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1.
Clin Exp Rheumatol ; 33(6 Suppl 94): S60-6, 2015.
Article in English | MEDLINE | ID: mdl-26394376

ABSTRACT

OBJECTIVES: Behçet's disease is a multifactorial vasculitis that shows its highest prevalence in geographical areas historically involved in the Silk Road, suggesting that it might have originated somewhere along these ancient trade routes. This study aims to provide a first clue towards genetic evidence for this hypothesis by testing it via an anthropological evolutionary genetics approach. METHODS: Behçet's disease variation at ancestry informative mitochondrial DNA control region and haplogroup diagnostic sites was characterised in 185 disease subjects of Italian descent and set into the Eurasian mitochondrial landscape by comparison with nearly 9,000 sequences representative of diversity observable in Italy and along the main Silk Road routes. RESULTS: Dissection of the actual genetic ancestry of disease individuals by means of population structure, spatial autocorrelation and haplogroup analyses revealed their closer relationships with some Middle Eastern and Central Asian groups settled along the Silk Road than with healthy Italians. CONCLUSIONS: These findings support the hypothesis that the Behçet's disease genetic risk has migrated to western Eurasia in parallel with ancestry components typical of Silk Road-related groups. This provided new insights that are useful to improve the understanding of disease origins and diffusion, as well as to inform future association studies aimed at properly accounting for the actual genetic ancestry of the examined Behçet's disease samples in order to minimise the detection of spurious associations and to improve the identification of genetic variants with actual clinical relevance.


Subject(s)
Asian People/genetics , Behcet Syndrome/genetics , Commerce , DNA, Mitochondrial/genetics , Evolution, Molecular , Genetic Markers , Silk , White People/genetics , Asia/ethnology , Behcet Syndrome/diagnosis , Behcet Syndrome/epidemiology , Cluster Analysis , Genetic Predisposition to Disease , Genetics, Population , Haplotypes , Humans , Italy/epidemiology , Pedigree , Phenotype , Risk Factors , Sequence Analysis, DNA , Silk/economics , Topography, Medical
2.
Am J Phys Anthropol ; 155(4): 600-9, 2014 Dec.
Article in English | MEDLINE | ID: mdl-25229359

ABSTRACT

The Yanesha are a Peruvian population who inhabit an environment transitional between the Andes and Amazonia. They present cultural traits characteristic of both regions, including in the language they speak: Yanesha belongs to the Arawak language family (which very likely originated in the Amazon/Orinoco lowlands), but has been strongly influenced by Quechua, the most widespread language family of the Andes. Given their location and cultural make-up, the Yanesha make for an ideal case study for investigating language and population dynamics across the Andes-Amazonia divide. In this study, we analyze data from high and mid-altitude Yanesha villages, both Y chromosome (17 STRs and 16 SNPs diagnostic for assigning haplogroups) and mtDNA data (control region sequences and 3 SNPs and one INDEL diagnostic for assigning haplogroups). We uncover sex-biased genetic trends that probably arose in different stages: first, a male-biased gene flow from Andean regions, genetically consistent with highland Quechua-speakers and probably dating back to Inca expansion; and second, traces of European contact consistent with Y chromosome lineages from Italy and Tyrol, in line with historically documented migrations. Most research in the history, archaeology and linguistics of South America has long been characterized by perceptions of a sharp divide between the Andes and Amazonia; our results serve as a clear case-study confirming demographic flows across that 'divide'.


Subject(s)
Chromosomes, Human, Y/genetics , DNA, Mitochondrial/genetics , Ethnicity/genetics , Indians, South American/genetics , Ethnicity/ethnology , Genotype , Haplotypes , Humans , Indians, South American/ethnology , Language , Male , Microsatellite Repeats/genetics , Polymorphism, Single Nucleotide/genetics , South America
3.
PLoS One ; 8(5): e65441, 2013.
Article in English | MEDLINE | ID: mdl-23734255

ABSTRACT

Located in the center of the Mediterranean landscape and with an extensive coastal line, the territory of what is today Italy has played an important role in the history of human settlements and movements of Southern Europe and the Mediterranean Basin. Populated since Paleolithic times, the complexity of human movements during the Neolithic, the Metal Ages and the most recent history of the two last millennia (involving the overlapping of different cultural and demic strata) has shaped the pattern of the modern Italian genetic structure. With the aim of disentangling this pattern and understanding which processes more importantly shaped the distribution of diversity, we have analyzed the uniparentally-inherited markers in ∼900 individuals from an extensive sampling across the Italian peninsula, Sardinia and Sicily. Spatial PCAs and DAPCs revealed a sex-biased pattern indicating different demographic histories for males and females. Besides the genetic outlier position of Sardinians, a North West-South East Y-chromosome structure is found in continental Italy. Such structure is in agreement with recent archeological syntheses indicating two independent and parallel processes of Neolithisation. In addition, date estimates pinpoint the importance of the cultural and demographic events during the late Neolithic and Metal Ages. On the other hand, mitochondrial diversity is distributed more homogeneously in agreement with older population events that might be related to the presence of an Italian Refugium during the last glacial period in Europe.


Subject(s)
Chromosomes, Human, Y/genetics , DNA, Mitochondrial/genetics , Genetic Variation , Genetics, Population/methods , Chromosomes, Human, Y/classification , Cluster Analysis , DNA, Mitochondrial/classification , Female , Geography , Haplotypes/genetics , Humans , Italy , Male , Phylogeny , Principal Component Analysis , Time Factors
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