2.b.v. Lyme Endemic to Non-Lyme Endemic Comparisons
Rather than using geopolitical boundaries, it is also possible to view
the data relative to the 95% human Lyme disease kernel, a proxy forB. burgdorferi s.s. prevalence. Overall, populations close to or
within the Lyme disease kernel were more closely related than
populations more distant from the kernel. For example, the populations
in North Carolina and Tennessee are within the Southeastern region, with
Stokes County, NC falling within the Lyme endemic region and Watauga
County, NC and Claiborne County, TN just outside the Lyme disease
kernel. All three, however, are within or extremely close to the genetic
cluster containing all populations within the Lyme Disease kernel,
irrespective of their distance to them (Figs. 2, 3). Alternatively, the
Missouri population is in the Northern geographic area, but is well
outside the Lyme disease kernel, with the genetic cluster for Missouri
also well away from all other Northern populations (which are inside the
Lyme disease kernel; Figs. 2, 3). This leads to the hypothesis that the
genetic differentiation occurring throughout the landscape likely is not
solely geographically driven, but instead is correlated with B.
burgdorferi s.s. prevalence. Thus, the information presented herein may
be used to redraw boundaries between genetically distinct groups ofI. scapularis , relationships that seem to be correlated with
human Lyme disease. Further work in this area is obviously warranted.