Browsing UMB Open Access Articles by Author "Chiappelli, J."
Cardiovascular risks impact human brain Nacetylaspartate in regionally specific patternsChiappelli, J.; Rowland, L.M.; Wijtenburg, S.A.; Chen, H.; Maudsley, A.A.; Sheriff, S.; Chen, S.; Savransky, A.; Marshall, W.; Ryan, M.C.; et al. (National Academy of Sciences, 2019)Cardiovascular risk factors such as dyslipidemia and hypertension increase the risk for white matter pathology and cognitive decline. We hypothesize that white matter levels of N-acetylaspartate (NAA), a chemical involved in the metabolic pathway for myelin lipid synthesis, could serve as a biomarker that tracks the influence of cardiovascular risk factors on white matter prior to emergence of clinical changes. To test this, we measured levels of NAA across white matter and gray matter in the brain using echo planar spectroscopic imaging (EPSI) in 163 individuals and examined the relationship of regional NAA levels and cardiovascular risk factors as indexed by the Framingham Cardiovascular Risk Score (FCVRS). NAA was strongly and negatively correlated with FCVRS across the brain, but, after accounting for age and sex, the association was found primarily in white matter regions, with additional effects found in the thalamus, hippocampus, and cingulate gyrus. FCVRS was also negatively correlated with creatine levels, again primarily in white matter. The results suggest that cardiovascular risks are related to neurochemistry with a predominantly white matter pattern and some subcortical and cortical gray matter involvement. NAA mapping of the brain may provide early surveillance for the potential subclinical impact of cardiovascular and metabolic risk factors on the brain.
Clinical and genetic validity of quantitative bipolarityBruce, H.A.; Kochunov, P.; Mitchell, B.; Strauss, K.A.; Ament, S.A.; Rowland, L.M.; Du, X.; Fisseha, F.; Kavita, T.; Chiappelli, J.; et al. (Nature Publishing Group, 2019)Research has yet to provide a comprehensive understanding of the genetic basis of bipolar disorder (BP). In genetic studies, defining the phenotype by diagnosis may miss risk-allele carriers without BP. The authors aimed to test whether quantitatively detected subclinical symptoms of bipolarity identifies a heritable trait that infers risk for BP. The Quantitative Bipolarity Scale (QBS) was administered to 310 Old Order Amish or Mennonite individuals from multigenerational pedigrees; 110 individuals had psychiatric diagnoses (20 BP, 61 major depressive disorders (MDD), 3 psychotic disorders, 26 other psychiatric disorders). Familial aggregation of QBS was calculated using the variance components method to derive heritability and shared household effects. The QBS score was significantly higher in BP subjects (31.5 ± 3.6) compared to MDD (16.7 ± 2.0), other psychiatric diagnoses (7.0 ± 1.9), and no psychiatric diagnosis (6.0 ± 0.65) (all p < 0.001). QBS in the whole sample was significantly heritable (h2 = 0.46 ± 0.15, p < 0.001) while the variance attributed to the shared household effect was not significant (p = 0.073). When subjects with psychiatric illness were removed, the QBS heritability was similar (h2 = 0.59 ± 0.18, p < 0.001). These findings suggest that quantitative bipolarity as measured by QBS can separate BP from other psychiatric illnesses yet is significantly heritable with and without BP included in the pedigrees suggesting that the quantitative bipolarity describes a continuous heritable trait that is not driven by a discrete psychiatric diagnosis. Bipolarity trait assessment may be used to supplement the diagnosis of BP in future genetic studies and could be especially useful for capturing subclinical genetic contributions to a BP phenotype.