Type 2 diabetes risk alleles demonstrate extreme directional differentiation among human populations, compared to other diseases

TCF7L2 and FTO Polymorphisms Are Associated with Type 2 Diabetes Mellitus Risk in Kuwait

OBJECTIVE

Despite the high prevalence of type 2 diabetes mellitus (T2DM) and obesity in the region, reports are limited on genetic risk factors associated with T2DM risk in Kuwait. Our aim was to investigate the association of reported FTO and TCF7L2 T2DM genetic risk variants in Kuwaiti T2DM patients.

SUBJECTS AND METHODS

FTO rs9939609 and TCF7L2 rs7903146 variants were genotyped in 203 T2DM patients and 162 healthy controls. Data analysis included Fisher's exact test, χ2 test, and linear and logistic regression analyses.

RESULTS

FTO rs9939609 (AA) and TCF7L2 rs7903146 (TT) genotypes associated with T2DM risk among Kuwaitis (p = 0.0016 and p < 0.0001; respectively). Both variants had the strongest association with T2DM risk in an autosomal recessive inheritance model (FTO rs9939609A: odds ratio (OR) 2.136, 95% confidence interval (CI): 1.21-3.67, p = 0.0075; TCF7L2 rs7903146T: OR 3.283, 95% CI: 1.92-5.76, p < 0.0001). Moreover, rs7903146T associated with risk of peripheral neuropathy (β = 0.735, 95% CI: 0.514-0.96, p < 0.001) and risk of myocardial infarction (β = 0.36, 95% CI: 0.024-0.7, p = 0.036) in T2DM patients.

CONCLUSION

The increased susceptibility of Kuwaitis to T2DM is influenced by the same common genetic factors found in other T2DM populations. Further investigations of other T2DM genetic risk factors in Kuwait should refine and further support the clinical utility of a genetic risk score in predicting T2DM risk in a high-risk population such as Kuwait.

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.

Epidemiology of Type 2 Diabetes in Indigenous Communities in the United States

PURPOSE OF REVIEW

The present review focuses on the epidemiology of type 2 diabetes (T2D) in Indigenous communities in the continental United States (U.S.)-including disease prevention and management-and discusses special considerations in conducting research with Indigenous communities.

RECENT FINDINGS

Previous studies have reported the disparately high prevalence of diabetes, especially T2D, among Indigenous peoples in the U.S. The high prevalence and incidence of early-onset T2D in Indigenous youth relative to that of all youth in the U.S. population pose challenges to the prevention of complications of diabetes. Behavioral, dietary, lifestyle, and genetic factors associated with T2D in Indigenous communities are often investigated. More limited is the discussion of the historical and ongoing consequences of colonization and displacement that impact the aforementioned risk factors. Future research is necessary to assess community-specific needs with respect to diabetes prevention and management across the diversity of Indigenous communities in the U.S.

Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People

The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.

Evolutionary forces in diabetes and hypertension pathogenesis in Africans

Rates of type 2 diabetes (T2D) and hypertension are increasing rapidly in urbanizing sub-Saharan Africa (SSA). While lifestyle factors drive the increases in T2D and hypertension prevalence, evidence across populations shows that genetic variation, which is driven by evolutionary forces including a natural selection that shaped the human genome, also plays a role. Here we report the evidence for the effect of selection in African genomes on mechanisms underlying T2D and hypertension, including energy metabolism, adipose tissue biology, insulin action and salt retention. Selection effects found for variants in genes PPARA and TCF7L2 may have enabled Africans to respond to nutritional challenges by altering carbohydrate and lipid metabolism. Likewise, African-ancestry-specific characteristics of adipose tissue biology (low visceral adipose tissue [VAT], high intermuscular adipose tissue and a strong association between VAT and adiponectin) may have been selected for in response to nutritional and infectious disease challenges in the African environment. Evidence for selection effects on insulin action, including insulin resistance and secretion, has been found for several genes including MPHOSPH9, TMEM127, ZRANB3 and MC3R. These effects may have been historically adaptive in critical conditions, such as famine and inflammation. A strong correlation between hypertension susceptibility variants and latitude supports the hypothesis of selection for salt retention mechanisms in warm, humid climates. Nevertheless, adaptive genomics studies in African populations are scarce. More work is needed, particularly genomics studies covering the wide diversity of African populations in SSA and Africans in diaspora, as well as further functional assessment of established risk loci.

Analysis of Evolution and Ethnic Diversity at Glucose-Associated SNPs of Circadian Clock-Related Loci with Cryptochrome 1, Cryptochrome 2, and Melatonin receptor 1B

Diabetes shows high heritability and, worldwide, causes significant health problems including cardiovascular disease and stroke. There is significant variation in the frequency of diabetes between different populations. Both Cryptochromes and Melatonin have a major role to regulate the circadian clock. Circadian clock failure causes metabolic dysfunctions including diabetes and obesity. Variations in the Cryptochrome 1, the Cryptochrome 2, and the Melatonin receptor 1B (MTNR1B) genes show associations with fasting glucose, and are also related to circadian clock. Here, we analyzed evidence for genetic selection and ethnic diversity at circadian clock- and glucose-related gene loci associated with Cryptochrome 1, Cryptochrome 2, and MTNR1B. We carried out a 3-step genetic method to investigate genetic selection at the Cryptochrome 1, Cryptochrome 2, and MTNR1B on four populations from the 1000 Genomes Project and HapMap. First we used F-statistics to quantify genetic population differences and find ethnic diversity. Then we applied a long-range haplotype test to detect significant extreme long haplotypes, and then the integrated haplotype score (iHS) to find genetic selection at Cryptochrome 1, Cryptochrome 2, and MTNR1B. We observed genetic population differences and ethnic diversity at one glucose-associated Cryptochrome 1 single-nucleotide polymorphism (SNP) (rs8192440), one glucose-associated Cryptochrome 2 SNP (rs11605924), and one glucose-associated MTNR1B SNP (rs10830963) by F-statistics. Both Cryptochrome 1 and MTNR1B also showed selection by the iHS. These observations show new evidence for evolution at Cryptochrome 1, Cryptochrome 2 and MTNR1B. Further investigation should continue to examine the evolution of circadian clock- and glucose-related genes.

Analysis of genetic selection at insulin receptor substrate-2 gene loci

Purpose

Type 2 diabetes mellitus (T2DM) is highly heritable and exhibits significant variability in prevalence between different populations. Prevalence of T2DM is higher in Asian and African relative to European populations. During evolution, traditional feast-famine cycles likely led to significant natural selection impacting metabolic genes. Human adaptation to environmental changes (food supply, lifestyle, climate, and geography) likely influenced differential selection of T2DM-associated genes. Together, insulin receptor substrate-1 and -2 (IRS1 and IRS2) genes encode the major ligands of insulin and IGF1 receptors. Irs2-deficient mice exhibit a T2DM phenotype with severe insulin resistance, and a common IRS2 polymorphism is associated with T2DM. Therefore, the present study sought evidence of natural selection at IRS2 loci.

Methods

Data were sourced from the HapMap and 1000 Genomes projects, comprising four different populations with distinct ancestries: European, Yoruba, Han Chinese, and Japanese. A three-step method was applied to detect IRS2 locus selection. The long-range haplotype (LRH) test detected unusual extended haplotypes, the integrated haplotype score (iHS) detected selection, and Wright's F-statistics (particularly Wright's fixation index: F_ST) were calculated as a measure of population differentiation.

Results

The African population exhibited highly significant LRH findings (percentile >99.9, p = 0.005-0.0009), while both the European and African populations exhibited extreme positive iHS test scores ([iHS] >2.5).

Conclusion

These findings indicate that genetic selection has occurred at the IRS2 locus, warranting further research into the adaptive evolution of metabolic disorder-associated genes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-021-00745-y.

The evolution of group differences in changing environments

The selection pressures that have shaped the evolution of complex traits in humans remain largely unknown, and in some contexts highly contentious, perhaps above all where they concern mean trait differences among groups. To date, the discussion has focused on whether such group differences have any genetic basis, and if so, whether they are without fitness consequences and arose via random genetic drift, or whether they were driven by selection for different trait optima in different environments. Here, we highlight a plausible alternative: that many complex traits evolve under stabilizing selection in the face of shifting environmental effects. Under this scenario, there will be rapid evolution at the loci that contribute to trait variation, even when the trait optimum remains the same. These considerations underscore the strong assumptions about environmental effects that are required in ascribing trait differences among groups to genetic differences.

Assessment of the potential role of natural selection in type 2 diabetes and related traits across human continental ancestry groups: comparison of phenotypic with genotypic divergence

AIMS/HYPOTHESIS

Prevalence of type 2 diabetes differs among human ancestry groups, and many hypotheses invoke differential natural selection to account for these differences. We sought to assess the potential role of differential natural selection across major continental ancestry groups for diabetes and related traits, by comparison of genetic and phenotypic differences.

METHODS

This was a cross-sectional comparison among 734 individuals from an urban sample (none of whom was more closely related to another than third-degree relatives), including 83 African Americans, 523 American Indians and 128 European Americans. Participants were not recruited based on diabetes status or other traits. BMI was calculated, and diabetes was diagnosed by a 75 g oral glucose tolerance test. In those with normal glucose tolerance (n = 434), fasting insulin and 30 min post-load insulin, adjusted for 30 min glucose, were taken as measures of insulin resistance and secretion, respectively. Whole exome sequencing was performed, resulting in 97,388 common (minor allele frequency ≥ 5%) variants; the coancestry coefficient (F_ST) was calculated across all markers as a measure of genetic divergence among ancestry groups. The phenotypic divergence index (P_ST) was also calculated from the phenotypic differences and heritability (which was estimated from genetic relatedness calculated empirically across all markers in 761 American Indian participants prior to the exclusion of close relatives). Under evolutionary neutrality, the expectation is P_ST = F_ST, while for traits under differential selection P_ST is expected to be significantly greater than F_ST. A bootstrap procedure was used to test the hypothesis P_ST = F_ST. RESULTS: With adjustment for age and sex, prevalence of type 2 diabetes was 34.0% in American Indians, 12.4% in African Americans and 10.4% in European Americans (p = 2.9 × 10^-10 for difference among groups). Mean BMI was 36.3, 33.4 and 33.0 kg/m², respectively (p = 1.9 × 10^-7). Mean fasting insulin was 63.8, 48.4 and 45.2 pmol/l (p = 9.2 × 10^-5), while mean 30 min insulin was 559.8, 553.5 and 358.8 pmol/l, respectively (p = 5.7 × 10^-8). F_ST across all markers was 0.130, while P_ST for liability to diabetes, adjusted for age and sex, was 0.149 (p = 0.35 for difference with F_ST). P_ST was 0.094 for BMI (p = 0.54), 0.095 for fasting insulin (p = 0.54) and 0.216 (p = 0.18) for 30 min insulin. For type 2 diabetes and BMI, the maximum divergence between populations was observed between American Indians and European Americans (P_ST-MAX = 0.22, p = 0.37, and P_ST-MAX = 0.14, p = 0.61), which suggests that a relatively modest 22% or 14% of the genetic variance, respectively, can potentially be explained by differential selection (assuming the absence of neutral drift).

CONCLUSIONS/INTERPRETATION

These analyses suggest that while type 2 diabetes and related traits differ significantly among continental ancestry groups, the differences are consistent with neutral expectations based on heritability and genetic distances. While these analyses do not exclude a modest role for natural selection, they do not support the hypothesis that differential natural selection is necessary to explain the phenotypic differences among these ancestry groups. Graphical abstract.

Ethnic differences in adiposity and diabetes risk - insights from genetic studies

Type 2 diabetes is more common in non-Europeans and starts at a younger age and at lower BMI cut-offs. This review discusses the insights from genetic studies about pathophysiological mechanisms which determine risk of disease with a focus on the role of adiposity and body fat distribution in ethnic disparity in risk of type 2 diabetes. During the past decade, genome-wide association studies (GWAS) have identified more than 400 genetic variants associated with the risk of type 2 diabetes. The Eurocentric nature of these genetic studies has made them less effective in identifying mechanisms that make non-Europeans more susceptible to higher risk of disease. One possible mechanism suggested by epidemiological studies is the role of ethnic difference in body fat distribution. Using genetic variants associated with an ability to store extra fat in a safe place, which is subcutaneous adipose tissue, we discuss how different ethnic groups could be genetically less susceptible to type 2 diabetes by developing a more favourable fat distribution.

High genetic burden of type 2 diabetes can promote the high prevalence of disease: a longitudinal cohort study in Iran

Type 2 diabetes (T2D) is emerging as one of the serious public health issues in both developed and developing counties. Here, we surveyed the worldwide population differentiation in T2D-associated variants and assessed the genetic burden of the disease in an ongoing Tehran Cardio-Metabolic Genetic Study (TCGS) cohort represented the Iranian population. We found multiple SNPs that were significantly depleted or enriched in at least one of the five populations of 1,000 Genome Project (African, American, East Asian, European, and South Asian) as well as the Iranian population. Interestingly, TCF7L2, a well-known associated gene with T2D, harbors the highest number of enriched risk alleles almost in all populations except for East Asian, where this gene embraces the largest number of significantly depleted risk alleles. The polygenic risk score (PRS) of the enriched risk alleles was calculated for 1,867 diabetic and 2,855 non-diabetic participants in the TCGS cohort, interestingly demonstrating that the risk of developing T2D was almost two times higher in top PRS quintile compared with the lowest quintile after adjusting for other known risk factors.

PRDM15 Is Associated with Risk of Chronic Obstructive Pulmonary Disease in a Rural Population in Chile

BACKGROUND

Genome-wide association studies (GWAS) have accelerated our understanding of the genetic underpinnings of chronic obstructive pulmonary disease (COPD); however, GWAS populations have typically consisted of European descent, with ∼1% of Latin American ancestry.

OBJECTIVE

To overcome this limitation, we conducted a GWAS in a rural Chilean population with increased COPD risk to investigate genetic variation of COPD risk in this understudied minority population.

METHOD

We carried out a case-control study of 214 COPD patients (defined by the GOLD criteria) and 193 healthy controls in Talca, Chile. DNA was extracted from venous blood and genotyped on the Illumina Global Screening Array (n = 754,159 markers). After exclusion based on Hardy-Weinberg equilibrium (p ≤ 0.001), call rates (<95%), and minor allele frequencies (<0.5%) in controls, 455,564 markers were available for logistic regression.

RESULTS

PRDM15 rs1054761 C allele (p = 2.22 × 10-7) was associated with decreased COPD risk. Three PRDM15 SNPs located on chromosome 21 were significantly associated with COPD risk (p < 10-6). Two of these SNPs, rs1054761 and rs4075967, were located on a noncoding transcript variant region of the gene.

CONCLUSION

PRDM15 overexpression may play a role in the B-cell dysregulation in COPD pathogenesis. To the best of our knowledge, the association between PRDM15 and COPD risk was not previously found in GWAS studies in largely European populations, highlighting the importance of investigating novel variants associated with COPD risk among ethnically diverse populations.

Racial/ethnic differences in the burden of type 2 diabetes over the life course: a focus on the USA and India

Type 2 diabetes is a common disease worldwide, but its prevalence varies widely by geographical region and by race/ethnicity. This review summarises differences in the frequencies of type 2 diabetes according to race, ethnicity, socioeconomic position, area of residence and environmental toxins. Type 2 diabetes susceptibility often begins early in life, starting with genetic susceptibility at conception and continuing in later life, via in utero, childhood and adult exposures. Early-life factors may lead to overt type 2 diabetes in childhood or in later life, supporting the concept of developmental origins of health and disease. The causes of the racial/ethnic differences in incidence of type 2 diabetes are not well understood. Specifically, the relative contributions of genetic and environmental factors to such differences are largely unknown. With a few exceptions in isolated populations, there is little evidence that differences in frequencies of known type 2 diabetes susceptibility genetic alleles account for racial/ethnic differences, although the search for genetic susceptibility has not been uniform among the world's racial/ethnic groups. In the USA, race/ethnicity is associated with many other risk factors for type 2 diabetes, including being overweight/obese, diet and socioeconomic status. Some studies suggest that some of these factors may account for the race/ethnic differences in prevalence of type 2 diabetes, although there is inadequate research in this area. A better understanding of the impact of these factors on type 2 diabetes risk should lead to more effective prevention and treatment of this disease. This has not yet been achieved but should be a goal for future research.

Pilot GWAS of caries in African-Americans shows genetic heterogeneity

BACKGROUND

Dental caries is the most common chronic disease in the US and disproportionately affects racial/ethnic minorities. Caries is heritable, and though genetic heterogeneity exists between ancestries for a substantial portion of loci associated with complex disease, a genome-wide association study (GWAS) of caries specifically in African Americans has not been performed previously.

METHODS

We performed exploratory GWAS of dental caries in 109 African American adults (age > 18) and 96 children (age 3-12) from the Center for Oral Health Research in Appalachia (COHRA1 cohort). Caries phenotypes (DMFS, DMFT, dft, and dfs indices) assessed by dental exams were tested for association with 5 million genotyped or imputed single nucleotide polymorphisms (SNPs), separately in the two age groups. The GWAS was performed using linear regression with adjustment for age, sex, and two principal components of ancestry. A maximum of 1 million adaptive permutations were run to determine empirical significance.

RESULTS

No loci met the threshold for genome-wide significance, though some of the strongest signals were near genes previously implicated in caries such as antimicrobial peptide DEFB1 (rs2515501; p = 4.54 × 10- 6) and TUFT1 (rs11805632; p = 5.15 × 10- 6). Effect estimates of lead SNPs at suggestive loci were compared between African Americans and Caucasians (adults N = 918; children N = 983). Significant (p < 5 × 10- 8) genetic heterogeneity for caries risk was found between racial groups for 50% of the suggestive loci in children, and 12-18% of the suggestive loci in adults.

CONCLUSIONS

The genetic heterogeneity results suggest that there may be differences in the contributions of genetic variants to caries across racial groups, and highlight the critical need for the inclusion of minorities in subsequent and larger genetic studies of caries in order to meet the goals of precision medicine and to reduce oral health disparities.

Genetic Basis of Obesity and Type 2 Diabetes in Africans: Impact on Precision Medicine

PURPOSE OF REVIEW

Recent advances in genomics provide opportunities for novel understanding of the biology of human traits with the goal of improving human health. Here, we review recent obesity and type 2 diabetes (T2D)-related genomic studies in African populations and discuss the implications of limited genomics studies on health disparity and precision medicine.

RECENT FINDINGS

Genome-wide association studies in Africans have yielded genetic discovery that would otherwise not be possible; these include identification of novel loci associated with obesity (SEMA-4D, PRKCA, WARS2), metabolic syndrome (CA-10, CTNNA3), and T2D (AGMO, ZRANB3). ZRANB3 was recently demonstrated to influence beta cell mass and insulin response. Despite these promising results, genomic studies in African populations are still limited and thus genomics tools and approaches such as polygenic risk scores and precision medicine are likely to have limited utility in Africans with the unacceptable possibility of exacerbating prevailing health disparities. African populations provide unique opportunities for increasing our understanding of the genetic basis of cardiometabolic disorders. We highlight the need for more coordinated and sustained efforts to increase the representation of Africans in genomic studies both as participants and scientists.

GlobAl Distribution of GEnetic Traits (GADGET) web server: polygenic trait scores worldwide

Human populations from around the world show striking phenotypic variation across a wide variety of traits. Genome-wide association studies (GWAS) are used to uncover genetic variants that influence the expression of heritable human traits; accordingly, population-specific distributions of GWAS-implicated variants may shed light on the genetic basis of human phenotypic diversity. With this in mind, we developed the GlobAl Distribution of GEnetic Traits web server (GADGET http://gadget.biosci.gatech.edu). The GADGET web server provides users with a dynamic visual platform for exploring the relationship between worldwide genetic diversity and the genetic architecture underlying numerous human phenotypes. GADGET integrates trait-implicated single nucleotide polymorphisms (SNPs) from GWAS, with population genetic data from the 1000 Genomes Project, to calculate genome-wide polygenic trait scores (PTS) for 818 phenotypes in 2504 individual genomes. Population-specific distributions of PTS are shown for 26 human populations across 5 continental population groups, with traits ordered based on the extent of variation observed among populations. Users of GADGET can also upload custom trait SNP sets to visualize global PTS distributions for their own traits of interest.

Phenotypic and genotypic differences between Indian and Scandinavian women with gestational diabetes mellitus

OBJECTIVE

Gestational diabetes mellitus (GDM) is a transient form of diabetes characterized by impaired insulin secretion and action during pregnancy. Population-based differences in prevalence exist which could be explained by phenotypic and genetic differences. The aim of this study was to examine these differences in pregnant women from Punjab, India and Scandinavia.

METHODS

Eighty-five GDM/T2D loci in European and/or Indian populations from previous studies were assessed for association with GDM based on Swedish GDM criteria in 4018 Punjabi Indian and 507 Swedish pregnant women. Selected loci were replicated in Scandinavian cohorts, Radiel (N = 398, Finnish) and STORK/STORK-G (N = 780, Norwegian).

RESULTS

Punjabi Indian women had higher GDM prevalence, lower insulin secretion and better insulin sensitivity than Swedish women. There were significant frequency differences of GDM/T2D risk alleles between both populations. rs7178572 at HMG20A, previously associated with GDM in South Indian and European women, was replicated in North Indian women. The T2D risk SNP rs11605924 in the CRY2 gene was associated with increased GDM risk in Scandinavian but decreased GDM risk in Punjabi Indian women. No other overlap was seen between GDM loci in both populations.

CONCLUSIONS

Gestational diabetes mellitus is more common in Indian than Swedish women, which partially can be attributed to differences in insulin secretion and action. There was marked heterogeneity in the GDM phenotypes between the populations which could only partially be explained by genetic differences.

Omega-3 and omega-6 polyunsaturated fatty acids and metabolic syndrome: A systematic review and meta-analysis

BACKGROUND & AIMS

Previous studies suggest that polyunsaturated fatty acids (PUFAs) may reduce the risk of metabolic diseases, but some have shown ambiguous results. The aim of this study was to systematically evaluate and summarize available evidence on the association between omega-3 and omega-6 PUFA levels and risk of metabolic syndrome (MetS).

METHODS

A systematic literature search of articles published until December 2017 was conducted in PubMed, Web of Science, and Cochrane Library databases. Meta-analyses of the highest vs. lowest categories of omega-3 and omega-6 PUFAs were conducted using the random effects models.

RESULTS

Thirteen studies (2 case-control, 9 cross-sectional, 1 nested case-control, and 1 prospective cohort) with 36,542 individuals were included. Higher omega-3 PUFA levels in diets or blood were associated with a 26% reduction in the risk of MetS (odds ratio (OR)/relative risk (RR) 0.74, 95% confidence interval (CI) 0.62-0.89). This inverse association was evident among studies with Asian populations (OR/RR 0.69, 95% CI 0.54-0.87), but not among those with American/European populations (OR/RR 0.84, 95% CI 0.55-1.28). Null results were found regarding the association between circulating/dietary omega-6 PUFAs and MetS.

CONCLUSION

The present meta-analysis indicates that higher intakes of omega-3 PUFAs, but not omega-6 PUFAs, was associated with lower MetS risk; adding to the current body of evidence on the metabolic health effects of circulating/dietary omega-3 PUFAs.

Association between genetic risk variants and glucose intolerance during pregnancy in north Indian women

Background

Gestational diabetes (GDM) is a more common problem in India than in many other parts of the world but it is not known whether this is due to unique environmental factors or a unique genetic background. To address this question we examined whether the same genetic variants associated with GDM and Type 2 Diabetes (T2D) in Caucasians also were associated with GDM in North Indian women.

Methods

Five thousand one hundred pregnant women of gestational age 24–28 weeks from Punjab were studied by a 75 g oral glucose tolerance test (OGTT). GDM was diagnosed by both WHO1999 and 2013 criteria. 79 single nucleotide polymorphisms (SNPs) previously associated with T2D and glycemic traits (12 of them also with GDM) and 6 SNPs from previous T2D associations based on Indian population (some also with European) were genotyped on a Sequenom platform or using Taqman assays in DNA from 4018 women.

Results

In support of previous findings in Caucasian GDM, SNPs at KCJN11 and GRB14 loci were nominally associated with GDM1999 risk in Indian women (both p = 0.02). Notably, T2D risk alleles of the variant rs1552224 near CENTD2, rs11708067 in ADCY5 and rs11605924 in CRY2 genes associated with protection from GDM regardless of criteria applied (p < 0.025). SNPs rs7607980 near COBLL1 (p = 0.0001), rs13389219 near GRB14 (p = 0.026) and rs10423928 in the GIPR gene (p = 0.012) as well as the genetic risk score (GRS) for these previously shown insulin resistance loci here associated with insulin resistance defined by HOMA2-IR and showed a trend towards GDM. GRS comprised of 3 insulin secretion loci here associated with insulin secretion but not GDM.

Conclusions

GDM in women from Punjab in Northern India shows a genetic component, seemingly driven by insulin resistance and secretion and partly shared with GDM in other parts of the world. Most previous T2D loci discovered in European studies did not associate with GDM in North India, indicative of different genetic etiology or alternately, differences in the linkage disequilibrium (LD) structure between populations in which the associated SNPs were identified and Northern Indian women. Interestingly some T2D risk variants were in fact indicative of being protective for GDM in these Indian women.

Electronic supplementary material

The online version of this article (10.1186/s12920-018-0380-8) contains supplementary material, which is available to authorized users.

Diabetes mellitus secondary to pancreatic diseases (type 3c): The effect of smoking on the exocrine-endocrine interactions of the pancreas

The present study was conducted to ascertain how cigarette smoke affects the exocrine-endocrine interactions of the human pancreas with diabetes mellitus secondary to pancreatic diseases (type 3c). Blood has been collected from smoking and non-smoking healthy individuals as well as from patients with diagnosed chronic pancreatitis and diabetes type 3c. The concentrations of interleukin-6, endothelin-1 and insulin in the plasma were determined by enzyme-linked immunosorbent assay (ELISA) tests. The activities of amylase and lipase in the serum, as well as the lipid profile, creatinine, uric acid and urea concentrations, were measured using colorimetric methods. Samples of normal pancreatic tissue and chronic pancreatitis were verified histopathologically and then interleukin-6, endothelin-1, insulin and glucagon were localized by immunohistochemical staining using a monoclonal anti-human antibody. The highest levels of interleukin-6 and endothelin-1 and the lowest levels of insulin and glucagon intensity from the immunostaining were observed in smoking patients with diabetes. In all smoking patients with pancreatitis and diabetes, there was a significant elevation in interleukin-6 and endothelin-1 concentration and amylase and lipase activities, hyperlipidaemia and a lower value of estimated glomerular filtration rate and blood urea nitrogen when compared to non-smokers. Our study confirmed that smoking exerts a pro-inflammatory effect and disturbs the exocrine-endocrine interactions of the pancreas.

A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations

Genetic association studies in admixed populations allow us to gain deeper understanding of the genetic architecture of human diseases and traits. However, population stratification, complicated linkage disequilibrium (LD) patterns, and the complex interplay of allelic and ancestry effects on phenotypic traits pose challenges in such analyses. These issues may lead to detecting spurious associations and/or result in reduced statistical power. Fortunately, if handled appropriately, these same challenges provide unique opportunities for gene mapping. To address these challenges and to take these opportunities, we propose a robust and powerful two-step testing procedure Local Ancestry Adjusted Allelic (LAAA) association. In the first step, LAAA robustly captures associations due to allelic effect, ancestry effect, and interaction effect, allowing detection of effect heterogeneity across ancestral populations. In the second step, LAAA identifies the source of association, namely allelic, ancestry, or the combination. By jointly modeling allele, local ancestry, and ancestry-specific allelic effects, LAAA is highly powerful in capturing the presence of interaction between ancestry and allele effect. We evaluated the validity and statistical power of LAAA through simulations over a broad spectrum of scenarios. We further illustrated its usefulness by application to the Candidate Gene Association Resource (CARe) African American participants for association with hemoglobin levels. We were able to replicate independent groups' previously identified loci that would have been missed in CARe without joint testing. Moreover, the loci, for which LAAA detected potential effect heterogeneity, were replicated among African Americans from the Women's Health Initiative study. LAAA is freely available at https://yunliweb.its.unc.edu/LAAA.

Current Level of Fish Consumption is Associated with Mortality in Chinese but not US Adults: New Findings From Two Nationwide Cohort Studies With 14 and 9.8 Years of Follow-Up

SCOPE

Whether dietary fish consumption is linked to mortality remains unclear. We aim to investigate the association of fish consumption with mortality in Chinese and US nationwide populations.

METHODS AND RESULTS

We utilize data from China Health and Nutrition Survey (CHNS, n = 14 117) and National Health and Nutrition Examination Survey (NHANES, n = 33 221) including NHANES III conducted in 1988-1994 and continuous NHANES 1999-2010. Cox proportional hazards regression is used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median follow-up of 14 and 9.8 years for CHNS and NHANES, 1007 and 5209 deaths are documented, respectively. Among Chinese adults, increased fish intake is significantly associated with decreased total mortality. The multivariable-adjusted HRs (95% CIs) across increasing categories of fish intake are 0.45 (0.36-0.56), 0.72 (0.60-0.86), and 0.70 (0.59-0.85) (p trend < 0.0001). However, fish intake is not associated with total mortality among US adults (p trend = 0.21). We only detected a borderline inverse association between fish intake and stroke mortality (p trend = 0.05), whereas a positive association with diabetes mortality in the third category of fish intake in NHANES.

CONCLUSION

In these two nationwide cohort studies, fish consumption is associated with a reduced risk of total mortality for Chinese but not US populations.

Type 2 diabetes mellitus: distribution of genetic markers in Kazakh population

Background

Ethnic differences exist in the frequencies of genetic variations that contribute to the risk of common disease. This study aimed to analyse the distribution of several genes, previously associated with susceptibility to type 2 diabetes and obesity-related phenotypes, in a Kazakh population.

Methods

A total of 966 individuals belonging to the Kazakh ethnicity were recruited from an outpatient clinic. We genotyped 41 common single nucleotide polymorphisms (SNPs) previously associated with type 2 diabetes in other ethnic groups and 31 of these were in Hardy–Weinberg equilibrium. The obtained allele frequencies were further compared to publicly available data from other ethnic populations. Allele frequencies for other (compared) populations were pooled from the haplotype map (HapMap) database. Principal component analysis (PCA), cluster analysis, and multidimensional scaling (MDS) were used for the analysis of genetic relationship between the populations.

Results

Comparative analysis of allele frequencies of the studied SNPs showed significant differentiation among the studied populations. The Kazakh population was grouped with Asian populations according to the cluster analysis and with the Caucasian populations according to PCA. According to MDS, results of the current study show that the Kazakh population holds an intermediate position between Caucasian and Asian populations.

Conclusion

A high percentage of population differentiation was observed between Kazakh and world populations. The Kazakh population was clustered with Caucasian populations, and this result may indicate a significant Caucasian component in the Kazakh gene pool.

Increasing prevalence of type 2 diabetes mellitus and impact of ethnicity in north Sudan

BACKGROUND

Diabetes mellitus constitutes a global health threat, with increasing burden of disease in low and middle-income countries witnessing ongoing epidemiological transition including Sudan.

AIMS

To study the prevalence of type 2 diabetes mellitus (T2DM) and prediabetes and determine the relationship to gender, age, waist circumference, body mass index, residence and ethnicity among the adult population in north Sudan.

METHODS

A cross-sectional, population-based study in Northern State and River Nile State using random multi-stage cluster sampling targeting 5376 participants from 14 localities divided into 60 urban and 40 rural clusters. In each cluster, 60 households were studied. Blood glucose level and anthropometric measurements were recorded and a questionnaire containing demographic data was obtained from each participant.

RESULTS

The prevalence of T2DM among participants was 18.7% and prediabetes was 12.9%. Among people living with T2DM, 694(71.0%) were known cases of T2DM, whereas 284(29.0%) were newly diagnosed cases. The significant associated risk factors for T2DM included urban residence (AOR 1.23, 95%CI 1.09-1.41), age above 60 years (AOR 4.77, 95%CI 4.04-5.63), obese BMI (AOR 1.26, 95%CI 1.03-1.55) and central obesity (AOR 1.39, 95%CI 1.14-1.68). Compared to indigenous population, individuals of Egyptian descents (AOR 1.28, 95%CI 1.04-1.57) and mixed origin (AOR 1.24, 95%CI 1.04-1.48) had increased risk of T2DM.

CONCLUSION

The prevalence of T2DM and prediabetes in north Sudan have increased significantly since 1996 with variations between ethnicities which showed to be an independent risk factor for T2DM. Health authorities are recommended to set plans to meet the health needs of these communities.

Multiethnic polygenic risk scores improve risk prediction in diverse populations

Methods for genetic risk prediction have been widely investigated in recent years. However, most available training data involves European samples, and it is currently unclear how to accurately predict disease risk in other populations. Previous studies have used either training data from European samples in large sample size or training data from the target population in small sample size, but not both. Here, we introduce a multiethnic polygenic risk score that combines training data from European samples and training data from the target population. We applied this approach to predict type 2 diabetes (T2D) in a Latino cohort using both publicly available European summary statistics in large sample size (Neff  = 40k) and Latino training data in small sample size (Neff  = 8k). Here, we attained a >70% relative improvement in prediction accuracy (from R2  = 0.027 to 0.047) compared to methods that use only one source of training data, consistent with large relative improvements in simulations. We observed a systematically lower load of T2D risk alleles in Latino individuals with more European ancestry, which could be explained by polygenic selection in ancestral European and/or Native American populations. We predict T2D in a South Asian UK Biobank cohort using European (Neff  = 40k) and South Asian (Neff  = 16k) training data and attained a >70% relative improvement in prediction accuracy, and application to predict height in an African UK Biobank cohort using European (N = 113k) and African (N = 2k) training data attained a 30% relative improvement. Our work reduces the gap in polygenic risk prediction accuracy between European and non-European target populations.

Personalized medicine-a modern approach for the diagnosis and management of hypertension

The main goal of treating hypertension is to reduce blood pressure to physiological levels and thereby prevent risk of cardiovascular disease and hypertension-associated target organ damage. Despite reductions in major risk factors and the availability of a plethora of effective antihypertensive drugs, the control of blood pressure to target values is still poor due to multiple factors including apparent drug resistance and lack of adherence. An explanation for this problem is related to the current reductionist and ‘trial-and-error’ approach in the management of hypertension, as we may oversimplify the complex nature of the disease and not pay enough attention to the heterogeneity of the pathophysiology and clinical presentation of the disorder. Taking into account specific risk factors, genetic phenotype, pharmacokinetic characteristics, and other particular features unique to each patient, would allow a personalized approach to managing the disease. Personalized medicine therefore represents the tailoring of medical approach and treatment to the individual characteristics of each patient and is expected to become the paradigm of future healthcare. The advancement of systems biology research and the rapid development of high-throughput technologies, as well as the characterization of different –omics, have contributed to a shift in modern biological and medical research from traditional hypothesis-driven designs toward data-driven studies and have facilitated the evolution of personalized or precision medicine for chronic diseases such as hypertension.

Diabetes in sub-Saharan Africa - from policy to practice to progress: targeting the existing gaps for future care for diabetes

The global prevalence and impact of diabetes has increased dramatically, particularly in sub-Saharan Africa. This region faces unique challenges in combating the disease including lack of funding for noncommunicable diseases, lack of availability of studies and guidelines specific to the population, lack of availability of medications, differences in urban and rural patients, and inequity between public and private sector health care. Because of these challenges, diabetes has a greater impact on morbidity and mortality related to the disease in sub-Saharan Africa than any other region in the world. In order to address these unacceptably poor trends, contextualized strategies for the prevention, identification, management, and financing of diabetes care within this population must be developed. This narrative review provides insights into the policy landscape, epidemiology, pathophysiology, care protocols, medication availability, and health care systems to give readers a comprehensive summary of many factors in these domains as they pertain to diabetes in sub-Saharan Africa. In addition to providing a review of the current evidence available in these domains, potential solutions to address the major gaps in care will be proposed to reverse the negative trends seen with diabetes in sub-Saharan Africa.

Revealing phenotype-associated functional differences by genome-wide scan of ancient haplotype blocks

Genome-wide scans for positive selection have become important for genomic medicine, and many studies aim to find genomic regions affected by positive selection that are associated with risk allele variations among populations. Most such studies are designed to detect recent positive selection. However, we hypothesize that ancient positive selection is also important for adaptation to pathogens, and has affected current immune-mediated common diseases. Based on this hypothesis, we developed a novel linkage disequilibrium-based pipeline, which aims to detect regions associated with ancient positive selection across populations from single nucleotide polymorphism (SNP) data. By applying this pipeline to the genotypes in the International HapMap project database, we show that genes in the detected regions are enriched in pathways related to the immune system and infectious diseases. The detected regions also contain SNPs reported to be associated with cancers and metabolic diseases, obesity-related traits, type 2 diabetes, and allergic sensitization. These SNPs were further mapped to biological pathways to determine the associations between phenotypes and molecular functions. Assessments of candidate regions to identify functions associated with variations in incidence rates of these diseases are needed in the future.

MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies

Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition-multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).

Predictive utility of a genetic risk score of common variants associated with type 2 diabetes in a black South African population

AIMS

To determine the predictive utility of polygenic risk scores of common variants associated with type 2 diabetes derived from the European and Asian ethnicities among a black South African population.

METHOD

Our study was a case-control study nested within the Prospective Urban and Rural Epidemiological (PURE) study of 178 male and female cases, matched for age and gender with 178 controls. Four types of genetic risk scores (GRS) were developed from 66 selected SNPs. These comprised of beta cell related variants (GRSb), variants which had significant associations with T2D in our study (GRSn), variants from the trans-ethnic meta-analysis (GRStrans) and all the 66 selected SNPs (GRSt).

RESULTS

Of the GRS's, only GRSn was associated with increased risk of T2D as indicated by an OR (95CI) of 1.21 (1.02-1.43) p-value=0.015. Stratified analysis of age and BMI, indicated the GRSn to be significantly associated with T2D among the non-obese and participants less than 50years. The area under the ROC of the T2D risk factors only was 0.652 (p value<0.001) and with the addition of GRSn it was 0.665 (p value<0.001).

CONCLUSIONS

The GRS of European and Asian derived variants have limited clinical utility in the black South African population. The inclusion of population specific variants in the GRS is pivotal.

Understanding rare and common diseases in the context of human evolution

The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.

Pharmacogenomic implications of the evolutionary history of infectious diseases in Africa

As the common birthplace of all human populations, modern humans have lived longer on the African continent than in any other geographical region of the world. This long history, along with the evolutionary need to adapt to environmental challenges such as exposure to infectious agents, has led to greater genetic variation in Africans. The vast genetic variation in Africans also extends to genes involved in the absorption, distribution, metabolism and excretion of pharmaceuticals. Ongoing cataloging of these clinically relevant variants reveals huge allele-frequency differences within and between African populations. Here, we examine Africa's large burden of infectious disease, discuss key examples of known genetic variation modulating disease risk, and provide examples of clinically relevant variants critical for establishing dosing guidelines. We propose that a more systematic characterization of the genetic diversity of African ancestry populations is required if the current benefits of precision medicine are to be extended to these populations.

Identification of type 2 diabetes subgroups through topological analysis of patient similarity

Type 2 diabetes (T2D) is a heterogeneous complex disease affecting more than 29 million Americans alone with a rising prevalence trending toward steady increases in the coming decades. Thus, there is a pressing clinical need to improve early prevention and clinical management of T2D and its complications. Clinicians have understood that patients who carry the T2D diagnosis have a variety of phenotypes and susceptibilities to diabetes-related complications. We used a precision medicine approach to characterize the complexity of T2D patient populations based on high-dimensional electronic medical records (EMRs) and genotype data from 11,210 individuals. We successfully identified three distinct subgroups of T2D from topology-based patient-patient networks. Subtype 1 was characterized by T2D complications diabetic nephropathy and diabetic retinopathy; subtype 2 was enriched for cancer malignancy and cardiovascular diseases; and subtype 3 was associated most strongly with cardiovascular diseases, neurological diseases, allergies, and HIV infections. We performed a genetic association analysis of the emergent T2D subtypes to identify subtype-specific genetic markers and identified 1279, 1227, and 1338 single-nucleotide polymorphisms (SNPs) that mapped to 425, 322, and 437 unique genes specific to subtypes 1, 2, and 3, respectively. By assessing the human disease-SNP association for each subtype, the enriched phenotypes and biological functions at the gene level for each subtype matched with the disease comorbidities and clinical differences that we identified through EMRs. Our approach demonstrates the utility of applying the precision medicine paradigm in T2D and the promise of extending the approach to the study of other complex, multifactorial diseases.

The Elevated Susceptibility to Diabetes in India: An Evolutionary Perspective

India has rapidly become a "diabetes capital" of the world, despite maintaining high rates of under-nutrition. Indians develop diabetes at younger age and at lower body weights than other populations. Here, we interpret these characteristics in terms of a "capacity-load" model of glucose homeostasis. Specifically, we assume that glycemic control depends on whether the body's "metabolic capacity," referring to traits, such as pancreatic insulin production and muscle glucose clearance, is able to resolve the "metabolic load" generated by high levels of body fat, high dietary glycemic load, and sedentary behavior. We employ data from modern cohorts to support the model and the interpretation that elevated diabetic risk among Indian populations results from the high metabolic load imposed by westernized lifestyles acting on a baseline of low metabolic capacity. We attribute this low metabolic capacity to the low birth weight characteristic of Indian populations, which is associated with short stature and low lean mass in adult life. Using stature as a marker of metabolic capacity, we review archeological and historical evidence to highlight long-term declines in Indian stature associated with adaptation to several ecological stresses. Underlying causes may include increasing population density following the emergence of agriculture, the spread of vegetarian diets, regular famines induced by monsoon failure, and the undermining of agricultural security during the colonial period. The reduced growth and thin physique that characterize Indian populations elevate susceptibility to truncal obesity, and increase the metabolic penalties arising from sedentary behavior and high glycemic diets. Improving metabolic capacity may require multiple generations; in the meantime, efforts to reduce the metabolic load will help ameliorate the situation.

Studying the Genetics of Complex Disease With Ancestry-Specific Human Phenotype Networks: The Case of Type 2 Diabetes in East Asian Populations

Genome‐wide association studies (GWAS) have led to the discovery of over 200 single nucleotide polymorphisms (SNPs) associated with type 2 diabetes mellitus (T2DM). Additionally, East Asians develop T2DM at a higher rate, younger age, and lower body mass index than their European ancestry counterparts. The reason behind this occurrence remains elusive. With comprehensive searches through the National Human Genome Research Institute (NHGRI) GWAS catalog literature, we compiled a database of 2,800 ancestry‐specific SNPs associated with T2DM and 70 other related traits. Manual data extraction was necessary because the GWAS catalog reports statistics such as odds ratio and P‐value, but does not consistently include ancestry information. Currently, many statistics are derived by combining initial and replication samples from study populations of mixed ancestry. Analysis of all‐inclusive data can be misleading, as not all SNPs are transferable across diverse populations. We used ancestry data to construct ancestry‐specific human phenotype networks (HPN) centered on T2DM. Quantitative and visual analysis of network models reveal the genetic disparities between ancestry groups. Of the 27 phenotypes in the East Asian HPN, six phenotypes were unique to the network, revealing the underlying ancestry‐specific nature of some SNPs associated with T2DM. We studied the relationship between T2DM and five phenotypes unique to the East Asian HPN to generate new interaction hypotheses in a clinical context. The genetic differences found in our ancestry‐specific HPNs suggest different pathways are involved in the pathogenesis of T2DM among different populations. Our study underlines the importance of ancestry in the development of T2DM and its implications in pharmocogenetics and personalized medicine.

Complex Genetics of Type 2 Diabetes and Effect Size: What have We Learned from Isolated Populations?

Genetic studies in large outbred populations have documented a complex, highly polygenic basis for type 2 diabetes (T2D). Most of the variants currently known to be associated with T2D risk have been identified in large studies that included tens of thousands of individuals who are representative of a single major ethnic group such as European, Asian, or African. However, most of these variants have only modest effects on the risk for T2D; identification of definitive 'causal variant' or 'causative loci' is typically lacking. Studies in isolated populations offer several advantages over outbred populations despite being, on average, much smaller in sample size. For example, reduced genetic variability, enrichment of rare variants, and a more uniform environment and lifestyle, which are hallmarks of isolated populations, can reduce the complexity of identifying disease-associated genes. To date, studies in isolated populations have provided valuable insight into the genetic basis of T2D by providing both a deeper understanding of previously identified T2D-associated variants (e.g. demonstrating that variants in KCNQ1 have a strong parent-of-origin effect) or providing novel variants (e.g. ABCC8 in Pima Indians, TBC1D4 in the Greenlandic population, HNF1A in Canadian Oji-Cree). This review summarizes advancements in genetic studies of T2D in outbred and isolated populations, and provides information on whether the difference in the prevalence of T2D in different populations (Pima Indians vs. non-Hispanic Whites and non-Hispanic Whites vs. non-Hispanic Blacks) can be explained by the difference in risk allele frequencies of established T2D variants.

Ethnic differences in prediabetes and diabetes in the Suriname Health Study

BACKGROUND

Diabetes is increasing worldwide, and information on risk factors to develop targeted interventions is limited. Therefore, we analyzed data of the Suriname Health Study to estimate the prevalence of prediabetes and diabetes. We also explored whether ethnic differences in prediabetes or diabetes risk could be explained by biological, demographic, lifestyle, anthropometric, and metabolic risk factors.

METHOD

The study was designed according to the WHO Steps guidelines. Fasting blood glucose levels were measured in 3393 respondents, aged 15-65 years, from an Amerindian, Creole, Hindustani, Javanese, Maroon or Mixed ethnic background. Prediabetes was defined by fasting blood glucose levels between 6.1 and 7.0 mmol/L and diabetes by fasting blood glucose levels ≥7.0 mmol/L or 'self-reported diabetes medication use.' For all ethnicities, we analyzed sex, age, marital status, educational level, income status, employment, smoking status, residence, physical activity, body mass index, waist circumference, hypertension, and the levels of triglyceride, total cholesterol, high-density lipoprotein-cholesterol and low-density lipoprotein-cholesterol.

RESULTS

The prevalence of prediabetes was 7.4%, while that of diabetes was 13 0%. From these diabetes cases, 39.6% were not diagnosed previously. No ethnic differences were observed in the prevalence of prediabetes. For diabetes, Hindustanis (23.3%) had twice the prevalence compared to other ethnic groups (4.7-14.2%). The associations of the risk factors with prediabetes or diabetes varied among the ethnic groups. The differences in the associations of ethnic groups with prediabetes or diabetes were partly explained by these risk factors.

CONCLUSIONS

The prevalence of diabetes in Suriname is high and most elevated in Hindustanis. The observed variations in risk factors among ethnic groups might explain the ethnic differences between these groups, but follow-up studies are needed to explore this in more depth.

Public and Population Health Genomics

Public health seeks to improve health at a population level through interventions that increase the net health benefit to the population as a whole. Advances in genomics knowledge and technologies can add to this endeavor, but also pose a challenge when faced with often conflicting public health (population) and genomic medicine (individual) perspectives. Combining the fields of genomic, population, and social sciences, population genomics or public health genomics looks at the promotion of health and prevention of disease using genomic knowledge through the lens of populations rather than individuals. In this chapter we will survey the three major disciplines contributing to population genomics (genomics, population, and social sciences) and explore two cross-cutting issues: global health and population versus individual health, using specific examples from diseases such as asthma, colon cancer, and cystic fibrosis.

Genetics of Type 2 Diabetes in African Americans

Type 2 diabetes (T2D) is a global health problem showing substantial ethnic disparity in disease prevalence. African Americans have one of the highest prevalence of T2D in the USA but little is known about their genetic risks. This review summarizes the findings of genetic regions and loci associated with T2D and related glycemic traits using linkage, admixture, and association approaches in populations of African ancestry. In particular, findings from genome-wide association and exome chip studies suggest the presence of both ancestry-specific and shared loci for T2D and glycemic traits. Among the European-identified loci that are transferable to individuals of African ancestry, allelic heterogeneity as well as differential linkage disequilibrium and risk allele frequencies pose challenges and opportunities for fine mapping and identification of causal variant(s) by trans-ancestry meta-analysis. More genetic research is needed in African ancestry populations including the next-generation sequencing to improve the understanding of genetic architecture of T2D.

BMD Loci Contribute to Ethnic and Developmental Differences in Skeletal Fragility across Populations: Assessment of Evolutionary Selection Pressures

Bone mineral density (BMD) is a highly heritable trait used both for the diagnosis of osteoporosis in adults and to assess bone health in children. Ethnic differences in BMD have been documented, with markedly higher levels in individuals of African descent, which partially explain disparity in osteoporosis risk across populations. To date, 63 independent genetic variants have been associated with BMD in adults of Northern-European ancestry. Here, we demonstrate that at least 61 of these variants are predictive of BMD early in life by studying their compound effect within two multiethnic pediatric cohorts. Furthermore, we show that within these cohorts and across populations worldwide the frequency of those alleles associated with increased BMD is systematically elevated in individuals of Sub-Saharan African ancestry. The amount of differentiation in the BMD genetic scores among Sub-Saharan and non-Sub-Saharan populations together with neutrality tests, suggest that these allelic differences are compatible with the hypothesis of selective pressures acting on the genetic determinants of BMD. These findings constitute an explorative contribution to the role of selection on ethnic BMD differences and likely a new example of polygenic adaptation acting on a human trait.

The role of climate and out-of-Africa migration in the frequencies of risk alleles for 21 human diseases

BACKGROUND

Demography and environmental adaptation can affect the global distribution of genetic variants and possibly the distribution of disease. Population heterozygosity of single nucleotide polymorphisms has been shown to decrease strongly with distance from Africa and this has been attributed to the effect of serial founding events during the migration of humans out of Africa. Additionally, population allele frequencies have been shown to change due to environmental adaptation. Here, we investigate the relationship of Out-of-Africa migration and climatic variables to the distribution of risk alleles for 21 diseases.

RESULTS

For each disease, we computed the regression of average heterozygosity and average allele frequency of the risk alleles with distance from Africa and 9 environmental variables. We compared these regressions to a null distribution created by regressing statistics for SNPs not associated with disease on distance from Africa and these environmental variables. Additionally, we used Bayenv 2.0 to assess the signal of environmental adaptation associated with individual risk SNPs. For those SNPs in HGDP and HapMap that are risk alleles for type 2 diabetes, we cannot reject that their distribution is as expected from Out-of-Africa migration. However, the allelic statistics for many other diseases correlate more closely with environmental variables than would be expected from the serial founder effect and show signals of environmental adaptation. We report strong environmental interactions with several autoimmune diseases, and note a particularly strong interaction between asthma and summer humidity. Additionally, we identified several risk genes with strong environmental associations.

CONCLUSIONS

For most diseases, migration does not explain the distribution of risk alleles and the worldwide pattern of allele frequencies for some diseases may be better explained by environmental associations, which suggests that some selection has acted on these diseases.

Role of Established Type 2 Diabetes-Susceptibility Genetic Variants in a High Prevalence American Indian Population

Several single nucleotide polymorphisms (SNPs) associated with type 2 diabetes mellitus (T2DM) have been identified, but there is little information on their role in populations at high risk for T2DM. We genotyped SNPs at 63 T2DM loci in 3,421 individuals from a high-risk American Indian population. Nominally significant (P < 0.05) associations were observed at nine SNPs in a direction consistent with the established association. A genetic risk score derived from all loci was strongly associated with T2DM (odds ratio 1.05 per risk allele, P = 6.2 × 10(-6)) and, in 292 nondiabetic individuals, with lower insulin secretion (by 4% per copy, P = 4.1 × 10(-6)). Genetic distances between American Indians and HapMap populations at T2DM markers did not differ significantly from genomic expectations. Analysis of U.S. national survey data suggested that 66% of the difference in T2DM prevalence between African Americans and European Americans, but none of the difference between American Indians and European Americans, was attributable to allele frequency differences at these loci. These analyses suggest that, in general, established T2DM loci influence T2DM in American Indians and that risk is mediated in part through an effect on insulin secretion. However, differences in allele frequencies do not account for the high population prevalence of T2DM.

Tuberculosis and diabetes mellitus in the Republic of Kiribati: a case-control study

OBJECTIVES

To better inform local management of TB-diabetes collaborative activities, we aimed to determine the prevalence of diabetes among persons with and without TB and to determine the association between TB and diabetes in Kiribati, a Pacific Island nation.

METHODS

We compared consecutively enrolled TB cases to a group of randomly selected community controls without evidence of TB. Diabetes was diagnosed by HbA1c, and clinical and demographic data were collected. A tuberculin skin test was administered to controls. The chi-square test was used to assess significance in differences between cases and controls. We also calculated an odds ratio, with 95% confidence intervals, for the odds of diabetes among cases relative to controls. Unweighted multivariate logistic regression was performed to adjust for the effects of age and sex.

RESULTS

A total of 275 TB cases and 499 controls were enrolled. The diabetes prevalence in cases (101, 37%) was significantly greater than in controls (94, 19%) (adjusted odds ratio: 2.8; 95% CI 2.0-4.1). Fifty-five percent (108) of all diabetic diagnoses were new; this proportion was higher among controls (64.8%) than cases (46.5%). Five patients with TB were screened to detect one patient with diabetes.

CONCLUSIONS

There is a strong association between TB and diabetes in Kiribati and bidirectional screening should be conducted in this setting.

Disease risk factors identified through shared genetic architecture and electronic medical records

Genome-wide association studies have identified genetic variants for thousands of diseases and traits. We evaluated the relationships between specific risk factors (for example, blood cholesterol level) and diseases on the basis of their shared genetic architecture in a comprehensive human disease-single-nucleotide polymorphism association database (VARIMED), analyzing the findings from 8962 published association studies. Similarity between traits and diseases was statistically evaluated on the basis of their association with shared gene variants. We identified 120 disease-trait pairs that were statistically similar, and of these, we tested and validated five previously unknown disease-trait associations by searching electronic medical records (EMRs) from three independent medical centers for evidence of the trait appearing in patients within 1 year of first diagnosis of the disease. We validated that the mean corpuscular volume is elevated before diagnosis of acute lymphoblastic leukemia; both have associated variants in the gene IKZF1. Platelet count is decreased before diagnosis of alcohol dependence; both are associated with variants in the gene C12orf51. Alkaline phosphatase level is elevated in patients with venous thromboembolism; both share variants in ABO. Similarly, we found that prostate-specific antigen and serum magnesium levels were altered before the diagnosis of lung cancer and gastric cancer, respectively. Disease-trait associations identify traits that could serve as future prognostics, if validated through EMR and subsequent prospective trials.

T2DM GWAS in the Lebanese population confirms the role of TCF7L2 and CDKAL1 in disease susceptibility

Genome-wide association studies (GWAS) of multiple populations with distinctive genetic and lifestyle backgrounds are crucial to the understanding of Type 2 Diabetes Mellitus (T2DM) pathophysiology. We report a GWAS on the genetic basis of T2DM in a 3,286 Lebanese participants. More than 5,000,000 SNPs were directly genotyped or imputed using the 1000 Genomes Project reference panels. We identify genome-wide significant variants in two loci CDKAL1 and TCF7L2, independent of sex, age and BMI, with leading variants rs7766070 (OR = 1.39, P = 4.77 × 10(-9)) and rs34872471 (OR = 1.35, P = 1.01 × 10(-8)) respectively. The current study is the first GWAS to find genomic regions implicated in T2DM in the Lebanese population. The results support a central role of CDKAL1 and TCF7L2 in T2DM susceptibility in Southwest Asian populations and provide a plausible component for understanding molecular mechanisms involved in the disease.

Causes of type 2 diabetes in China

The prevalence of diabetes in China has increased substantially over recent decades, with more than 100 million people estimated to be affected by the disease presently. During this period there has been an increase in the rates of obesity and a reduction in physical activity. Many of the changes in lifestyle and diet are a result of increased economic development and urbanisation. In addition to an increasingly westernised diet, the traditional Chinese diet also plays a part, with the quantity and quality of rice intake linked to the risk of type 2 diabetes. Familial factors including inherited genetic variants are important, although differences in the genetic architecture suggest a different combination of genetic variants could be most relevant in Chinese when compared with Europeans. Recent advances have also emphasised the role of early life factors in the epidemic of diabetes and non-communicable diseases: maternal undernutrition, maternal obesity, and gestational diabetes are all linked to increased risk of diabetes in offspring. A mismatch between developmentally programmed biology and the modern environment is relevant for countries like China where there has been rapid economic transformation. Multisectoral efforts to address the risks will be needed at different stages throughout the lifecourse to reduce the burden of diabetes.

The ethnoepidemiology of obesity

The prevalence of overweight and obesity varies significantly across ethnic groups and among aboriginal people in Canada and appears to be increasing overall in children and youth, which will have significant health consequences in the future. Individual health behaviours, genetic predisposition, and community-level factors all contribute to the high burden of overweight and obesity across communities in Canada. Preliminary studies indicate that individuals who live in neighbourhoods in Canada with increased walkability, fewer fast food outlets, and higher socioeconomic status have lower rates of overweight/obesity when compared with other neighbourhoods. However, more research is required to understand the impact of community level factors on overweight/obesity trends in Canadian ethnic groups, including children and youth, and aboriginal people.