An Examination of Racial/Ethnic Differences on the Neurobehavioral Symptom Inventory Among Veterans Completing the Comprehensive Traumatic Brain Injury Evaluation: A Veterans Affairs Million Veteran Program Study

OBJECTIVE

The purpose of this study was to explore racial/ethnic differences in neurobehavioral symptom reporting and symptom validity testing among military veterans with a history of traumatic brain injury (TBI).

METHOD

Participants of this observational cross-sectional study (N = 9,646) were post-deployed Iraq-/Afghanistan-era veterans enrolled in the VA's Million Veteran Program with a clinician-confirmed history of TBI on the Comprehensive TBI Evaluation (CTBIE). Racial/ethnic groups included White, Black, Hispanic, Asian, Multiracial, Another Race, American Indian or Alaska Native, and Native Hawaiian or Other Pacific Islander. Dependent variables included neurobehavioral symptom domains and symptom validity assessed via the Neurobehavioral Symptom Inventory (NSI) and Validity-10, respectively.

RESULTS

Chi-square analyses showed significant racial/ethnic group differences for vestibular, somatic/sensory, and affective symptoms as well as for all Validity-10 cutoff scores examined (≥33, ≥27, ≥26, >22, ≥22, ≥13, and ≥7). Follow-up analyses compared all racial/ethnic groups to one another, adjusting for sociodemographic- and injury-related characteristics. These analyses revealed that the affective symptom domain and the Validity-10 cutoff of ≥13 revealed the greatest number of racial/ethnic differences.

CONCLUSIONS

Results showed significant racial/ethnic group differences on neurobehavioral symptom domains and symptom validity testing among veterans who completed the CTBIE. An enhanced understanding of how symptoms vary by race/ethnicity is vital so that clinical care can be appropriately tailored to the unique needs of all veterans. Results highlight the importance of establishing measurement invariance of the NSI across race/ethnicity and underscore the need for ongoing research to determine the most appropriate Validity-10 cutoff score(s) to use across racially/ethnically diverse veterans.

Abstract MP16: Multi-trait Gwas Of Atherosclerosis Detects Novel Loci And Potential Therapeutic Targets

Atherosclerosis, which is the narrowing of the arterial walls via accumulation of cholesterol-rich arterial plaques, is the leading cause of vascular disease worldwide, including myocardial infarction and ischemic stroke. Although atherosclerosis affects arteries throughout the body, previous genome-wide association studies (GWAS) have been performed on specific atherosclerotic phenotypes such as coronary artery disease (CAD) and peripheral artery disease (PAD). There is substantial evidence to suggest that these more specific atherosclerosis phenotypes share a common genetic etiology. We performed a series of multi-trait GWAS using combinations of two atherosclerosis traits and seven atherosclerosis risk factor traits and detected 31 novel pleiotropic loci. We performed these multi-trait GWAS using the N-GWAMA multi-trait GWAS method and summary statistics for CAD (van der Harst et al. 2018), PAD (Klarin et al. 2019), body mass index (Pulit et al. 2019), type II diabetes (Vujkovic et al. 2020), smoking initiation (Wootton et al. 2020), and lipid traits (Klarin et al. 2019). We identified candidate causal genes for 14 of these loci through colocalization analysis with GTEx expression quantitative trait locus (eQTL) data. VDAC2 and PCSK6 are two candidate causal genes that our results and previous literature suggest are potential therapeutic targets. VDAC2 eQTLs in aorta and tibial artery colocalized with a multi-trait GWAS signal detected in the CAD PAD multi-trait GWAS. Previous work has shown that VDAC2 regulates apoptosis, and our results suggest increased VDAC2 expression in smooth muscle cells could increase smooth muscle cell accumulation in atherosclerotic plaques. A sQTL (splicing QTL) for PCSK6 in liver colocalized with a multi-trait GWAS signal between PAD and LDL. Further analysis of the sQTL signal suggested that the effect allele correlates with a more active isoform of PCSK6 , which could increase lipid fractions and risk of atherosclerosis. These results show that joint analysis of atherosclerotic disease traits and their risk factors allows for identification of unified biology that may offer the opportunity for therapeutic manipulation.

Minority-centric meta-analyses of blood lipid levels identify novel loci in the Population Architecture using Genomics and Epidemiology (PAGE) study

Lipid levels are important markers for the development of cardio-metabolic diseases. Although hundreds of associated loci have been identified through genetic association studies, the contribution of genetic factors to variation in lipids is not fully understood, particularly in U.S. minority groups. We performed genome-wide association analyses for four lipid traits in over 45,000 ancestrally diverse participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study, followed by a meta-analysis with several European ancestry studies. We identified nine novel lipid loci, five of which showed evidence of replication in independent studies. Furthermore, we discovered one novel gene in a PrediXcan analysis, minority-specific independent signals at eight previously reported loci, and potential functional variants at two known loci through fine-mapping. Systematic examination of known lipid loci revealed smaller effect estimates in African American and Hispanic ancestry populations than those in Europeans, and better performance of polygenic risk scores based on minority-specific effect estimates. Our findings provide new insight into the genetic architecture of lipid traits and highlight the importance of conducting genetic studies in diverse populations in the era of precision medicine.

Blood lipid levels are closely linked to cardio-metabolic diseases, and genetic factors play an important role in their metabolism and regulation. Although over 400 loci have been identified through genetic association studies, the genetic architecture of lipid levels is not fully characterized. The lack of representation of diverse populations in previous studies resulted in a large gap in understanding the genetic background of lipid traits between European and minority populations, including African Americans, Hispanics, Hawaiians, and Native Americans. In our current analyses which included ancestrally diverse populations, we identified nine novel loci, one novel gene, and minority-specific independent signals at eight known loci, and pinpointed potential functional variants at two known loci. We further observed smaller effect sizes of reported lipids-associated loci in African Americans and Hispanics than those in Europeans, and better performance of polygenic risk scores using minority-specific instead of European-derived effect sizes when estimating genetic predisposition in minority populations. Our findings showed the benefits of including multi-ethnic studies in identification and refinement of lipids-associated loci, which will help to reduce the existing disparities and to pave the road to precision medicine.