Identification of type 2 diabetes loci in 433,540 East Asian individuals

Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

Meta-analysis is pervasively used to combine multiple genome-wide association studies (GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort study. Here, we first demonstrate that heterogeneity (e.g., of sample size, phenotyping, imputation) hurts calibration of meta-analysis fine-mapping. We propose a summary statistics-based quality-control (QC) method, suspicious loci analysis of meta-analysis summary statistics (SLALOM), that identifies suspicious loci for meta-analysis fine-mapping by detecting outliers in association statistics. We validate SLALOM in simulations and the GWAS Catalog. Applying SLALOM to 14 meta-analyses from the Global Biobank Meta-analysis Initiative (GBMI), we find that 67% of loci show suspicious patterns that call into question fine-mapping accuracy. These predicted suspicious loci are significantly depleted for having nonsynonymous variants as lead variant (2.7×; Fisher's exact p = 7.3 × 10^-4). We find limited evidence of fine-mapping improvement in the GBMI meta-analyses compared with individual biobanks. We urge extreme caution when interpreting fine-mapping results from meta-analysis of heterogeneous cohorts.

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture

BACKGROUND

Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D.

METHOD

A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets.

RESULTS

We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy).

CONCLUSION

The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies

In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.

Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes

AIMS/HYPOTHESIS

We sought to subtype South East Asian patients with type 2 diabetes by de novo cluster analysis on clinical variables, and to determine whether the novel subgroups carry distinct genetic and lipidomic features as well as differential cardio-renal risks.

METHODS

Analysis by k-means algorithm was performed in 687 participants with recent-onset diabetes in Singapore. Genetic risk for beta cell dysfunction was assessed by polygenic risk score. We used a discovery-validation approach for the lipidomics study. Risks for cardio-renal complications were studied by survival analysis.

RESULTS

Cluster analysis identified three novel diabetic subgroups, i.e. mild obesity-related diabetes (MOD, 45%), mild age-related diabetes with insulin insufficiency (MARD-II, 36%) and severe insulin-resistant diabetes with relative insulin insufficiency (SIRD-RII, 19%). Compared with the MOD subgroup, MARD-II had a higher polygenic risk score for beta cell dysfunction. The SIRD-RII subgroup had higher levels of sphingolipids (ceramides and sphingomyelins) and glycerophospholipids (phosphatidylethanolamine and phosphatidylcholine), whereas the MARD-II subgroup had lower levels of sphingolipids and glycerophospholipids but higher levels of lysophosphatidylcholines. Over a median of 7.3 years follow-up, the SIRD-RII subgroup had the highest risks for incident heart failure and progressive kidney disease, while the MARD-II subgroup had moderately elevated risk for kidney disease progression.

CONCLUSIONS/INTERPRETATION

Cluster analysis on clinical variables identified novel subgroups with distinct genetic, lipidomic signatures and varying cardio-renal risks in South East Asian participants with type 2 diabetes. Our study suggests that this easily actionable approach may be adapted in other ethnic populations to stratify the heterogeneous type 2 diabetes population for precision medicine.

Immunoglobulin G N-glycan, inflammation and type 2 diabetes in East Asian and European populations: a Mendelian randomization study

Background

Immunoglobulin G (IgG) N-glycans have been shown to be associated with the risk of type 2 diabetes (T2D) and its risk factors. However, whether these associations reflect causal effects remain unclear. Furthermore, the associations of IgG N-glycans and inflammation are not fully understood.

Methods

We examined the causal associations of IgG N-glycans with inflammation (C-reactive protein (CRP) and fibrinogen) and T2D using two-sample Mendelian randomization (MR) analysis in East Asian and European populations. Genetic variants from IgG N-glycan quantitative trait loci (QTL) data were used as instrumental variables. Two-sample MR was conducted for IgG N-glycans with inflammation (75,391 and 18,348 participants of CRP and fibrinogen in the East Asian population, 204,402 participants of CRP in the European population) and T2D risk (77,418 cases and 356,122 controls of East Asian ancestry, 81,412 cases and 370,832 controls of European ancestry).

Results

After correcting for multiple testing, in the East Asian population, genetically determined IgG N-glycans were associated with a higher risk of T2D, the odds ratios (ORs) were 1.009 for T2D per 1- standard deviation (SD) higher GP5, 95% CI = 1.003–1.015; P = 0.0019; and 1.013 for T2D per 1-SD higher GP13, 95% CI = 1.006–1.021; P = 0.0005. In the European population, genetically determined decreased GP9 was associated with T2D (OR = 0.899 per 1-SD lower GP9, 95% CI: 0.845–0.957). In addition, there was suggestive evidence that genetically determined IgG N-glycans were associated with CRP in both East Asian and European populations after correcting for multiple testing, but no associations were found between IgG N-glycans and fibrinogen. There was limited evidence of heterogeneity and pleiotropy bias.

Conclusions

Our results provided novel genetic evidence that IgG N-glycans are causally associated with T2D.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00543-z.

Positive association between research competitiveness of Chinese academic hospitals and the scale of their biobanks: A national survey

Biobanks are important research infrastructure developed rapidly by Chinese hospitals. The objective of this study is to investigate the association between the comprehensive research competitiveness of hospitals and the development of hospital biobanks. In 2018, we conducted a national survey among Chinese biobank managers and directors. An online questionnaire was used to collect data of biobank characteristics. Of the 70 academic hospital biobanks responded to our survey, 49 of their hospitals were listed in the Science and Technology Evaluation Metrics (STEM) and 46 of their hospitals were listed in the Fudan Hospital Rankings, respectively, in 2018. Hospital scores from the STEM and Fudan Hospital Rankings were identified from their official websites. Multivariate linear regression analyses were used to assess the associations of STEM scores and Fudan Hospital Rankings with the scale of biobanks. The overall STEM score, Scientific and Technological Output, and Academic Impact in hospitals with large-scale biobanks were 48.35%, 55.16%, and 58.65% higher than those with small-scale biobanks, respectively. The scale of biobanks was positively associated with STEM score (β = 0.367, p = 0.009), Scientific and Technological Output (β = 0.441, p = 0.001), and Academic Impact (β = 0.304, p = 0.044) after adjustment for potential confounders. For Fudan Hospital Rankings, the comprehensive score and sustainable development ability score were higher in hospitals with large-scale biobanks. Further analyses showed that the scale of the biobanks was positively associated with a higher comprehensive score (β = 0.313, p = 0.037) and a sustainable development ability score (β = 0.463, p < 0.001). The scale of hospital biobanks was positively associated with the research competitiveness of Chinese hospitals.

Effect of Cognitive-Behavioral Therapy or Mindfulness Therapy on Pain and Quality of Life in Patients with Diabetic Neuropathy: A Systematic Review and Meta-Analysis

OBJECTIVES

This study aimed to evaluate the effectiveness of cognitive behavioral therapy (CBT) and mindfulness therapy (MT) for pain relief and quality of life (QOL) in patients with diabetic neuropathy.

REVIEW/ANALYSIS METHODS

Four databases were systematically searched from their respective inception dates to 29 June 2021. Relevant randomized controlled trials (RCTs) were screened and assessed for risk of bias. Eight RCTs evaluating CBT or MT were included. Statistical analysis was performed using Review Manager 5.4.

RESULTS

Eight RCTs involving 384 patients with painful diabetic neuropathy (PDN) tested psychological interventions, including three CBT and five MT studies. The results showed that patients' pain severity (standardized mean difference [SMD] = -0.60, 95% confidence interval [CI; -0.93 to -0.27], P = .0003) and QOL (SMD = -0.43, 95% CI [-0.83 to -0.04], p = .03) were improved immediately after treatment. Besides, the pain intensity (SMD = -0.67, 95% CI [-1.37 to 0.03], p = .06), pain interference (SMD = -0.75, 95% CI [-1.20 to -0.30], p = .001) and depressive symptoms (SMD = -0.62, 95% CI [-0.96 to -0.28], p = .0003) were superior to the control group after follow up. The subgroup analysis results of different intervention type showed that the CBT group could immediately improve pain (SMD = -0.44, 95% CI [-0.78 to -0.10], p = .01) after treatment. However, there was no statistically significant difference in the CBT group after follow-up (SMD = -0.15, 95% CI [-0.52 to 0.22], p = .42).

CONCLUSIONS

Cognitive behavioral therapy or MT is effective for treating pain in patients with diabetic peripheral neuropathy, improving the QOL, and reducing depressive symptoms. However, large-scale, multi-centre, rigorously designed RCTs are needed to further verify the long-term effects.

Interconnection between cardiovascular, renal and metabolic disorders: A narrative review with a focus on Japan

Insights from epidemiological, clinical and basic research are illuminating the interplay between metabolic disorders, cardiovascular disease (CVD) and kidney dysfunction, termed cardio-renal-metabolic (CRM) disease. Broadly defined, CRM disease involves multidirectional interactions between metabolic diseases such as type 2 diabetes (T2D), various types of CVD and chronic kidney disease (CKD). T2D confers increased risk for heart failure, which-although well known-has only recently come into focus for treatment, and may differ by ethnicity, whereas atherosclerotic heart disease is a well-established complication of T2D. Many people with T2D also have CKD, with a higher risk in Asians than their Western counterparts. Furthermore, CVD increases the risk of CKD and vice versa, with heart failure, notably, present in approximately half of CKD patients. Molecular mechanisms involved in CRM disease include hyperglycaemia, insulin resistance, hyperactivity of the renin-angiotensin-aldosterone system, production of advanced glycation end-products, oxidative stress, lipotoxicity, endoplasmic reticulum stress, calcium-handling abnormalities, mitochondrial malfunction and deficient energy production, and chronic inflammation. Pathophysiological manifestations of these processes include diabetic cardiomyopathy, vascular endothelial dysfunction, cardiac and renal fibrosis, glomerular hyperfiltration, renal hypoperfusion and venous congestion, reduced exercise tolerance leading to metabolic dysfunction, and calcification of atherosclerotic plaque. Importantly, recognition of the interaction between CRM diseases would enable a more holistic approach to CRM care, rather than isolated treatment of individual conditions, which may improve patient outcomes. Finally, aspects of CRM diseases may differ between Western and East Asian countries such as Japan, a super-ageing country, with potential differences in epidemiology, complications and prognosis that represent an important avenue for future research.

Germline Genetic and Treatment-Related Risk Factors for Diabetes Mellitus in Survivors of Childhood Cancer: A Report From the Childhood Cancer Survivor Study and St Jude Lifetime Cohorts

PURPOSE

To characterize germline genetic risk factors of diabetes mellitus among long-term survivors of childhood cancer.

METHODS

Adult survivors of childhood cancer from the Childhood Cancer Survivor Study (CCSS) Original Cohort (n = 5,083; 383 with diabetes) were used to conduct a discovery genome-wide association study. Replication was performed using the CCSS Expansion (n = 2,588; 40 with diabetes) and the St Jude Lifetime (SJLIFE; n = 3,351; 208 with diabetes) cohorts. Risk prediction models, stratified on exposure to abdominal radiation, were calculated using logistic regression including attained age, sex and body mass index, diagnosis, alkylating chemotherapy, age at cancer diagnosis, and a polygenic risk score (PRS) on the basis of 395 diabetes variants from the general population. Area under the receiver operating characteristic curve (AUC) was calculated for models on the basis of traditional risk factors, clinical risk factors, and PRS.

RESULTS

There was a genome-wide significant association of rs55849673-A with diabetes among survivors (odds ratio, 2.9; 95% CI, 2.0 to 4.2; P = 3.7 × 10^-8), which is related to expression of ERCC6L2 in the Genotype-Tissue Expression project. The association of rs55849673-A was observed largely among survivors not exposed to abdominal radiation (odds ratio = 3.5, P = 1.1 × 10^-7) and the frequency of rs55849673-A was consistently higher among diabetic survivors in the CCSS Expansion and SJLIFE cohorts. Risk prediction models including traditional diabetes risk factors, clinical risk factors and PRS had an optimism-corrected AUC of 0.801, with an AUC of 0.751 in survivors treated with abdominal radiation versus 0.813 in survivors who did not receive abdominal radiation.

CONCLUSION

There is evidence for a novel locus of diabetes among survivors not exposed to abdominal radiation. Further refinement and validation of clinic-based risk prediction models for diabetes among long-term survivors of childhood cancer is warranted.

Gene co-expression analyses of health(span) across multiple species

Health(span)-related gene clusters/modules were recently identified based on knowledge about the cross-species genetic basis of health, to interpret transcriptomic datasets describing health-related interventions. However, the cross-species comparison of health-related observations reveals a lot of heterogeneity, not least due to widely varying health(span) definitions and study designs, posing a challenge for the exploration of conserved healthspan modules and, specifically, their transfer across species. To improve the identification and exploration of conserved/transferable healthspan modules, here we apply an established workflow based on gene co-expression network analyses employing GEO/ArrayExpress data for human and animal models, and perform a comprehensive meta-study of the resulting modules related to health(span), yielding a small set of literature backed health(span) candidate genes. For each experiment, WGCNA (weighted gene correlation network analysis) was used to infer modules of genes which correlate in their expression with a 'health phenotype score' and to determine the most-connected (hub) genes (and their interactions) for each such module. After mapping these hub genes to their human orthologs, 12 health(span) genes were identified in at least two species (ACTN3, ANK1, MRPL18, MYL1, PAXIP1, PPP1CA, SCN3B, SDCBP, SKIV2L, TUBG1, TYROBP, WIPF1), for which enrichment analysis by g:profiler found an association with actin filament-based movement and associated organelles, as well as muscular structures. We conclude that a meta-study of hub genes from co-expression network analyses for the complex phenotype health(span), across multiple species, can yield molecular-mechanistic insights and can direct experimentalists to further investigate the contribution of individual genes and their interactions to health(span).

GPSM1 impairs metabolic homeostasis by controlling a pro-inflammatory pathway in macrophages

G-protein-signaling modulator 1 (GPSM1) exhibits strong genetic association with Type 2 diabetes (T2D) and Body Mass Index in population studies. However, how GPSM1 carries out such control and in which types of cells are poorly understood. Here, we demonstrate that myeloid GPSM1 promotes metabolic inflammation to accelerate T2D and obesity development. Mice with myeloid-specific GPSM1 ablation are protected against high fat diet-induced insulin resistance, glucose dysregulation, and liver steatosis via repression of adipose tissue pro-inflammatory states. Mechanistically, GPSM1 deficiency mainly promotes TNFAIP3 transcription via the Gα_i3/cAMP/PKA/CREB axis, thus inhibiting TLR4-induced NF-κB signaling in macrophages. In addition, we identify a small-molecule compound, AN-465/42243987, which suppresses the pro-inflammatory phenotype by inhibiting GPSM1 function, which could make it a candidate for metabolic therapy. Furthermore, GPSM1 expression is upregulated in visceral fat of individuals with obesity and is correlated with clinical metabolic traits. Overall, our findings identify macrophage GPSM1 as a link between metabolic inflammation and systemic homeostasis.

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.

Association of KCNJ11 and ABCC8 single-nucleotide polymorphisms with type 2 diabetes mellitus in a Kinh Vietnamese population

Type 2 diabetes mellitus (T2DM) is a genetically influenced disease, but few studies have been performed to investigate the genetic basis of T2DM in Vietnamese subjects. Thus, the potential associations of KCNJ11 and ABCC8 single nucleotide polymorphisms (SNPs) with T2DM were investigated in a Kinh Vietnamese population. A cross-sectional study consisting of 404 subjects including 202 T2DM cases and 202 non-T2DM controls was designed to examine the potential associations of 4 KCNJ11 and ABCC8 SNPs (rs5219, rs2285676, rs1799859, and rs757110) with T2DM. Genotypes were identified based on restriction fragment length polymorphism and tetra-primer amplification refractory mutation system polymerase chain reaction. After statistically adjusting for age, sex, and BMI, rs5219 was found to be associated with an increased risk of T2DM under 2 inheritance models: codominant (OR = 2.15, 95% confidence intervals [CI] = 1.09-4.22) and recessive (OR = 2.08, 95%CI = 1.09-3.94). On the other hand, rs2285676, rs1799859, and rs757110 were not associated with an increased risk of T2DM. Haplotype analysis elucidated a strong linkage disequilibrium between the 3 SNPs, rs5219, rs2285676, and rs757110. The haplotype rs5219(A)/rs2285676(T)/rs757110(G) was associated with an increased risk of T2DM (OR = 1.42, 95%CI = 1.01-1.99). The results show that rs5219 is a lead candidate SNP associated with an increased risk of developing T2DM in the Kinh Vietnamese population. Further functional characterization is needed to uncover the mechanism underlying the potential genotype-phenotype associations.

A novel splice-affecting HNF1A variant with large population impact on diabetes in Greenland

Background

The genetic disease architecture of Inuit includes a large number of common high-impact variants. Identification of such variants contributes to our understanding of the genetic aetiology of diseases and improves global equity in genomic personalised medicine. We aimed to identify and characterise novel variants in genes associated with Maturity Onset Diabetes of the Young (MODY) in the Greenlandic population.

Methods

Using combined data from Greenlandic population cohorts of 4497 individuals, including 448 whole genome sequenced individuals, we screened 14 known MODY genes for previously identified and novel variants. We functionally characterised an identified novel variant and assessed its association with diabetes prevalence and cardiometabolic traits and population impact.

Findings

We identified a novel variant in the known MODY gene HNF1A with an allele frequency of 1.9% in the Greenlandic Inuit and absent elsewhere. Functional assays indicate that it prevents normal splicing of the gene. The variant caused lower 30-min insulin (β = -232 pmol/L, β_SD = -0.695, P = 4.43 × 10^-4) and higher 30-min glucose (β = 1.20 mmol/L, β_SD = 0.441, P = 0.0271) during an oral glucose tolerance test. Furthermore, the variant was associated with type 2 diabetes (OR 4.35, P = 7.24 × 10^-6) and HbA1c (β = 0.113 HbA1c%, β_SD = 0.205, P = 7.84 × 10^-3). The variant explained 2.5% of diabetes variance in Greenland.

Interpretation

The reported variant has the largest population impact of any previously reported variant within a MODY gene. Together with the recessive TBC1D4 variant, we show that close to 1 in 5 cases of diabetes (18%) in Greenland are associated with high-impact genetic variants compared to 1-3% in large populations.

Funding

Novo Nordisk Foundation, Independent Research Fund Denmark, and Karen Elise Jensen's Foundation.

The contribution of common and rare genetic variants to variation in metabolic traits in 288,137 East Asians

Metabolic traits are heritable phenotypes widely-used in assessing the risk of various diseases. We conduct a genome-wide association analysis (GWAS) of nine metabolic traits (including glycemic, lipid, liver enzyme levels) in 125,872 Korean subjects genotyped with the Korea Biobank Array. Following meta-analysis with GWAS from Biobank Japan identify 144 novel signals (MAF ≥ 1%), of which 57.0% are replicated in UK Biobank. Additionally, we discover 66 rare (MAF < 1%) variants, 94.4% of them co-incident to common loci, adding to allelic series. Although rare variants have limited contribution to overall trait variance, these lead, in carriers, substantial loss of predictive accuracy from polygenic predictions of disease risk from common variant alone. We capture groups with up to 16-fold variation in type 2 diabetes (T2D) prevalence by integration of genetic risk scores of fasting plasma glucose and T2D and the I349F rare protective variant. This study highlights the need to consider the joint contribution of both common and rare variants on inherited risk of metabolic traits and related diseases.

Evidence that the pituitary gland connects type 2 diabetes mellitus and schizophrenia based on large-scale trans-ethnic genetic analyses

BACKGROUND

Previous studies on European (EUR) samples have obtained inconsistent results regarding the genetic correlation between type 2 diabetes mellitus (T2DM) and Schizophrenia (SCZ). A large-scale trans-ethnic genetic analysis may provide additional evidence with enhanced power.

OBJECTIVE

We aimed to explore the genetic basis for both T2DM and SCZ based on large-scale genetic analyses of genome-wide association study (GWAS) data from both East Asian (EAS) and EUR subjects.

METHODS

A range of complementary approaches were employed to cross-validate the genetic correlation between T2DM and SCZ at the whole genome, autosomes (linkage disequilibrium score regression, LDSC), loci (Heritability Estimation from Summary Statistics, HESS), and causal variants (MiXeR and Mendelian randomization, MR) levels. Then, genome-wide and transcriptome-wide cross-trait/ethnic meta-analyses were performed separately to explore the effective shared organs, cells and molecular pathways.

RESULTS

A weak genome-wide negative genetic correlation between SCZ and T2DM was found for the EUR (r_g = - 0.098, P = 0.009) and EAS (r_g =- 0.053 and P = 0.032) populations, which showed no significant difference between the EUR and EAS populations (P = 0.22). After Bonferroni correction, the r_g remained significant only in the EUR population. Similar results were obtained from analyses at the levels of autosomes, loci and causal variants. 25 independent variants were firstly identified as being responsible for both SCZ and T2DM. The variants associated with the two disorders were significantly correlated to the gene expression profiles in the brain (P = 1.1E-9) and pituitary gland (P = 1.9E-6). Then, 61 protein-coding and non-coding genes were identified as effective genes in the pituitary gland (P < 9.23E-6) and were enriched in metabolic pathways related to glutathione mediated arsenate detoxification and to D-myo-inositol-trisphosphate.

CONCLUSION

Here, we show that a negative genetic correlation exists between SCZ and T2DM at the whole genome, autosome, locus and causal variant levels. We identify pituitary gland as a common effective organ for both diseases, in which non-protein-coding effective genes, such as lncRNAs, may be responsible for the negative genetic correlation. This highlights the importance of molecular metabolism and neuroendocrine modulation in the pituitary gland, which may be responsible for the initiation of T2DM in SCZ patients.

Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes

To explore the complex genetic architecture of common diseases and traits, we conducted comprehensive PheWAS of ten diseases and 34 quantitative traits in the community-based Taiwan Biobank (TWB). We identified 995 significantly associated loci with 135 novel loci specific to Taiwanese population. Further analyses highlighted the genetic pleiotropy of loci related to complex disease and associated quantitative traits. Extensive analysis on glycaemic phenotypes (T2D, fasting glucose and HbA_1c) was performed and identified 115 significant loci with four novel genetic variants (HACL1, RAD21, ASH1L and GAK). Transcriptomics data also strengthen the relevancy of the findings to metabolic disorders, thus contributing to better understanding of pathogenesis. In addition, genetic risk scores are constructed and validated for absolute risks prediction of T2D in Taiwanese population. In conclusion, our data-driven approach without a priori hypothesis is useful for novel gene discovery and validation on top of disease risk prediction for unique non-European population.

Sex Differences in the Effects of CDKAL1 Variants on Glycemic Control in Diabetic Patients: Findings from the Korean Genome and Epidemiology Study

BACKGROUND

Using long-term data from the Korean Genome and Epidemiology Study, we defined poor glycemic control and investigated possible risk factors, including variants related to type 2 diabetes mellitus (T2DM). In addition, we evaluated interaction effects among risk factors for poor glycemic control.

METHODS

Among 436 subjects with newly diagnosed diabetes, poor glycemic control was defined based on glycosylated hemoglobin trajectory patterns by group-based trajectory modeling. For the variants related to T2DM, genetic risk scores (GRSs) were calculated and divided into quartiles. Risk factors for poor glycemic control were assessed using a logistic regression model.

RESULTS

Of the subjects, 43% were in the poor-glycemic-control group. Body mass index (BMI) and triglyceride (TG) were associated with poor glycemic control. The risk for poor glycemic control increased by 11.0% per 1 kg/m2 increase in BMI and by 3.0% per 10 mg/dL increase in TG. The risk for GRS with poor glycemic control was sex-dependent (Pinteraction=0.07), and a relationship by GRS quartiles was found in females but not in males. Moreover, the interaction effect was found to be significant on both additive and multiplicative scales. The interaction effect was evident in the variants of cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like (CDKAL1).

CONCLUSION

Females with risk alleles of variants in CDKAL1 associated with T2DM had a higher risk for poor glycemic control than males.

Vitamin D and heart failure: A two-sample mendelian randomization study

BACKGROUND AND AIMS

The relationship between vitamin D and heart failure (HF) has attracted significant interest, but the association between the two in previous studies remains uncertain. Therefore, we used two-sample Mendelian randomization (MR) to investigate a causal association between 25-hydroxyvitamin D (25OHD) and HF risk.

METHODS AND RESULTS

This study utilized summary statistics from the most extensive genome-wide association studies for 25OHD and HF. To make the results more reliable, we used several methods based on three assumptions for MR analysis. We also used the multivariable MR adjusting for hypertension, BMI, diabetes, chronic kidney disease to further elucidate the association between 25OHD and HF. Considering the potential pleiotropy, we performed an MR analysis with conditionally independent genetic instruments at core genes to further determine the relationship between vitamin D and heart failure. We found that per 1 SD increase in standardized log-transformed 25OHD level, the relative risk of HF decreased by 16.5% (OR: 0.835, 95% Cl: 0.743-0.938, P = 0.002), and other MR methods also showed consistent results. The multivariable MR also reported that per 1 SD increase in standardized log-transformed 25OHD level, the relative risk of HF decreased. And the scatter plots showed a trend towards an inverse MR association between 25OHD levels, instrumented by the core 25OHD genes, and HF.

CONCLUSION

In summary, we found a potential inverse association between elevated 25OHD levels and the risk of HF, which suggested that timely 25OHD supplementation or maintaining adequate 25OHD concentrations may be an essential measure for HF prevention in the general population.

Zmiz1 is required for mature β-cell function and mass expansion upon high fat feeding

OBJECTIVE

Identifying the transcripts which mediate genetic association signals for type 2 diabetes (T2D) is critical to understand disease mechanisms. Studies in pancreatic islets support the transcription factor ZMIZ1 as a transcript underlying a T2D GWAS signal, but how it influences T2D risk is unknown.

METHODS

β-Cell-specific Zmiz1 knockout (Zmiz1^βKO) mice were generated and phenotypically characterised. Glucose homeostasis was assessed in Zmiz1^βKO mice and their control littermates on chow diet (CD) and high fat diet (HFD). Islet morphology and function were examined by immunohistochemistry and in vitro islet function was assessed by dynamic insulin secretion assay. Transcript and protein expression were assessed by RNA sequencing and Western blotting. In islets isolated from genotyped human donors, we assessed glucose-dependent insulin secretion and islet insulin content by static incubation assay.

RESULTS

Male and female Zmiz1^βKO mice were glucose intolerant with impaired insulin secretion, compared with control littermates. Transcriptomic profiling of Zmiz1^βKO islets identified over 500 differentially expressed genes including those involved in β-cell function and maturity, which we confirmed at the protein level. Upon HFD, Zmiz1^βKO mice fail to expand β-cell mass and become severely diabetic. Human islets from carriers of the ZMIZ1-linked T2D-risk alleles have reduced islet insulin content and glucose-stimulated insulin secretion.

CONCLUSIONS

β-Cell Zmiz1 is required for normal glucose homeostasis. Genetic variation at the ZMIZ1 locus may influence T2D-risk by reducing islet mass expansion upon metabolic stress and the ability to maintain a mature β-cell state.

Identification of Putative Causal Relationships Between Type 2 Diabetes and Blood-Based Biomarkers in East Asians by Mendelian Randomization

Observational studies have revealed phenotypic associations between type 2 diabetes (T2D) and many biomarkers. However, causality between these conditions in East Asians is unclear. We leveraged genome-wide association study (GWAS) summary statistics on T2D (n = 77,418 cases; n = 356,122 controls) from the Asian Genetic Epidemiology Network (sample recruited during 2001-2011) and GWAS summary statistics on 42 biomarkers (n = 12,303-143,658) from BioBank Japan (sample recruited during 2003-2008) to investigate causal relationships between T2D and biomarkers. Applications of Mendelian randomization approaches consistently revealed genetically instrumented associations of T2D with increased serum potassium levels (liability-scale β = 0.04-0.10; P = 6.41 × 10-17-9.85 × 10-5) and decreased serum chloride levels (liability-scale β = -0.16 to -0.06; P = 5.22 × 10-27-3.14 × 10-5), whereas these 2 biomarkers showed no causal effects on T2D. Heritability Estimation Using Summary Statistics (ρ-HESS) and summary-data-based Mendelian randomization highlighted 27 genomic regions and 3 genes (α-1,3-mannosyl-glycoprotein 2-β-N-acetylglucosaminyltransferase (MGAT1), transducing-like enhancer (TLE) family member 1, transcriptional corepressor (TLE1), and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR)) that interactively associated with the shared genetics underlying T2D and the 2 biomarkers. Thus, T2D may causally affect serum potassium and chloride levels among East Asians. In contrast, the relationships of potassium and chloride with T2D are not causal, suggesting the importance of monitoring electrolyte disorders for T2D patients.

Phosphoproteomics of three exercise modalities identifies canonical signaling and C18ORF25 as an AMPK substrate regulating skeletal muscle function

Exercise induces signaling networks to improve muscle function and confer health benefits. To identify divergent and common signaling networks during and after different exercise modalities, we performed a phosphoproteomic analysis of human skeletal muscle from a cross-over intervention of endurance, sprint, and resistance exercise. This identified 5,486 phosphosites regulated during or after at least one type of exercise modality and only 420 core phosphosites common to all exercise. One of these core phosphosites was S67 on the uncharacterized protein C18ORF25, which we validated as an AMPK substrate. Mice lacking C18ORF25 have reduced skeletal muscle fiber size, exercise capacity, and muscle contractile function, and this was associated with reduced phosphorylation of contractile and Ca2+ handling proteins. Expression of C18ORF25 S66/67D phospho-mimetic reversed the decreased muscle force production. This work defines the divergent and canonical exercise phosphoproteome across different modalities and identifies C18ORF25 as a regulator of exercise signaling and muscle function.

Advances in multi-omics study of biomarkers of glycolipid metabolism disorder

Glycolipid metabolism disorder are major threats to human health and life. Genetic, environmental, psychological, cellular, and molecular factors contribute to their pathogenesis. Several studies demonstrated that neuroendocrine axis dysfunction, insulin resistance, oxidative stress, chronic inflammatory response, and gut microbiota dysbiosis are core pathological links associated with it. However, the underlying molecular mechanisms and therapeutic targets of glycolipid metabolism disorder remain to be elucidated. Progress in high-throughput technologies has helped clarify the pathophysiology of glycolipid metabolism disorder. In the present review, we explored the ways and means by which genomics, transcriptomics, proteomics, metabolomics, and gut microbiomics could help identify novel candidate biomarkers for the clinical management of glycolipid metabolism disorder. We also discuss the limitations and recommended future research directions of multi-omics studies on these diseases.

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.

How dysregulation of the immune system promotes diabetes mellitus and cardiovascular risk complications

Diabetes mellitus (DM) is a chronic metabolic disorder characterized by persistent hyperglycemia due to insulin resistance or failure to produce insulin. Patients with DM develop microvascular complications that include chronic kidney disease and retinopathy, and macrovascular complications that mainly consist in an accelerated and more severe atherosclerosis compared to the general population, increasing the risk of cardiovascular (CV) events, such as stroke or myocardial infarction by 2- to 4-fold. DM is commonly associated with a low-grade chronic inflammation that is a known causal factor in its development and its complications. Moreover, it is now well-established that inflammation and immune cells play a major role in both atherosclerosis genesis and progression, as well as in CV event occurrence. In this review, after a brief presentation of DM physiopathology and its macrovascular complications, we will describe the immune system dysregulation present in patients with type 1 or type 2 diabetes and discuss its role in DM cardiovascular complications development. More specifically, we will review the metabolic changes and aberrant activation that occur in the immune cells driving the chronic inflammation through cytokine and chemokine secretion, thus promoting atherosclerosis onset and progression in a DM context. Finally, we will discuss how genetics and recent systemic approaches bring new insights into the mechanisms behind these inflammatory dysregulations and pave the way toward precision medicine.

Detecting associated genes for complex traits shared across East Asian and European populations under the framework of composite null hypothesis testing

Background

Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking.

Methods

By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement.

Results

Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones.

Conclusion

Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03637-8.

Variants influencing age at diagnosis of HNF1A-MODY

BACKGROUND

HNF1A-MODY is a monogenic form of diabetes caused by variants in the HNF1A gene. Different HNF1A variants are associated with differences in age of disease onset, but other factors are postulated to influence this trait. Here, we searched for genetic variants influencing age of HNF1A-MODY onset.

METHODS

Blood samples from 843 HNF1A-MODY patients from Czech Republic, France, Poland, Slovakia, the UK and the US were collected. A validation set consisted of 121 patients from the US. We conducted a genome-wide association study in 843 HNF1A-MODY patients. Samples were genotyped using Illumina Human Core arrays. The core analysis was performed using the GENESIS package in R statistical software. Kinship coefficients were estimated with the KING and PC-Relate algorithms. In the linear mixed model, we accounted for year of birth, sex, and location of the HNF1A causative variant.

RESULTS

A suggestive association with age of disease onset was observed for rs2305198 (p = 2.09E-07) and rs7079157 (p = 3.96E-06) in the HK1 gene, rs2637248 in the LRMDA gene (p = 2.44E-05), and intergenic variant rs2825115 (p = 2.04E-05). Variant rs2637248 reached nominal significance (p = 0.019), while rs7079157 (p = 0.058) and rs2825115 (p = 0.068) showed suggestive association with age at diabetes onset in the validation set.

CONCLUSIONS

rs2637248 in the LRMDA gene is associated with age at diabetes onset in HNF1A-MODY patients.

L-carnitine, a friend or foe for cardiovascular disease? A Mendelian randomization study

BACKGROUND

L-carnitine is emerging as an item of interest for cardiovascular disease (CVD) prevention and treatment, but controversy exists. To examine the effectiveness and safety of L-carnitine, we assessed how genetically different levels of L-carnitine are associated with CVD risk and its risk factors. Given higher CVD incidence and L-carnitine in men, we also examined sex-specific associations.

METHODS

We used Mendelian randomization to obtain unconfounded estimates. Specifically, we used genetic variants to predict L-carnitine, and obtained their associations with coronary artery disease (CAD), ischemic stroke, heart failure, and atrial fibrillation, as well as CVD risk factors (type 2 diabetes, glucose, HbA1c, insulin, lipid profile, blood pressure and body mass index) in large consortia and established cohorts, as well as sex-specific association in the UK Biobank. We obtained the Wald estimates (genetic association with CVD and its risk factors divided by the genetic association with L-carnitine) and combined them using inverse variance weighting. In sensitivity analysis, we used different analysis methods robust to pleiotropy and replicated using an L-carnitine isoform, acetyl-carnitine.

RESULTS

Genetically predicted L-carnitine was nominally associated with higher risk of CAD overall (OR 1.07 per standard deviation (SD) increase in L-carnitine, 95% CI 1.02 to 1.11) and in men (OR 1.09, 95% CI 1.02 to 1.16) but had a null association in women (OR 1.00, 95% CI 0.92 to 1.09). These associations were also robust to different methods and evident for acetyl-carnitine.

CONCLUSIONS

Our findings do not support a beneficial association of L-carnitine with CVD and its risk factors but suggest potential harm. L-carnitine may also exert a sex-specific role in CAD. Consideration of the possible sex disparity and exploration of the underlying pathways would be worthwhile.

Lung- and liver-dominant phenotypes of Korean eight constitution medicine have different profiles of genotype associated with each organ function

Eight Constitution Medicine (ECM), a ramification of traditional Korean medicine, has categorized people into eight constitutions. The main criteria of classification are inherited differences or predominance in the functions of organs, such as the liver or lung, diagnosed through ECM-specific pulse patterns. This study investigated the association between single nucleotide polymorphism (SNP) genotypes and ECM phenotypes and explored candidate genetic makeups responsible for each constitution using a genome-wide association study (GWAS). Sixty-three healthy volunteers, who were either categorized as the Hepatonia (HEP, n = 32) or Pulmotonia (PUL, n = 31) constitution, were enrolled. HEP and PUL are two contrasting ECM types representing the dominant liver and lung phenotypes, respectively. SNPs were analyzed from the oral mucosa DNA using a commercially available microarray chip that can identify 820,000 SNPs. We conducted GWAS using logistic regression analysis and additive mode genotypes and constructed phylogenetic trees using the SNPhylo program with 8 SNPs specific for the liver phenotype and 15 SNPs for the lung phenotype. Although genome-wide significant SNPs were not found, the phylogenetic tree showed a clear difference between the two constitutions. This is the first observation suggesting genetic involvement in the ECM and can be extended to all ECM constitutions.

Genetic evidence for a causal relationship between type 2 diabetes and peripheral artery disease in both Europeans and East Asians

BACKGROUND

Observational studies have revealed that type 2 diabetes (T2D) is associated with an increased risk of peripheral artery disease (PAD). However, whether the two diseases share a genetic basis and whether the relationship is causal remain unclear. It is also unclear as to whether these relationships differ between ethnic groups.

METHODS

By leveraging large-scale genome-wide association study (GWAS) summary statistics of T2D (European-based: N_case = 21,926, N_control = 342,747; East Asian-based: N_case = 36,614, N_control = 155,150) and PAD (European-based: N_case = 5673, N_control = 359,551; East Asian-based: N_case = 3593, N_control = 208,860), we explored the genetic correlation and putative causal relationship between T2D and PAD in both Europeans and East Asians using linkage disequilibrium score regression and seven Mendelian randomization (MR) models. We also performed multi-trait analysis of GWAS and two gene-based analyses to reveal candidate variants and risk genes involved in the shared genetic basis between T2D and PAD.

RESULTS

We observed a strong genetic correlation (r_g) between T2D and PAD in both Europeans (r_g = 0.51; p-value = 9.34 × 10^-15) and East Asians (r_g = 0.46; p-value = 1.67 × 10^-12). The MR analyses provided consistent evidence for a causal effect of T2D on PAD in both ethnicities (odds ratio [OR] = 1.05 to 1.28 for Europeans and 1.15 to 1.27 for East Asians) but not PAD on T2D. This putative causal effect was not influenced by total cholesterol, body mass index, systolic blood pressure, or smoking initiation according to multivariable MR analysis, and the genetic overlap between T2D and PAD was further explored employing an independent European sample through polygenic risk score regression. Multi-trait analysis of GWAS revealed two novel European-specific single nucleotide polymorphisms (rs927742 and rs1734409) associated with the shared genetic basis of T2D and PAD. Gene-based analyses consistently identified one gene ANKFY1 and gene-gene interactions (e.g., STARD10 [European-specific] to AP3S2 [East Asian-specific]; KCNJ11 [European-specific] to KCNQ1 [East Asian-specific]) associated with the trans-ethnic genetic overlap between T2D and PAD, reflecting a common genetic basis for the co-occurrence of T2D and PAD in both Europeans and East Asians.

CONCLUSIONS

Our study provides the first evidence for a genetically causal effect of T2D on PAD in both Europeans and East Asians. Several candidate variants and risk genes were identified as being associated with this genetic overlap. Our findings emphasize the importance of monitoring PAD status in T2D patients and suggest new genetic biomarkers for screening PAD risk among patients with T2D.

In silico functional and pathway analysis of risk genes and SNPs for type 2 diabetes in Asian population

Type 2 diabetes (T2D) has earned widespread recognition as a primary cause of death, disability, and increasing healthcare costs. There is compelling evidence that hereditary factors contribute to the development of T2D. Clinical trials in T2D have mostly focused on genes and single nucleotide polymorphisms (SNPs) in protein-coding areas. Recently, it was revealed that SNPs located in noncoding areas also play a significant impact on disease vulnerability. It is required for cell type-specific gene expression. However, the precise mechanism by which T2D risk genes and SNPs work remains unknown. We integrated risk genes and SNPs from genome-wide association studies (GWASs) and performed comprehensive bioinformatics analyses to further investigate the functional significance of these genes and SNPs. We identified four intriguing transcription factors (TFs) associated with T2D. The analysis revealed that the SNPs are engaged in chromatin interaction regulation and/or may have an effect on TF binding affinity. The Gene Ontology (GO) study revealed high enrichment in a number of well-characterized signaling pathways and regulatory processes, including the STAT3 and JAK signaling pathways, which are both involved in T2D metabolism. Additionally, a detailed KEGG pathway analysis identified two major T2D genes and their prospective therapeutic targets. Our findings underscored the potential functional significance of T2D risk genes and SNPs, which may provide unique insights into the disease’s pathophysiology.

Nutrigenetic Interaction of Spontaneously Hypertensive Rat Chromosome 20 Segment and High-Sucrose Diet Sensitizes to Metabolic Syndrome

Several corresponding regions of human and mammalian genomes have been shown to affect sensitivity to the manifestation of metabolic syndrome via nutrigenetic interactions. In this study, we assessed the effect of sucrose administration in a newly established congenic strain BN.SHR20, in which a limited segment of rat chromosome 20 from a metabolic syndrome model, spontaneously hypertensive rat (SHR), was introgressed into Brown Norway (BN) genomic background. We mapped the extent of the differential segment and compared the genomic sequences of BN vs. SHR within the segment in silico. The differential segment of SHR origin in BN.SHR20 spans about 9 Mb of the telomeric portion of the short arm of chromosome 20. We identified non-synonymous mutations e.g., in ApoM, Notch4, Slc39a7, Smim29 genes and other variations in or near genes associated with metabolic syndrome in human genome-wide association studies. Male rats of BN and BN.SHR20 strains were fed a standard diet for 18 weeks (control groups) or 16 weeks of standard diet followed by 14 days of high-sucrose diet (HSD). We assessed the morphometric and metabolic profiles of all groups. Adiposity significantly increased only in BN.SHR20 after HSD. Fasting glycemia and the glucose levels during the oral glucose tolerance test were higher in BN.SHR20 than in BN groups, while insulin levels were comparable. The fasting levels of triacylglycerols were the highest in sucrose-fed BN.SHR20, both compared to the sucrose-fed BN and the control BN.SHR20. The non-esterified fatty acids and total cholesterol concentrations were higher in BN.SHR20 compared to their respective BN groups, and the HSD elicited an increase in non-esterified fatty acids only in BN.SHR20. In a new genetically defined model, we have isolated a limited genomic region involved in nutrigenetic sensitization to sucrose-induced metabolic disturbances.

Association of GLP1R Polymorphisms With the Incretin Response

CONTEXT

Polymorphisms in the gene encoding the glucagon-like peptide-1 receptor (GLP1R) are associated with type 2 diabetes but their effects on incretin levels remain unclear.

OBJECTIVE

We evaluated the physiologic and hormonal effects of GLP1R genotypes before and after interventions that influence glucose physiology.

DESIGN

Pharmacogenetic study conducted at 3 academic centers in Boston, Massachusetts.

PARTICIPANTS

A total of 868 antidiabetic drug-naïve participants with type 2 diabetes or at risk for developing diabetes.

INTERVENTIONS

We analyzed 5 variants within GLP1R (rs761387, rs10305423, rs10305441, rs742762, and rs10305492) and recorded biochemical data during a 5-mg glipizide challenge and a 75-g oral glucose tolerance test (OGTT) following 4 doses of metformin 500 mg over 2 days.

MAIN OUTCOMES

We used an additive mixed-effects model to evaluate the association of these variants with glucose, insulin, and incretin levels over multiple timepoints during the OGTT.

RESULTS

During the OGTT, the G-risk allele at rs761387 was associated with higher total GLP-1 (2.61 pmol/L; 95% CI, 1.0.72-4.50), active GLP-1 (2.61 pmol/L; 95% CI, 0.04-5.18), and a trend toward higher glucose (3.63; 95% CI, -0.16 to 7.42 mg/dL) per allele but was not associated with insulin. During the glipizide challenge, the G allele was associated with higher insulin levels per allele (2.01 IU/mL; 95% CI, 0.26-3.76). The other variants were not associated with any of the outcomes tested.

CONCLUSIONS

GLP1R variation is associated with differences in GLP-1 levels following an OGTT load despite no differences in insulin levels, highlighting altered incretin signaling as a potential mechanism by which GLP1R variation affects T2D risk.

Association of Polygenic Variants with Type 2 Diabetes Risk and Their Interaction with Lifestyles in Asians

Over the last several decades, there has been a considerable growth in type 2 diabetes (T2DM) in Asians. A pathophysiological mechanism in Asian T2DM is closely linked to low insulin secretion, β-cell mass, and inability to compensate for insulin resistance. We hypothesized that genetic variants associated with lower β-cell mass and function and their combination with unhealthy lifestyle factors significantly raise T2DM risk among Asians. This hypothesis was explored with participants aged over 40. Participants were categorized into T2DM (case; n = 5383) and control (n = 53,318) groups. The genetic variants associated with a higher risk of T2DM were selected from a genome-wide association study in a city hospital-based cohort, and they were confirmed with a replicate study in Ansan/Ansung plus rural cohorts. The interacted genetic variants were identified with generalized multifactor dimensionality reduction analysis, and the polygenic risk score (PRS)-nutrient interactions were examined. The 8-SNP model was positively associated with T2DM risk by about 10 times, exhibiting a higher association than the 20-SNP model, including all T2DM-linked SNPs with p < 5 × 10−6. The SNPs in the models were primarily involved in pancreatic β-cell growth and survival. The PRS of the 8-SNP model interacted with three lifestyle factors: energy intake based on the estimated energy requirement (EER), Western-style diet (WSD), and smoking status. Fasting serum glucose concentrations were much higher in the participants with High-PRS in rather low EER intake and high-WSD compared to the High-EER and Low-WSD, respectively. They were shown to be higher in the participants with High-PRS in smokers than in non-smokers. In conclusion, the genetic impact of T2DM risk was mainly involved with regulating pancreatic β-cell mass and function, and the PRS interacted with lifestyles. These results highlight the interaction between genetic impacts and lifestyles in precision nutrition.

A minority of somatically mutated genes in pre-existing fatty liver disease have prognostic importance in the development of NAFLD

BACKGROUND

Understanding the genetics of liver disease has the potential to facilitate clinical risk stratification. We recently identified acquired somatic mutations in six genes and one lncRNA in pre-existing fatty liver disease. We hypothesised that germline variation in these genes might be associated with the risk of developing steatosis and contribute to the prediction of disease severity.

METHODS

Genome-wide association study (GWAS) summary statistics were extracted from seven studies (>1.7 million participants) for variants near ACVR2A, ALB, CIDEB, FOXO1, GPAM, NEAT1 and TNRC6B for: aminotransferases, liver fat, HbA1c, diagnosis of NAFLD, ARLD and cirrhosis. Findings were replicated using GWAS data from multiple independent cohorts. A phenome-wide association study was performed to examine for related metabolic traits, using both common and rare variants, including gene-burden testing.

RESULTS

There was no evidence of association between rare germline variants or SNPs near five genes (ACVR2A, ALB, CIDEB, FOXO1 and TNRC6B) and risk or severity of liver disease. Variants in GPAM (proxies for p.Ile43Val) were associated with liver fat (p = 3.6 × 10-13 ), ALT (p = 2.8 × 10-39 ) and serum lipid concentrations. Variants in NEAT1 demonstrated borderline significant associations with ALT (p = 1.9 × 10-11 ) and HbA1c, but not with liver fat, as well as influencing waist-to-hip ratio, adjusted for BMI.

CONCLUSIONS

Despite the acquisition of somatic mutations at these loci during progressive fatty liver disease, we did not find associations between germline variation and markers of liver disease, except in GPAM. In the future, larger sample sizes may identify associations. Currently, germline polygenic risk scores will not capture data from genes affected by somatic mutations.

Effects of polygenic risk score of type 2 diabetes on the hippocampal topological property and episodic memory

Type 2 diabetes is associated with a higher risk of dementia. The pathogenesis is complex and partly influenced by genetic factors. The hippocampus is the most vulnerable brain region in individuals with type 2 diabetes. However, whether the genetic risk of type 2 diabetes is associated with the hippocampus and episodic memory remains unclear. This study explored the influence of polygenic risk score (PRS) of type 2 diabetes on the white matter topological properties of the hippocampus among individuals with and without type 2 diabetes and its associations with episodic memory. This study included 103 individuals with type 2 diabetes and 114 well-matched individuals without type 2 diabetes. All the participants were genotyped, and a diffusion tensor imaging-based structural network was constructed. PRS was calculated based on a genome-wide association study of type 2 diabetes. The PRS-by-disease interactions on the bilateral hippocampal topological network properties were evaluated by analysis of covariance (ANCOVA). There were significant PRS-by-disease interaction effects on the nodal topological properties of the right hippocampus node. In the individuals with type 2 diabetes, the PRS was correlated with the right hippocampal nodal properties, and the nodal properties were correlated with the episodic memory. In addition, the right hippocampal nodal properties mediated the effect of PRS on episodic memory in individuals with type 2 diabetes. Our results suggested a gene-brain-cognition biological pathway, which might help understand the neural mechanism of the genetic risk of type 2 diabetes affects episodic memory in type 2 diabetes.

A variation in SORBS1 is associated with type 2 diabetes and high-density lipoprotein cholesterol in Chinese population

AIM

Sorbin and SH3-domain-containing-1 (SORBS1) play important roles in insulin signalling and cytoskeleton regulation. Variants of the SORBS1 gene have been inconsistently reported to be associated with type 2 diabetes or diabetic kidney disease (DKD).

METHODS

Two independent case-control studies based on two randomized sampling cohorts (cohort 1, n = 3345; cohort 2, n = 2282) were used to confirm the association between rs2281939 of SORBS1 and impaired glucose regulation (IGR). An additional hospital-based cohort (cohort 3, n = 2135) and cohort 1 were used to investigate the association between rs2281939 and DKD. The phenotype of rare variants of SORBS1 was explored in 453 patients with early onset type 2 diabetes (diagnosed before 40 years of age, EOD).

RESULTS

The G allele was associated with type 2 diabetes (additive model: OR = 1.25, 95% CI [1.03-1.52], p = 0.022) in cohort 1, and IGR in cohort 2 (additive model: OR = 1.22, 95% CI [1.05-1.43], p = 0.01). We found that the G allele was also associated with HDL-c levels in women in both cohort 1 (p = 0.03) and 2 (p = 0.029) in the dominant model. The rare variant carriers also had lower HDL-c and LDL-c levels than non-carriers in patients with EOD. No association between rs2281939 or rare variants and DKD was observed.

CONCLUSIONS

The variants in the SORBS1 gene were associated with IGR and HDL-c levels but not with DKD in the Chinese Han population.

Metabolism-secretion coupling in glucose-stimulated insulin secretion

Pancreatic β-cells in the islets of Langerhans secrete insulin in response to blood glucose levels. Precise control of the amount of insulin secreted is of critical importance for maintaining systemic carbohydrate homeostasis. It is now well established that glucose induced production of ATP from ADP and the K_ATP channel closure elevate cytosolic Ca²⁺, triggering insulin exocytosis in β-cells. However, for full activation of insulin secretion by glucose, other mechanisms besides Ca²⁺ elevation are needed. These mechanisms are the targets of current research and include intracellular metabolic pathways branching from glycolysis. They are metabolic pathways originating from the TCA cycle intermediates, the glycerolipid/free fatty acid cycle and the pentose phosphate pathway. Signaling effects of these pathways including degradation (removal) of protein SUMOylation, modulation of insulin vesicular energetics, and lipid modulation of exocytotic machinery may converge to fulfill insulin secretion, though the precise mechanisms have yet to be elucidated. This mini-review summarize recent advances in research on metabolic coupling mechanisms functioning in insulin secretion.

Pathophysiology, phenotypes and management of type 2 diabetes mellitus in Indian and Chinese populations

Nearly half of all adults with type 2 diabetes mellitus (T2DM) live in India and China. These populations have an underlying predisposition to deficient insulin secretion, which has a key role in the pathogenesis of T2DM. Indian and Chinese people might be more susceptible to hepatic or skeletal muscle insulin resistance, respectively, than other populations, resulting in specific forms of insulin deficiency. Cluster-based phenotypic analyses demonstrate a higher frequency of severe insulin-deficient diabetes mellitus and younger ages at diagnosis, lower β-cell function, lower insulin resistance and lower BMI among Indian and Chinese people compared with European people. Individuals diagnosed earliest in life have the most aggressive course of disease and the highest risk of complications. These characteristics might contribute to distinctive responses to glucose-lowering medications. Incretin-based agents are particularly effective for lowering glucose levels in these populations; they enhance incretin-augmented insulin secretion and suppress glucagon secretion. Sodium-glucose cotransporter 2 inhibitors might also lower blood levels of glucose especially effectively among Asian people, while α-glucosidase inhibitors are better tolerated in east Asian populations versus other populations. Further research is needed to better characterize and address the pathophysiology and phenotypes of T2DM in Indian and Chinese populations, and to further develop individualized treatment strategies.

Genetics and Epigenetics in Personalized Nutrition: Evidence, Expectations and Experiences

With the presentation of the blueprint of the first human genome in 2001 and the advent of technologies for high-throughput genetic analysis, personalized nutrition (PN) became a new scientific field and the first commercial offerings of genotype-based nutrition advice emerged at the same time. Here, we summarize the state of evidence for the effect of genetic and epigenetic factors in the development of obesity, the metabolic syndrome and resulting illnesses such as non-insulin-dependent diabetes mellitus and cardiovascular diseases. We also critically value the concepts of PN that were built around the new genetic avenue from both the academic and a commercial perspective and their effectiveness in causing sustained changes in diet, lifestyle and for improving health. Despite almost 20 years of research and commercial direct-to-consumer offerings, evidence for the success of gene-based dietary recommendations is still generally lacking. This calls for new concepts of future PN solutions that incorporate more phenotypic measures and provide a panel of instruments (e.g., self- and bio-monitoring tools, feedback systems, algorithms based on artificial intelligence) that increases compliance based on the individual´s physical and social environment and value system. This article is protected by copyright. All rights reserved.

Ethnic disparities attributed to the manifestation in and response to type 2 diabetes: insights from metabolomics

Type 2 diabetes (T2D) associated health disparities among different ethnicities have long been known. Ethnic variations also exist in T2D related comorbidities including insulin resistance, vascular complications and drug response. Genetic heterogeneity, dietary patterns, nutrient metabolism and gut microbiome composition attribute to ethnic disparities in both manifestation and progression of T2D. These factors differentially regulate the rate of metabolism and metabolic health. Metabolomics studies have indicated significant differences in carbohydrate, lipid and amino acid metabolism among ethnicities. Interestingly, genetic variations regulating lipid and amino acid metabolism might also contribute to inter-ethnic differences in T2D. Comprehensive and comparative metabolomics analysis between ethnicities might help to design personalized dietary regimen and newer therapeutic strategies. In the present review, we explore population based metabolomics data to identify inter-ethnic differences in metabolites and discuss how (a) genetic variations, (b) dietary patterns and (c) microbiome composition may attribute for such differences in T2D.

Association between serum manganese levels and diabetes in chinese adults with hypertension

Manganese (Mn) is an essential trace metal element that is associated with diabetes; however, the results of previous studies are inconsistent. Furthermore, few studies have been conducted in a hypertensive population. The purpose of this study is to explore the relationship between manganese and diabetes in a population with hypertension. A cross‐sectional study was conducted, including 2575 hypertensive individuals from 14 provinces in China. Serum manganese concentrations were measured by the inductively coupled plasma mass spectrometry (ICP‐MS) method. And logistic regression models were used to analyze the association between serum manganese and the risk of diabetes. The prevalence of diabetes was 27.0% in this hypertensive population. In logistic regression models, the odds ratios (95% confidence interval) for diabetes in tertile subgroups were 1.40 (1.12, 1.76) and 1.32 (1.05, 1.65) for tertiles 1 and tertiles 3, respectively, compared to tertile 2 (reference). Additionally, an interaction between sex and manganese was observed. The odds ratios (95% confidence interval) for diabetes were 1.29 (0.95, 1.75) and 0.96 (0.70, 1.31) for tertiles 1 and tertiles 3 among males, and 1.44 (1.01, 2.04) and 1.81 (1.29, 2.55) for tertiles 1 and tertiles 3 among females, respectively, compared to tertile 2. In conclusion, a U‐shaped association between serum manganese and diabetes was observed in a Chinese population with hypertension, and the association was modified by sex.

Shared genetic architectures of subjective well-being in East Asian and European ancestry populations

Subjective well-being (SWB) has been explored in European ancestral populations; however, whether the SWB genetic architecture is shared across populations remains unclear. We conducted a cross-population genome-wide association study for SWB using samples from Korean (n = 110,919) and European (n = 563,176) ancestries. Five ancestry-specific loci and twelve cross-ancestry significant genomic loci were identified. One novel locus (rs12298541 near HMGA2) associated with SWB was also identified through the European meta-analysis. Significant cross-ancestry genetic correlation for SWB between samples was observed. Polygenic risk analysis in an independent Korean cohort (n = 22,455) demonstrated transferability between populations. Significant correlations between SWB and major depressive disorder, and significant enrichment of central nervous system-related polymorphisms heritability in both ancestry populations were found. Hence, large-scale cross-ancestry genome-wide association studies can advance our understanding of SWB genetic architecture and mental health.

Type 2 Diabetes, Fasting Glucose, Hemoglobin A1c Levels and Risk of Primary Open-Angle Glaucoma: A Mendelian Randomization Study

Purpose

To evaluate the potential causal associations between type 2 diabetes and fasting glucose and HbA1c levels and the risk of primary open-angle glaucoma (POAG) in European and East Asian populations.

Methods

We selected genetic variants (P < 5 × 10⁻⁸) for type 2 diabetes (898,130 Europeans; 433,540 East Asians), fasting glucose, and HbA1c (196,991 Europeans; 36,584 East Asians) from three meta-analyses of genome-wide association studies (GWAS). The GWAS for POAG provided summary statistics (192,702 Europeans; 46,523 East Asians). Mendelian randomization (MR) analysis was accomplished using the inverse variance–weighted method, weighted-median method, MR Egger method, and MR-Pleiotropy RESidual Sum and Outlier test.

Results

Genetically predicted type 2 diabetes was potentially positively associated with POAG in the European ancestry (body mass index [BMI]–unadjusted: odds ratio [OR] = 1.07, 95% confidence interval [CI], 1.01–1.14, P = 0.028; BMI-adjusted: OR = 1.07, 95% CI, 1.01–1.15, P = 0.035), but not in the East Asian ancestry (BMI-unadjusted: OR = 1.01, 95% CI, 0.95–1.06, P = 0.866; BMI-adjusted: OR = 1.00, 95% CI, 0.94–1.05, P = 0.882). There was no evidence to support a causal association of fasting glucose (European: OR = 1.19, P = 0.157; East Asian: OR = 0.94, P = 0.715) and HbA1c (European: OR = 1.27, P = 0.178; East Asian: OR = 0.85, P = 0.508) levels with POAG.

Conclusions

The causal effect of type 2 diabetes on the risk of POAG is different in European and East Asian populations. The point estimates of fasting glucose and Hb1Ac with POAG are large but not statistically significant, which prompts the question of statistical power.

Genetics of Type 2 Diabetes: Implications from Large-Scale Studies

PURPOSE OF REVIEW

Type 2 diabetes (T2D) is a multifactorial, heritable syndrome characterized by dysregulated glucose homeostasis that results from impaired insulin secretion and insulin resistance. Genetic association studies have successfully identified hundreds of T2D risk loci implicating many genes in disease pathogenesis. In this review, we provide an overview of the recent T2D genetic studies from the past 3 years with particular focus on the effects of sample size and ancestral diversity on genetic discovery as well as discuss recent work on the use and limitations of genetic risk scores (GRS) for T2D risk prediction.

RECENT FINDINGS

Recent large-scale, multi-ancestry genetic studies of T2D have identified over 500 novel risk loci. The genetic variants (i.e., single nucleotide polymorphisms (SNPs)) marking these novel loci in general have smaller effect sizes than previously discovered loci. Inclusion of samples from diverse ancestral backgrounds shows a few ancestry specific loci marked by common variants, but overall, the majority of loci discovered are common across ancestries. Inclusion of common variant GRS, even with hundreds of loci, does not substantially increase T2D risk prediction over standard clinical risk factors such as age and family history. Common variant association studies of T2D have now identified over 700 T2D risk loci, half of which have been discovered in the past 3 years. These recent studies demonstrate that inclusion of ancestrally diverse samples can enhance locus discovery and improve accuracy of GRS for T2D risk prediction. GRS based on common variants, however, only minimally enhances risk prediction over standard clinical risk factors.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Familial aggregation and shared genetic loading for major psychiatric disorders and type 2 diabetes

AIMS/HYPOTHESIS

Psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BPD), are highly comorbid with type 2 diabetes. However, the mechanisms underlying such comorbidity are understudied. This study explored the familial aggregation of common psychiatric disorders and type 2 diabetes by testing family history association, and investigated the shared genetic loading between them by testing the polygenic risk score (PRS) association.

METHODS

A total of 105,184 participants were recruited from the Taiwan Biobank, and genome-wide genotyping data were available for 95,238 participants. The Psychiatric Genomics Consortium-derived PRS for SCZ, MDD and BPD was calculated. Logistic regression was used to estimate the OR with CIs between a family history of SCZ/MDD/BPD and a family history of type 2 diabetes, and between the PRS and the risk of type 2 diabetes.

RESULTS

A family history of type 2 diabetes was associated with a family history of SCZ (OR 1.23, 95% CI 1.08, 1.40), MDD (OR 1.19, 95% CI 1.13, 1.26) and BPD (OR 1.26, 95% CI 1.15, 1.39). Compared with paternal type 2 diabetes, maternal type 2 diabetes was associated with a higher risk of a family history of SCZ. SCZ PRS was negatively associated with type 2 diabetes in women (OR 0.92, 95% CI 0.88, 0.97), but not in men; the effect of SCZ PRS reduced after adjusting for BMI. MDD PRS was positively associated with type 2 diabetes (OR 1.04, 95% CI 1.00, 1.07); the effect of MDD PRS reduced after adjusting for BMI or smoking. BPD PRS was not associated with type 2 diabetes.

CONCLUSIONS/INTERPRETATION

The comorbidity of type 2 diabetes with psychiatric disorders may be explained by shared familial factors. The shared polygenic loading between MDD and type 2 diabetes implies not only pleiotropy but also a shared genetic aetiology for the mechanism behind the comorbidity. The negative correlation between polygenic loading for SCZ and type 2 diabetes implies the role of environmental factors.

Generation of Isogenic hiPSCs with Targeted Edits at Multiple Intronic SNPs to Study the Effects of the Type 2 Diabetes Associated KCNQ1 Locus in American Indians

The top genetic association signal for type 2 diabetes (T2D) in Southwestern American Indians maps to intron 15 of KCNQ1, an imprinted gene. We aim to understand the biology whereby variation at this locus affects T2D specifically in this genomic background. To do so, we obtained human induced pluripotent stem cells (hiPSC) derived from American Indians. Using these iPSCs, we show that imprinting of KCNQ1 and CDKN1C during pancreatic islet-like cell generation from iPSCs is consistent with known imprinting patterns in fetal pancreas and adult islets and therefore is an ideal model system to study this locus. In this report, we detail the use of allele-specific guide RNAs and CRISPR to generate isogenic hiPSCs that differ only at multiple T2D associated intronic SNPs at this locus which can be used to elucidate their functional effects. Characterization of these isogenic hiPSCs identified a few aberrant cell lines; namely cell lines with large hemizygous deletions in the putative functional region of KCNQ1 and cell lines hypomethylated at the KCNQ1OT1 promoter. Comparison of an isogenic cell line with a hemizygous deletion to the parental cell line identified CDKN1C and H19 as differentially expressed during the endocrine progenitor stage of pancreatic-islet development.

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.