Nine things to remember about human genome diversity

Admixture Has Shaped Romani Genetic Diversity in Clinically Relevant Variants

Genetic patterns of inter-population variation are a result of different demographic and adaptive histories, which gradually shape the frequency distribution of the variants. However, the study of clinically relevant mutations has a Eurocentric bias. The Romani, the largest transnational minority ethnic group in Europe, originated in South Asia and received extensive gene flow from West Eurasia. Most medical genetic studies have only explored founder mutations related to Mendelian disorders in this population. Here we analyze exome sequences and genome-wide array data of 89 healthy Spanish Roma individuals to study complex traits and disease. We apply a different framework and focus on variants with both increased and decreased allele frequencies, taking into account their local ancestry. We report several OMIM traits enriched for genes with deleterious variants showing increased frequencies in Roma or in non-Roma (e.g., obesity is enriched in Roma, with an associated variant linked to South Asian ancestry; while non-insulin dependent diabetes is enriched in non-Roma Europeans). In addition, previously reported pathogenic variants also show differences among populations, where some variants segregating at low frequency in non-Roma are virtually absent in the Roma. Lastly, we describe frequency changes in drug-response variation, where many of the variants increased in Roma are clinically associated with metabolic and cardiovascular-related drugs. These results suggest that clinically relevant variation in Roma cannot only be characterized in terms of founder mutations. Instead, we observe frequency differences compared to non-Roma: some variants are absent, while other have drifted to higher frequencies. As a result of the admixture events, these clinically damaging variants can be traced back to both European and South Asian-related ancestries. This can be attributed to a different prevalence of some genetic disorders or to the fact that genetic susceptibility variants are mostly studied in populations of European descent, and can differ in individuals with different ancestries.

Genetic Variants Allegedly Linked to Antisocial Behaviour Are Equally Distributed Across Different Populations

Human behaviour is determined by a complex interaction of genetic and environmental factors. Several studies have demonstrated different associations between human behaviour and numerous genetic variants. In particular, allelic variants in SLC6A4, MAOA, DRD4, and DRD2 showed statistical associations with major depressive disorder, antisocial behaviour, schizophrenia, and bipolar disorder; BDNF polymorphic variants were associated with depressive, bipolar, and schizophrenia diseases, and TPH2 variants were found both in people with unipolar depression and in children with attention deficit-hyperactivity disorder (ADHD). Independent studies have failed to confirm polymorphic variants associated with criminal and aggressive behaviour. In the present study, a set of genetic variants involved in serotoninergic, dopaminergic, and neurobiological pathways were selected from those previously associated with criminal behaviour. The distribution of these genetic variants was compared across worldwide populations. While data on single polymorphic variants showed differential distribution across populations, these differences failed to be significant when a comprehensive analysis was conducted on the total number of published variants. The lack of reproducibility of the genetic association data published to date, the weakness of statistical associations, the heterogeneity of the phenotype, and the massive influence of the environment on human behaviour do not allow us to consider these genetic variants as undoubtedly associated with antisocial behaviour. Moreover, these data confirm the absence of ethnic predisposition to aggressive and criminal behaviour.

Using Anthropological Principles to Transform the Teaching of Human "Difference" and Genetic Variation in College Classrooms

Exposure to information about genetics is at an all-time high, while a full understanding of the biocultural complexity of human difference is low. This paper demonstrates the value of an "anthropological approach" to enhance genetics education in biology, anthropology, and other related disciplines, when teaching about human differences such as race/ethnicity, sex/gender, and disability. As part of this approach, we challenge educators across social and natural sciences to critically examine and dismantle the tacit cultural assumptions that shape our understanding of genetics and inform the way we perceive (and teach about) human differences. It calls on educators from both social and natural science disciplines to "de-silo" their classrooms and uses examples from our biological anthropology and sociocultural anthropology classrooms, to demonstrate how educators can better contextualize the "genetics" of human difference in their own teaching. Numerous opportunities to transform our teaching exist, and we are doing a disservice to our students by not taking these critical steps.

Direct-to-Consumer Genetic Testing's Red Herring: "Genetic Ancestry" and Personalized Medicine

The growth in the direct-to-consumer genetic testing industry poses a number of challenges for healthcare practice, among a number of other areas of concern. Several companies providing this service send their customers reports including information variously referred to as genetic ethnicity, genetic heritage, biogeographic ancestry, and genetic ancestry. In this article, we argue that such information should not be used in healthcare consultations or to assess health risks. Far from representing a move toward personalized medicine, use of this information poses risks both to patients as individuals and to racialized ethnic groups because of the way it misrepresents human genetic diversity.

Human Leukocyte Antigen-A, B, C, DRB1, and DQB1 Allele and Haplotype Frequencies in a Subset of 237 Donors in the South African Bone Marrow Registry

Human leukocyte antigen- (HLA-) A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 allele and haplotype frequencies were studied in a subset of 237 volunteer bone marrow donors registered at the South African Bone Marrow Registry (SABMR). Hapl-o-Mat software was used to compute allele and haplotype frequencies from individuals typed at various resolutions, with some alleles in multiple allele code (MAC) format. Four hundred and thirty-eight HLA-A, 235 HLA-B, 234 HLA-DRB1, 41 HLA-DQB1, and 29 HLA-C alleles are reported. The most frequent alleles were A∗02:02g (0.096), B∗07:02g (0.082), C∗07:02g (0.180), DQB1∗06:02 (0.157), and DRB1∗15:01 (0.072). The most common haplotype was A∗03:01g~B∗07:02g~C∗07:02g~DQB1∗06:02~DRB1∗15:01 (0.067), which has also been reported in other populations. Deviations from Hardy-Weinberg equilibrium were observed in A, B, and DRB1 loci, with C~DQB1 being the only locus pair in linkage disequilibrium. This study describes allele and haplotype frequencies from a subset of donors registered at SABMR, the only active bone marrow donor registry in Africa. Although the sample size was small, our results form a key resource for future population studies, disease association studies, and donor recruitment strategies.

Intersectionality and risk for ischemic heart disease in Sweden: Categorical and anti-categorical approaches

Intersectionality theory can contribute to epidemiology and public health by furthering understanding of power dynamics driving production of health disparities, and increasing knowledge about heterogeneities within, and overlap between, social categories. Drawing on McCall, we relate the first of these potential contributions to categorical intersectionality and the second to anti-categorical intersectionality. Both approaches are used in study of risk of ischemic heart disease (IHD), based on register data on 3.6 million adults residing in Sweden by 2010, followed for three years. Categorical intersectionality is here coupled with between-group differences in average risk calculation, as we use intersectional categorizations while estimating odds ratios through logistic regressions. The anti-categorical approach is operationalized through measurement of discriminatory accuracy (DA), i.e., capacity to accurately categorize individuals with or without a certain outcome, through computation of the area under the curve (AUC). Our results show substantial differences in average risk between intersectional groupings. The DA of social categorizations is found to be low, however, due to outcome variability within and overlap between categories. We argue that measures of DA should be used for proper interpretation of differences in average risk between social (or any other) categories. Tension between average between-group risk and the DA of categorizations, which can be related to categorical and anti-categorical intersectional analyses, should be made explicit and discussed to a larger degree in epidemiology and public health.

Recent advances in the study of fine-scale population structure in humans

Empowered by modern genotyping and large samples, population structure can be accurately described and quantified even when it only explains a fraction of a percent of total genetic variance. This is especially relevant and interesting for humans, where fine-scale population structure can both confound disease-mapping studies and reveal the history of migration and divergence that shaped our species' diversity. Here we review notable recent advances in the detection, use, and understanding of population structure. Our work addresses multiple areas where substantial progress is being made: improved statistics and models for better capturing differentiation, admixture, and the spatial distribution of variation; computational speed-ups that allow methods to scale to modern data; and advances in haplotypic modeling that have wide ranging consequences for the analysis of population structure. We conclude by outlining four important open challenges: the limitations of discrete population models, uncertainty in individual origins, the incorporation of both fine-scale structure and ancient DNA in parametric models, and the development of efficient computational tools, particularly for haplotype-based methods.

The Uromodulin Gene Locus Shows Evidence of Pathogen Adaptation through Human Evolution

Common variants in the UMOD gene encoding uromodulin, associated with risk of hypertension and CKD in the general population, increase UMOD expression and urinary excretion of uromodulin, causing salt-sensitive hypertension and renal lesions. To determine the effect of selective pressure on variant frequency, we investigated the allelic frequency of the lead UMOD variant rs4293393 in 156 human populations, in eight ancient human genomes, and in primate genomes. The T allele of rs4293393, associated with CKD risk, has high frequency in most modern populations and was the one detected in primate genomes. In contrast, we identified only the derived, C allele in Denisovan and Neanderthal genomes. The distribution of the UMOD ancestral allele did not follow the ancestral susceptibility model observed for variants associated with salt-sensitive hypertension. Instead, the global frequencies of the UMOD alleles significantly correlated with pathogen diversity (bacteria, helminths) and prevalence of antibiotic-resistant urinary tract infections (UTIs). The inverse correlation found between urinary levels of uromodulin and markers of UTIs in the general population substantiates the link between UMOD variants and protection against UTIs. These data strongly suggest that the UMOD ancestral allele, driving higher urinary excretion of uromodulin, has been kept at a high frequency because of its protective effect against UTIs.

Personalized Medicine for Sepsis

Sepsis is a complex syndrome triggered by infection and characterized by systemic deregulation of immune and inflammatory pathways. It is a major cause of death worldwide and results in the widespread use of antibiotics and substantial health care costs. In a vicious circle, sepsis treatment promotes the emergence of highly virulent and resistant pathogens and devastating nosocomial infections. Sepsis is a heterogeneous disease affecting many people worldwide. Because individual patients have different inflammatory responses and unique profiles of immune activation against pathogens, the most effective way to advance the treatment of sepsis is probably through a tailored approach. The advent of high-throughput technologies and the remarkable progress in the field of bioinformatics has allowed the subclassification of many pathological conditions. This has potential to provide better understanding of life-threatening infections in people. The study of host factors, however, needs to be integrated with studies on bacterial signaling in both symbiotic and pathogenic bacteria. Sepsis is certainly the sum of multiple host-microbial interactions and the metagenome should be extensively investigated. Personalized medicine is probably the only strategy able to deconstruct and reassemble our knowledge about sepsis, and its use should allow us to understand and manipulate sepsis as a wide, interconnected phenomenon with myriad variables and peculiarities. In this study, the recent advances in this area, the major challenges that remain, and the reasons why the septic patient should be approached as a superorganism are discussed.

A reconsideration of the role of self-identified races in epidemiology and biomedical research

A considerable number of studies in epidemiology and biomedicine investigate the etiology of complex diseases by considering (self-identified) race as a relevant variable and focusing on the differences in risk among racial groups in the United States; they extensively draw on a genetic hypothesis--viz. the hypothesis that differences in the risk of complex diseases among racial groups are largely due to genetic differences covarying with genetic ancestry--that appears highly problematic in the light of both current biological evidence and the theory of human genome evolution. Is this reason for dismissing self-identified races? No. An alternative promising use of self-identified races exists, and ironically is suggested by those studies that investigate the etiology of complex diseases without focusing on racial differences. These studies provide a large amount of empirical evidence supporting the primacy of the contribution of non-genetic as opposed to genetic factors to the risk of complex diseases. We show that differences in race--or, better, in racial self-identification--may be critically used as proxies for differences in risk-related exposomes and epigenomes in the context of the United States. Self-identified race is what we need to capture the complexity of the effects of present and past racism on people's health and investigate risk-related external and internal exposures, gene-environment interactions, and epigenetic events. In fact patterns of racial self-identifications on one side, and patterns of risk-related exposomes and epigenomes on the other side, constantly coevolve and tend to match each other. However, there is no guarantee that using self-identified races in epidemiology and biomedical research will be beneficial all things considered: special attention must be paid at balancing positive and negative consequences.

Implications of the apportionment of human genetic diversity for the apportionment of human phenotypic diversity

Researchers in many fields have considered the meaning of two results about genetic variation for concepts of "race." First, at most genetic loci, apportionments of human genetic diversity find that worldwide populations are genetically similar. Second, when multiple genetic loci are examined, it is possible to distinguish people with ancestry from different geographical regions. These two results raise an important question about human phenotypic diversity: To what extent do populations typically differ on phenotypes determined by multiple genetic loci? It might be expected that such phenotypes follow the pattern of similarity observed at individual loci. Alternatively, because they have a multilocus genetic architecture, they might follow the pattern of greater differentiation suggested by multilocus ancestry inference. To address the question, we extend a well-known classification model of Edwards (2003) by adding a selectively neutral quantitative trait. Using the extended model, we show, in line with previous work in quantitative genetics, that regardless of how many genetic loci influence the trait, one neutral trait is approximately as informative about ancestry as a single genetic locus. The results support the relevance of single-locus genetic-diversity partitioning for predictions about phenotypic diversity.

Questioning the discriminatory accuracy of broad migrant categories in public health: self-rated health in Sweden

Background: Differences between natives and migrants in average risk for poor self-rated health (SRH) are well documented, which has lent support to proposals for interventions targeting disadvantaged minority groups. However, such proposals are based on measures of association that neglect individual heterogeneity around group averages and thereby the discriminatory accuracy (DA) of the categories used (i.e. their ability to discriminate the individuals with poor and good SRH, respectively). Therefore, applying DA measures rather than only measures of association our study revisits the value of broad native and migrant categorizations for predicting SRH. Design, setting and participants: We analyzed 27 723 individuals aged 18–80 who responded to a 2008 Swedish public health survey. We performed logistic regressions to estimate odds ratios (ORs), predicted risks and the area under the receiver operating characteristic curve (AU-ROC) as a measure of epidemiological DA. Results: Being born abroad was associated with higher odds of poor SRH (OR = 1.75), but the AU-ROC of this variable only added 0.02 units to the AU-ROC for age alone (from 0.53 to 0.55). The AU-ROC increased, but remained unsatisfactorily low (0.62), when available social and demographic variables were included. Conclusions: Our results question the use of broad native/migrant categorizations as instruments for forecasting individual SRH. Such simple categorizations have a very low DA and should be abandoned in public health practice. Measures of association and DA should be reported together whenever an intervention is being considered, especially in the area of ethnicity, migration and health.

Confidentiality and data sharing: vulnerabilities of the Mexican Genomics Sovereignty Act

A law known as "Genomic Sovereignty Act", instituted in 2011, regulates research on the human genome in Mexico. This law establishes Government regulations for the exportation of DNA samples from Mexican nationals for population genetics studies. The Genomic Sovereignty Act protects fundamental human values, as confidentiality and non-discrimination based on personal genetic information. It also supports the development of the genome-based medical biotechnology and the bio-economy. Current laws for the protection of the genomic confidentiality, however, are inexplicit and insufficient, and the legal and technological instruments are primitive and insufficient to safeguard this bioethical principle. In addition, this law may undermine efforts of the national and international scientific communities to cooperate with big-data analysis for the development of the genome-based biomedical sciences. The argument of this article is that deficiencies in the protection of the confidentiality of genomic information and limitations in data sharing severely weaken the objectives and scope of the Genomic Sovereignty Act. In addition, the Act may compromise the national biomedical development and the international cooperation for research and development in the field of human genomics.

Women who deliver twins are more likely to smoke and have high frequencies of specific SNPs: Results from a sample of African-American women who delivered preterm, low birth weight babies

OBJECTIVES

We examine if there are genetic and environmental differences between mothers of singleton and multiple pregnancies in a sample of African-American mothers.

METHODS

We focus on genomic areas suggested to increase or decrease the odds of multiple pregnancies. We computed the odds ratio (OR) and the 95% confidence interval (CI) for each SNP unadjusted or adjusted with smoking. SNPs' allelic differences between mothers of multiple pregnancies and singletons were also tested using Fisher's exact test. We considered additive terms for the SNPs' genotypes, smoking, and a multiplicative interaction term of two selected SNPs' genotypes.

RESULTS

We found significant interactions between smoking and SNPs of the CYP19A, MDM4, MTHFR and TP53 genes which correlated with higher odds of twinning. We also found a significant interaction between SNPs at the TP53 (rs8079544) and MTHFR gene (rs4846049), where the interaction between the homozygotes (TT for rs8079544, GG for rs4846049) correlated with lowered odds of multiple pregnancy.

CONCLUSIONS

We provide a mechanistic explanation and preliminary evidence for previous reports that mothers of twins are more likely to have smoked, despite seemingly conflicting evidence for the fertility-reducing effects of nicotine. Nicotine, as an aromatase inhibitor, inhibits estrogen synthesis and may allow for greater production of gonadotropins. While smoking may have deleterious effects on fertility across many genotypes, in women of specific genotypes it may raise their odds of producing twins. TP53 involvement suggests the necessity of future work examining relationships between women who bear multiples and cancer risk.