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

Loh, Marie; Zhang, Weihua; Ng, Hong Kiat; Schmid, Katharina; Lamri, Amel; Lin, Tong; Ahmad, Meraj; Lee, Jung‐Jin; Ng, Maggie C. Y.; Petty, Lauren E.; Spracklen, Cassandra N.; Takeuchi, Fumihiko; Islam, Md. Tariqul; Jasmine, Farzana; Kasturiratne, Anuradhani; Kibriya, Muhammad G.; Mohlke, Karen L.; Paré, Guillaume; Prasad, Gauri; Shahriar, Mohammad Hasan; Chee, Miao Ling; Silva, H Janaka de; Engert, James C.; Gerstein, Hertzel C.; Mani, K. Radha; Sabanayagam, Charumathi; Vujkovic, Marijana; Wickremasinghe, Rajitha; Wong, Tien Yin; Yajnik, Chittaranjan S; Yusuf, Salim; Ahsan, Habibul; Bharadwaj, Dwaipayan; Anand, Sonia S.; Below, Jennifer E.; Boehnke, Michael; Bowden, Donald W.; Chandak, Giriraj R; Cheng, Ching‐Yu; Kato, Norihiro; Sim, Xueling; McCarthy, Mark; Morris, Andrew P.; Kooner, Jaspal S.; Saleheen, Danish; Chambers, John C.

doi:10.1038/s42003-022-03248-5

Cited by 28 publications

(22 citation statements)

References 98 publications

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“…The datasets for the genome-wide association studies (GWASs) summary statistics used in this analysis were from the GWAS Catalog (available at , accessed on 19 July 2022). GWAS data on BMI and dyslipidemia were adopted from Biobank Japan (BBJ, n = 179,000) for the East Asian population [ 24 ], while T2D GWAS data from 50,533 samples (16,677 cases and 33,856 controls) were collected from a DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) project for a South Asian population [ 25 ]. The datasets for summary statistics are described in detail in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

Causal Association of Obesity and Dyslipidemia with Type 2 Diabetes: A Two-Sample Mendelian Randomization Study

Lee

Kim

Seo

2022

Genes

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Recent studies have suggested an association between obesity and dyslipidemia in the development of type 2 diabetes (T2D). The purpose of this study was to explore the causal effects of obesity and dyslipidemia on T2D risk in Asians. Two-sample Mendelian randomization (MR) analyses were performed to assess genetically predicted obesity using body mass index (BMI) and dyslipidemia using high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TCHL), and triglycerides (TG) versus T2D susceptibility using genome-wide association study (GWAS) results derived from the summary statistics of Biobank Japan (n = 179,000) and DIAbetes Meta-ANalysis of Trans-Ethnic association studies (n = 50,533). The MR analysis demonstrated evidence of a causal effect of higher BMI on the risk of T2D (odds ratio (OR) > 1.0, p < 0.05). In addition, TG showed a protective effect on the risk of T2D (ORs 0.68–0.85). However, HDL, LDL, and TCHL showed little genetic evidence supporting a causal association between dyslipidemia and T2D. We found strong genetic evidence supporting a causal association of BMI with T2D. Although HDL, LDL, and TCHL did not show a causal association with T2D, TG had a causal relationship with the decrease of T2D. Although it was predicted that TG would be linked to a higher risk of T2D, it actually exhibited a paradoxical protective effect against T2D, which requires further investigation.

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Section: Methodsmentioning

confidence: 99%

Causal Association of Obesity and Dyslipidemia with Type 2 Diabetes: A Two-Sample Mendelian Randomization Study

Lee

Kim

Seo

2022

Genes

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“…Additional evidence has found that the Roma people have no increased genetic susceptibility to diabetes compared with the general population [119]. This finding contrasts with the South Asian populations, which has a known genetic predisposition to diabetes [80].…”

Section: A Pre-colonial South Asian Historical Control Populationmentioning

confidence: 96%

“…Furthermore, at least six genetic variants associated with the premature onset of insulin-resistant diabetes have been found to be much more prevalent in South Asians than in Europeans [79]. Another study suggested that based on genetic data (polygenic risk score), South Asians had about a four times higher risk of type 2 diabetes than the European population [80]. South Asians have a higher postprandial insulin response, with a higher tendency toward insulin resistance in the overfed state (Figures 1 and 2) and there is a three-to four-fold higher prevalence of insulin resistance in lean South Asian men than in lean men of other ethnic groups [81,82].…”

Section: Greater Insulin Resistance/insulin Responsementioning

confidence: 99%

The Susceptibility of South Asians to Cardiometabolic Disease as a Result of Starvation Adaptation Exacerbated During the Colonial Famines

2022

Endocrinol Diabetes Metab J

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South Asians, representing one quarter of the world's population, have disproportionally high rates of obesity and cardiometabolic disease thus resulting an epidemic health crisis. This crisis could be the consequence of epigenetic effects exacerbated during the colonial-era famines resulting in a unique starvation-adapted physiology. Due to evolutionary mismatch in circumstances of abundance, this starvation-adapted physiology can become harmful. Evidence for this starvation adaptation in South Asians includes high body fat and unfavorable adipokines; low lean body mass; lower resting energy expenditure (compounded by lack of brown adipose tissue); greater insulin resistance and insulin response; exaggerated lipemic response to fat and sugar intake; less capacity to handle an overabundance of food; lower fat burning (oxidative capacity) and VO2max during aerobic exercise; and energyconserving response to resistance exercise, as well as increased lipoprotein (a) levels. The Roma people, also of South Asian ancestry, may represent an interesting pre-colonial historical control. Physician and patient knowledge of this unique physiology in South Asians will promote a stronger physicianpatient relationship and foster compliance with treatment.

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“…Pathogenesis of DN depends on genetic factors as well and genetically susceptible individuals can develop DN after environmental interaction DN is a complex, polygenic disease. For the identification of associated genes for the development of DN, two main strategies have been used which include analysis of candidate genes and more recently genome-wide scan [37].…”

Section: Genetic Susceptibilitymentioning

confidence: 99%

The Risk for the Development of Diabetic Nephropathy: Interplay of Biochemical, Genetic, Nutritional and Lifestyle Factors

Shahid¹,

Jawed²

2024

Novel Topics in the Diagnosis, Treatment, and Follow-Up of Nephritis, Nephrotic Syndrome, and Nephrosis

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The recent unprecedented pandemic COVID-19 has blatantly exposed the healthcare system globally. The increasing rate of mortality and morbidity/co-morbidity were observed due to an interplay of COVID-19 infection with chronic diseases like diabetes, cancers, CVDs, respiratory and mental illness. According to World Health Organization, diabetes kills 1.7 million people annually. The prevalence and incidence of diabetes mellitus, representing >90% of all cases of diabetes and its complications, are increasing rapidly. The International Diabetes Federation has estimated that the number of people with diabetes is expected to rise from 366 million in 2011 to 552 million by 2030 if no urgent action is taken. Diabetes is a leading cause of kidney disease. About one in three adult diabetic patients has kidney disease, that is, diabetic nephropathy. In search for the risk and causes of diabetes and its complications such as diabetic nephropathy, research has now advanced to the molecular level. Genetics, epigenetics, genomics, proteomics, and metabolomics are opening ways to a new and deeper understanding of bodily processes and are providing the tools for more precisely targeted interventions when their function is disturbed. Similarly, tobacco use, physical inactivity, the harmful use of alcohol, and unhealthy diets all increase the risk of developing diabetic nephropathy. This chapter will focus on analyzing recently researched and published biochemical, genetic, nutritional, and lifestyle factors in various populations to ascertain the interplay of a wide variety of modifiable and non-modifiable factors, which will help delay and/or prevent the development of kidney disease in diabetes.

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

Cited by 28 publications

References 98 publications

Causal Association of Obesity and Dyslipidemia with Type 2 Diabetes: A Two-Sample Mendelian Randomization Study

Causal Association of Obesity and Dyslipidemia with Type 2 Diabetes: A Two-Sample Mendelian Randomization Study

The Susceptibility of South Asians to Cardiometabolic Disease as a Result of Starvation Adaptation Exacerbated During the Colonial Famines

The Risk for the Development of Diabetic Nephropathy: Interplay of Biochemical, Genetic, Nutritional and Lifestyle Factors

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