Geographic Distribution of Disease Mutations in the Ashkenazi Jewish Population Supports Genetic Drift over Selection

Risch, Neil; Tang, Hua; Katzenstein, Howard M.; Ekstein, Josef

doi:10.1086/373882

Cited by 127 publications

(120 citation statements)

References 39 publications

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“…The particular identifier used (language, ethnicity, geographic origin, religion) will depend on the particular study and the hypotheses being tested. For example, use of religion as a descriptor will be important if discussing diseases prevalent in Jewish populations, which may result from genetic drift due to founder effect 68 (e.g., Tay Sachs, Torsion dystonia, breast cancer and Gaucher disease).…”

Section: Biomedical Implicationsmentioning

confidence: 99%

Implications of biogeography of human populations for 'race' and medicine

2004

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In this review, we focus on the biogeographical distribution of genetic variation and address whether or not populations cluster according to the popular concept of 'race'. We show that racial classifications are inadequate descriptors of the distribution of genetic variation in our species. Although populations do cluster by broad geographic regions, which generally correspond to socially recognized races, the distribution of genetic variation is quasicontinuous in clinal patterns related to geography. The broad global pattern reflects the accumulation of genetic drift associated with a recent African origin of modern humans, followed by expansion out of Africa and across the rest of the globe. Because disease genes may be geographically restricted due to mutation, genetic drift, migration and natural selection, knowledge of individual ancestry will be important for biomedical studies. Identifiers based on race will often be insufficient.

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Section: Biomedical Implicationsmentioning

confidence: 99%

Implications of biogeography of human populations for 'race' and medicine

2004

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“…First, inferring the coalescence times and the number of ancient lineages of a contemporary sample or population helps to elucidate ancient demographic history, including population admixture, migration, and founder effect. It can also provide insights into medical studies regarding the origin and genetic architecture of inherited diseases in different populations, as well as to ecological studies, for example, on investigating the process of species invasion (Risch et al 2003;Anderson and Slatkin 2007;Dlugosch and Parker 2007). Second, the distributions of coalescence times and ancestral lineage numbers are the essential components needed to construct a coalescent likelihood, for example, in the allele frequency spectrum-based approaches (Tavaré 1984;Griffiths and Tavaré 1998;Chen 2012).…”

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confidence: 99%

Asymptotic Distributions of Coalescence Times and Ancestral Lineage Numbers for Populations with Temporally Varying Size

Chen

2013

Genetics

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The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic distributions, which were derived in Griffiths (1984) for populations with constant size. In this article, we derive the asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size. For a sample of size n, denote by T m the mth coalescent time, when m + 1 lineages coalesce into m lineages, and A n (t) the number of ancestral lineages at time t back from the current generation. Similar to the results in Griffiths (1984), the number of ancestral lineages, A n (t), and the coalescence times, T m , are asymptotically normal, with the mean and variance of these distributions depending on the population size function, N(t). At the very early stage of the coalescent, when t / 0, the number of coalesced lineages n 2 A n (t) follows a Poisson distribution, and as m / n, nðn 2 1ÞT m =2Nð0Þ follows a gamma distribution. We demonstrate the accuracy of the asymptotic approximations by comparing to both exact distributions and coalescent simulations. Several applications of the theoretical results are also shown: deriving statistics related to the properties of gene genealogies, such as the time to the most recent common ancestor (TMRCA) and the total branch length (TBL) of the genealogy, and deriving the allele frequency spectrum for large genealogies. With the advent of genomic-level sequencing data for large samples, the asymptotic distributions are expected to have wide applications in theoretical and methodological development for population genetic inference. COALESCENT theory provides a fundamental framework for stochastic modeling and likelihood inference in population genetic studies (Griffiths 1980;Kingman 1982a;Hudson 1990;Nordborg 2001). A coalescent process can be decomposed into two independent processes: the topology of the gene genealogy and the sequential process of intercoalescence times (Kingman 1982a). In this article, we aim to investigate the latter process and two important random quantities associated with this process: the coalescence times and the number of ancestral lineages (Kingman 1982a). Studying the two quantities is both biologically and theoretically meaningful. First, inferring the coalescence times and the number of ancient lineages of a contemporary sample or population helps to elucidate ancient demographic history, including population admixture, migration, and founder effect. It can also provide insights into medical studies regarding the origin and genetic architecture of inherited diseases in different populations, as well as to ecological studies, for example, on investigating the process of species invasion (Risch et al. 2003;...

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“…5 Nevertheless, differential distribution of disease-causingmutations among Ashkenazi Jews of Eastern European versus Central European ancestry suggests genetic drift and may thus imply possible population substructures among Ashkenazi Jews. 6 This consideration is particularly crucial when association studies are performed with the common disease variant approach, as the prevalence of the diseaseassociated variant may vary among populations owing to genetic drift. 4 Indeed, during an association study on type II diabetes mellitus and its complications recently conducted by our group, we found a significant difference in the distribution of linked sets of mitochondrial DNA (mtDNA) common variants (haplogroups) in Ashkenazi Jews of different geographic origins (Feder et al, 2007, submitted).…”

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confidence: 99%

Ashkenazi Jewish mtDNA haplogroup distribution varies among distinct subpopulations: lessons of population substructure in a closed group

et al. 2007

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The quest for genes associated with diseases is widely recognized as an essential task in the effort to investigate the genetic basis of complex human disorders and traits. A basic stage in association studies is the careful choice of the model population, with preference to closed groups having little population substructure. Here, we show evidence for significant geographic substructure (P ¼ 0.017) of the maternal lineage represented by mitochondrial DNA variation in one of the most commonly studied populations, the Ashkenazi Jews. Most of the substructure effect stems from differential representation of haplogroups K and H. Our results underline the essentiality of adjusting data of population genetic variation for substructure during the design of association studies, even in apparently closed populations.

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Geographic Distribution of Disease Mutations in the Ashkenazi Jewish Population Supports Genetic Drift over Selection

Cited by 127 publications

References 39 publications

Implications of biogeography of human populations for 'race' and medicine

Implications of biogeography of human populations for 'race' and medicine

Asymptotic Distributions of Coalescence Times and Ancestral Lineage Numbers for Populations with Temporally Varying Size

Ashkenazi Jewish mtDNA haplogroup distribution varies among distinct subpopulations: lessons of population substructure in a closed group

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