This review explores the limitations of self-reported race, ethnicity, and genetic ancestry in biomedical research. Various terminologies are used to classify human differences in genomic research including race, ethnicity, and ancestry. Although race and ethnicity are related, race refers to a person’s physical appearance, such as skin color and eye color. Ethnicity, on the other hand, refers to communality in cultural heritage, language, social practice, traditions, and geopolitical factors. Genetic ancestry inferred using ancestry informative markers (AIMs) is based on genetic/genomic data. Phenotype-based race/ethnicity information and data computed using AIMs often disagree. For example, self-reporting African Americans can have drastically different levels of African or European ancestry. Genetic analysis of individual ancestry shows that some self-identified African Americans have up to 99% of European ancestry, whereas some self-identified European Americans have substantial admixture from African ancestry. Similarly, African ancestry in the Latino population varies between 3% in Mexican Americans to 16% in Puerto Ricans. The implication of this is that, in African American or Latino populations, self-reported ancestry may not be as accurate as direct assessment of individual genomic information in predicting treatment outcomes. To better understand human genetic variation in the context of health disparities, we suggest using “ancestry” (or biogeographical ancestry) to describe actual genetic variation, “race” to describe health disparity in societies characterized by racial categories, and “ethnicity” to describe traditions, lifestyle, diet, and values. We also suggest using ancestry informative markers for precise characterization of individuals’ biological ancestry. Understanding the sources of human genetic variation and the causes of health disparities could lead to interventions that would improve the health of all individuals.

/pdf/self-reported-race-ethnicity-in-the-age-of-genomic-research-5c52di3tf2.pdf

Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities

https://link.springer.com/content/pdf/10.1007%2Fs13311-018-0616-5.pdf

Glutamate and Its Receptors as Therapeutic Targets for Migraine

Polynesia consists of several islands that are scattered across a vast triangle in the Pacific, and include New Zealand, Hawaii, and the Pacific islands. There are reported differences in the types of cancer and epidemiologies seen among communities in these islands, the reasons for which are diverse and complex. In this Review, we describe patterns of cancer incidence, mortality, and survival in indigenous populations compared with populations of European origin in Polynesia, and highlight the limited available data for Pacific populations. Additionally, we document the current knowledge of the underlying biology of cancers in these populations, and report risk factors that differ between ethnicities, including smoking, viral infections, and obesity. Disparities in measures of health are highlighted, as are evident differences in knowledge of tumour biology and cancer management between majority and minority populations.

https://www.thelancet.com/pdfs/journals/lanonc/PIIS1470-2045(08)70127-X.pdf

Cancer disparities in indigenous Polynesian populations: Māori, Native Hawaiians, and Pacific people

// Marta Kowalska 1 , Michal Prendecki 1 , Wojciech Kozubski 2 , Margarita Lianeri 1 and Jolanta Dorszewska 1 1 Laboratory of Neurobiology, Department of Neurology, Poznan University of Medical Sciences, Poznan, Poland 2 Chair and Department of Neurology, Poznan University of Medical Sciences, Poznan, Poland Correspondence to: Jolanta Dorszewska, email: // Keywords : gene polymorphisms, biochemical factors, migraine Received : October 07, 2015 Accepted : May 05, 2016 Published : May 14, 2016 Abstract Migraine is a common neurological disorder that affects 11% of adults worldwide. This disease most likely has a neurovascular origin. Migraine with aura (MA) and more common form - migraine without aura (MO) – are the two main clinical subtypes of disease. The exact pathomechanism of migraine is still unknown, but it is thought that both genetic and environmental factors are involved in this pathological process. The first genetic studies of migraine were focused on the rare subtype of MA: familial hemiplegic migraine (FHM). The genes analysed in familial and sporadic migraine are: MTHFR , KCNK18 , HCRTR1, SLC6A4, STX1A , GRIA1 and GRIA3 . It is possible that migraine is a multifactorial disease with polygenic influence. Recent studies have shown that the pathomechanisms of migraine involves both factors responsible for immune response and oxidative stress such as: cytokines, tyrosine metabolism, homocysteine; and factors associated with pain transmission and emotions e.g.: serotonin, hypocretin-1, calcitonin gene-related peptide, glutamate. The correlations between genetic variants of the HCRTR1 gene, the polymorphism 5-HTTLPR and hypocretin-1, and serotonin were observed. It is known that serotonin inhibits the activity of hypocretin neurons and may affect the appearance of the aura during migraine attack. The understanding of the molecular mechanisms of migraine, including genotype-phenotype correlations, may contribute to finding markers important for the diagnosis and treatment of this disease.

/pdf/molecular-factors-in-migraine-4em9xbiz17.pdf

Molecular factors in migraine

Publisher Summary
This chapter gives an account of Nutrigenomics, which plays an important role in integrating genomic approaches into nutrition research. Nutrigenomics (sometimes called nutritional genomics) considers the interactions between foods or dietary supplements and an individual's genome and the consequent downstream effects on their phenotype. It offers a multi-level systems biology model that is both flexible and rigorous. Some newer tools provide a sensitivity that has been previously lacking. The Nutrigenomics New Zealand model provides an approach towards personalized, genotype-based nutrition that has the potential to provide food products and personalized advice to benefit health at the individual or population level. There is convincing evidence that single nucleotide polymorphisms (SNPs) in certain genes may profoundly influence the biological response to nutrients. However, effects of single-gene variants on risk or risk factor levels of a complex disease tend to be small and inconsistent. Increased sensitivity of current biological measurements and methods of integrating information on combinations of relevant SNPs or copy-number variants in different genes have become necessary to move the field to a higher dimension. There are only sporadic examples of clinical trials utilizing these technologies and many of the challenges are in bioinformatics, especially in relation to reducing the complexity of multidimensional data sets.

Chapter 23 – Nutrigenomics: Integrating Genomic Approaches into Nutrition Research

Aims To estimate (a) the prevalence of gene variants associated with slow nicotine metabolism in the general Maori population and (b) nicotine intake and metabolic rate in Maori and European smokers. Methods The procedure involved (a) genotyping 85 Maori participants for cytochrome P-450 2A6 (CYP2A6) gene variants, which are associated with reduced nicotine metabolic rate (ie CYP2A6*9 and *4); and (b) measuring salivary cotinine (COT) and trans-3'-hydroxycotinine (3-HC) as biomarkers of nicotine intake and metabolic rate in 12 female smokers from the Hawke's Bay Region (6 Maori and 6 European). Results (a) The frequencies of the slow nicotine metabolising variants, CYP2A6*9 and *4, were significantly higher in Maori compared to European (p<0.01). Indeed, the prevalence of the CYP2A6*9 variant in these Maori was among the highest in the world (~20%). (b) In smokers, the Maori group had ~35% lower 3-HC:COT ratios indicating a reduced metabolic rate, as well as 2-fold lower cotinine levels per cigarette smoked, indicating reduced nicotine intake (p<0.05). The CYP2A6*9 allele was significantly more frequent in Maori smokers (70%) compared to Europeans (30%), p=0.03. Conclusions The findings of this study provide evidence that Maori are genetically slower nicotine metabolisers compared to Europeans. Although more research is required, this study may help explain ethnic differences in smoking initiation and may also have important implications for smoking cessation programs—since metabolic differences between groups with varying ancestry implies that different optimal dosages of nicotine replacement therapy may be required for successful quitting. In New Zealand (NZ), the prevalence of cigarette smoking is around 22% for the general population. However the smoking rates are markedly higher for Maori (~46%) compared to Europeans (20%) and, for reasons that are unclear, the rates for female Maori are among the highest in the world—52% nationally and up to 60% in some regions. 1 Extensive targeted campaigns for smoking cessation in the 1990s has led to a reduction in tobacco consumption in NZ, yet the high prevalence of smoking for Maori has not decreased. 1 High rates of smoking are associated with elevated rates of smoking-related diseases, and it has been estimated that smoking is responsible for around 30% of Maori deaths compared to about 17% nationally. 2 As these statistics emphasise, identifying the determinants of the high smoking prevalence in Maori and using this information to develop new targeted cessation strategies is of major public health importance in NZ.

Ethnic differences in nicotine metabolic rate among New Zealanders

Background.—The excitatory neurotransmitter glutamate has been implicated in both the hyperexcitability required for cortical spreading depression as well as activation of the trigeminovascular system required for the allodynia associated with migraine. Polymorphisms in the glutamate receptor ionotropic amino-3-hydroxy-5-methyl-4-isoxazole-propionin acid 1 (GRIA1) and GRIA3 genes that code for 2 of 4 subunits of the glutamate receptor have been previously associated with migraine in an Italian population. In addition, the GRIA3 gene is coded within a previously identified migraine susceptibility locus at Xq24. This study investigated the previously associated polymorphisms in both genes in an Australian case-control population. Methods.—Variants in GRIA1 and GRIA3 were genotyped in 472 unrelated migraine cases and matched controls, and data were analyzed for association. Results.—Analysis showed no association between migraine and the GRIA1 gene. However, association was observed with the GRIA3 single nucleotide polymorphism (SNP) rs3761555 (P = .008). Conclusion.—The results of this study confirmed the previous report of association at the rs3761555 SNP within the migraine with aura subgroup of migraineurs. However, the study identified association with the inverse allele suggesting that rs3761555 may not be the causative SNP but is more likely in linkage disequilibrium with another causal variant in both populations. This study supports the plethora of evidence suggesting that glutamate dysfunction may contribute to migraine susceptibility, warranting further investigation of the glutamatergic system and particularly of the GRIA3 gene.

Research Submissions Association of a GRIA3 Gene Polymorphism With Migraine in an Australian Case-Control Cohort

Title : Identification of a novel mutation C144F in the Notch3 gene in an Australian CADASIL pedigree

Mutation and Polymorphism Report

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Ethnic differences in nicotine metabolic rate among New Zealanders

Research Submissions Association of a GRIA3 Gene Polymorphism With Migraine in an Australian Case-Control Cohort

Mutation and Polymorphism Report