012-.049). Latent causal variable analysis revealed causal effect estimates that were not statistically significant.

CONCLUSIONS

Problematic cannabis use and vulnerability to serious COVID-19 complications share genetic underpinnings that are unique from common correlates. While CUD may plausibly contribute to severe COVID-19 presentations, causal inference models yielded no evidence of putative causation. Curbing excessive cannabis use may mitigate the impact of COVID-19.

Towards organism-level systems biology by next-generation genetics and whole-organ cell profiling

The system-level identification and analysis of molecular and cellular networks in mammals can be accelerated by "next-generation" genetics, which is defined as genetics that can achieve desired genetic makeup in a single generation without any animal crossing. We recently established a highly efficient procedure for producing knock-out (KO) mice using the "Triple-CRISPR" method, which targets a single gene by triple gRNAs in the CRISPR/Cas9 system. This procedure achieved an almost perfect KO efficiency (96-100%). We also established a highly efficient procedure, the "ES-mouse" method, for producing knock-in (KI) mice within a single generation. In this method, ES cells were treated with three inhibitors to keep their potency and then injected into 8-cell-stage embryos. These procedures dramatically shortened the time required to produce KO or KI mice from years down to about 3 months. The produced KO and KI mice can also be systematically profiled at a single-cell resolution by the "whole-organ cell profiling," which was realized by tissue-clearing methods, such as CUBIC, and an advanced light-sheet microscopy. The review describes the establishment and application of these technologies above in analyzing the three states (NREM sleep, REM sleep, and awake) of mammalian brains. It also discusses the role of calcium and muscarinic receptors in these states as well as the current challenges and future opportunities in the next-generation mammalian genetics and whole-organ cell profiling for organism-level systems biology.

Association of ACE I/D and PAI-1 4G/5G polymorphisms with susceptibility to type 2 diabetes mellitus

BACKGROUND

A number of studies were carried out to assess the association of angiotensin I converting enzyme (ACE) I/D and plasminogen activator inhibitor-1 (PAI-1-1) 4G/5G polymorphisms with susceptibility to type 2 diabetes mellitus (T2DM). However, there are a few studies in Iranian patients with T2DM. Here, we tested for an association of ACE I/D and PAI-1 4G/5G polymorphisms with T2DM risk.

METHODS

One hundred-eighteen patients with T2DM and 125 healthy subjects were participates in this study. The ACE I/D (rs4340) and PAI-1 4G/5G (rs1799889) polymorphisms was genotyped by conventional and PCR-RFLP assays, receptively. The associations was evaluated by calculating the odds ratio (OR) and 95% confidence interval (95% CI).

RESULTS

The genotype distribution of ACE I/D and PAI-1 4G/5G polymorphisms were not deviated from the Hardy-Weinberg equilibrium in healthy controls. The ACE II, ID, and DD genotype frequencies were 18.6%, 48.3%, and 33.1% in the T2DM patients versus 24.0%, 45.6% and 30.4% in healthy subjects, respectively. The PAI-1 4G/4G, 4G/5G, and 5G/5G genotype frequencies were 16.9%, 51.7%, and 31.4% in cases versus 24.8%, 57.6% and 17.6% in controls, respectively. There is a significant distribution in genotype/allele of PAI-1 4G/4G between cases with T2DM and healthy control, but not for ACE I/D. Moreover, the 5G/5G genotype is significantly (OR = 2.139, CI 95% 1.171-3.907, p = 0.013) increased the risk of T2DM by two folds in the cases than healthy controls.

CONCLUSIONS

Our findings suggest that PAI-1 4G/5G may be likelihood risk factor for the development of T2DM in the Iranian patients. The higher frequency of PAI-1 5G/5G genotype in patients with T2DM revealed that individuals with the 5G allele may be at higher risk of T2DM development than those with 4G. However, there was no significant association between ACE I/D polymorphism and T2DM in our population. Future rigorous, well-designed studies with larger sample should replicate this study to confirm our findings in Iranian T2DM patients.

TCF7L2 lncRNA: a link between bipolar disorder and body mass index through glucocorticoid signaling

Bipolar disorder (BD) and obesity are highly comorbid. We previously performed a genome-wide association study (GWAS) for BD risk accounting for the effect of body mass index (BMI), which identified a genome-wide significant single-nucleotide polymorphism (SNP) in the gene encoding the transcription factor 7 like 2 (TCF7L2). However, the molecular function of TCF7L2 in the central nervous system (CNS) and its possible role in the BD and BMI interaction remained unclear. In the present study, we demonstrated by studying human induced pluripotent stem cell (hiPSC)-derived astrocytes, cells that highly express TCF7L2 in the CNS, that the BD-BMI GWAS risk SNP is associated with glucocorticoid-dependent repression of the expression of a previously uncharacterized TCF7L2 transcript variant. That transcript is a long non-coding RNA (lncRNA-TCF7L2) that is highly expressed in the CNS but not in peripheral tissues such as the liver and pancreas that are involved in metabolism. In astrocytes, knockdown of the lncRNA-TCF7L2 resulted in decreased expression of the parent gene, TCF7L2, as well as alterations in the expression of a series of genes involved in insulin signaling and diabetes. We also studied the function of TCF7L2 in hiPSC-derived astrocytes by integrating RNA sequencing data after TCF7L2 knockdown with TCF7L2 chromatin-immunoprecipitation sequencing (ChIP-seq) data. Those studies showed that TCF7L2 directly regulated a series of BD risk genes. In summary, these results support the existence of a CNS-based mechanism underlying BD-BMI genetic risk, a mechanism based on a glucocorticoid-dependent expression quantitative trait locus that regulates the expression of a novel TCF7L2 non-coding transcript.

The association of ABO blood group with the asymptomatic COVID-19 cases in India

The COVID-19 pandemic resulted in multiple waves of infection worldwide. The large variations in case fatality rate among different geographical regions suggest that the human susceptibility against this virus varies substantially. Several studies from different parts of the world showed a significant association of ABO blood group and COVID-19 susceptibility. It was demonstrated that individuals with blood group O are at the lower risk of coronavirus infection. To establish the association of ABO blood group in SARS-CoV-2 susceptibility, we for the first time analysed SARS-CoV-2 neutralising antibodies among 509 individuals, collected from three major districts of Eastern Uttar Pradesh region of India. Interestingly, we found neutralising antibodies in a significantly higher percentage of people with blood group AB (0.36) followed by B (0.31), A (0.22) and lowest in people with blood group O (0.11). We further estimated that people with blood group AB are at comparatively higher risk of infection than other blood groups. Thus, among the asymptomatic SARS-CoV-2 recovered people blood group AB has highest, whilst individuals with blood group O has lowest risk of infection.

The impact of race and socioeconomic factors on paediatric diabetes

There are over 29,000 children and young people (CYP) with Type 1 diabetes mellitus (T1DM) in England and Wales and another 726 with Type 2 diabetes mellitus (T2DM). There is little effect of deprivation on the prevalence of T1DM whereas the association of deprivation on the percentage of CYP with T2DM is striking with 45% of cases drawn from the most deprived backgrounds. A number that has not changed over the last 4 years. Data from the UK and USA as well as other countries demonstrate the impact of deprivation on outcomes in diabetes mellitus with clear effects on measures of long-term control and complications. In the UK black CYP had higher glycosylated haemoglobin (HbA1c) values compared to other groups. Within the black group, CYP from a Caribbean background had a higher mean HbA1c (77.0 mmol/mol (9.2%)) than those from Africa (70.4 mmol/mol (8.6%)). Treatment regimen (multiple daily injections or insulin pump therapy) explained the largest proportion of the variability in HbA1c followed by deprivation. Those in the least deprived areas had an average HbA1c 5.88 mmol/mol (0.5%) lower than those living in the most deprived areas. The picture is complex as UK data also show that deprivation and ethnicity is associated with less use of technology that is likely to improve diabetes control. Increased usage of pump therapy and continuous glucose monitoring was associated with a younger age of patient (less than 10 years of age), living in the least deprived areas and white ethnicity. This gap between pump usage amongst CYP with T1DM living in the most and least deprived areas has widened with time. In 2014/15 the gap was 7.9% and by 2018/19 had increased to 13.5%. To attain an equitable service for CYP with diabetes mellitus we need to consider interventions at the patient, health care professional, community, and health care system levels.