Effect of simulated reversal of anticoagulation.

<p>The simulated anticoagulation condition (<i>τ</i> = 13) was abruptly switched to simulated normal coagulation (<i>τ</i> = 9) at the time points indicated on the x-axis during the course of hemorrhage expansion. Simulations were otherwise performed as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048458#pone-0048458-t001" target="_blank">Table 1</a>.</p

Analysis of macrobleeds under various simulated anticoagulant conditions.

<p>All data were derived from 10,000 hemorrhage simulations (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048458#s2" target="_blank">Methods</a>). P-values (in comparison to next lower value of <i>τ</i>) were determined by chi-square (proportion of macrobleeds) or Mann-Whitney test (volume, duration, rate).</p>*<p>p<0.001.</p

Effect of model parameters on distribution of hemorrhage volumes.

<p>Panel A depicts combinations of expansion coefficient <i>α</i> and coagulation time constant <i>τ (</i>β = 500). Z-scale is # macrobleed/# microbleeds (log 10 ratio). Panel B shows sample histograms for bimodal conditions with three different levels of decay constants (top: <i>τ</i> = 13; middle: <i>τ</i> = 11, bottom: <i>τ</i> = 9, all with <i>α</i> = 0.01). Red marks in panel B indicate median size of macrobleeds at those parameters (log value 4.71 for <i>τ</i> = 9, 5.62 for <i>τ</i> = 11, and 6.02 for <i>τ = </i>13, corresponding to the values for macrobleed volume shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048458#pone-0048458-t001" target="_blank">Table 1</a>).</p

Simulated hemorrhage growth.

<p>Shearing forces from a primary rupture (panel A, red) generate possible secondary ruptures at neighboring segments (B, black arrows). Secondary vessel ruptures (dark blue) then contribute to possible further ruptures in subsequent cycles (C, D). The probability of adjacent rupture declines exponentially with each cycle, simulating coagulation (lightening arrows).</p

Representative expanding macrobleed.

<p>The originating vessel segment is shown in red, more recent ruptures in lightening shades of blue. No further growth occurred beyond cycle 340. Run parameters: <i>α</i> = 0.01, <i>τ</i> = 11, β = 500.</p

Boston criteria for CAA diagnosis.

<p>*As defined in reference 20.</p>‡<p>Other causes of intracerebral hemorrhage include:</p><p>• excessive warfarin dosing (INR >3.0)</p><p>• antecedent head trauma or ischemic stroke</p><p>• CNS tumor</p><p>• vascular malformation</p><p>• CNS vasculitis</p><p>• blood dyscrasia</p><p>• coagulopathy.</p><p>Note: INR.3.0 or other nonspecific laboratory abnormalities permitted for diagnosis of possible CAA.</p

Characteristics of Patients with Sporadic CAA.

<p>Characteristics of Patients with Sporadic CAA.</p

Data_Sheet_1_Comparison of Genetic and Self-Identified Ancestry in Modeling Intracerebral Hemorrhage Risk.docx

<p>Background: We sought to determine whether a small pool of ancestry-informative DNA markers (AIMs) improves modeling of intracerebral hemorrhage (ICH) risk in heterogeneous populations, compared with self-identified race/ethnicity (SIRE) alone.</p><p>Methods: We genotyped 15 preselected AIMs to perform principal component (PC) analysis in the ERICH study (a multi-center case-control study of ICH in whites, blacks, and Hispanics). We used multivariate logistic regression and tests for independent samples to compare associations for genetic ancestry and SIRE with ICH-associated vascular risk factors (VRFs). We then compared the performance of models for ICH risk that included AIMs and SIRE alone.</p><p>Results: Among 4,935 subjects, 34.7% were non-Hispanic black, 35.1% non-Hispanic white, and 30.2% Hispanic by SIRE. In stratified analysis of these SIRE groups, AIM-defined ancestry was strongly associated with seven of the eight VRFs analyzed (p < 0.001). Within each SIRE group, regression of AIM-derived PCs against VRFs confirmed independent associations of AIMs across at least two race/ethnic groups for seven VRFs. Akaike information criterion (AIC) (6,294 vs. 6,286) and likelihood ratio test (p < 0.001) showed that genetic ancestry defined by AIMs achieved a better ICH risk modeling compared to SIRE alone.</p><p>Conclusion: Genetically-defined ancestry provides valuable risk exposure information that is not captured by SIRE alone. Particularly among Hispanics and blacks, inclusion of AIMs adds value over self-reported ancestry in controlling for genetic and environmental exposures that influence risk of ICH. While differences are small, this modeling approach may be superior in highly heterogeneous clinical poulations. Additional studies across other ancestries and risk exposures are needed to confirm and extend these findings.</p

Summary of polymorphisms and classification for the genetic risk score.

<p>Summary of polymorphisms and classification for the genetic risk score.</p

Adjusted association between individual dopamine variants and depressive symptoms.

<p>Cell entries are beta coefficients, standard errors (s.e.), p-values and 95% confidence intervals (CI). The HS model controlled for race/ethnicity.</p