Toward Establishing Internal Validity for Correlated Gene Expression Measures in Imaging Genomics of Functional Networks: Why Distance Corrections and External Face Validity Alone Fall Short. Reply to "Distance Is Not Everything in Imaging Genomics of Functional Networks: Reply to a Commentary on Correlated Gene Expression Supports Synchronous Activity in Brain Networks".

The primary claim of the Richiardi et al. (2015) Science article is that a measure of correlated gene expression, significant strength fraction (SSF), is related to resting state fMRI (rsfMRI) networks. However, there is still debate about this claim and whether spatial proximity, in the form of contiguous clusters, accounts entirely, or only partially, for SSF (Pantazatos and Li, 2017; Richiardi et al., 2017). Here, 13 distributed networks were simulated by combining 34 contiguous clusters randomly placed throughout cortex, with resulting edge distance distributions similar to rsfMRI networks. Cluster size was modulated (6-15 mm radius) to test its influence on SSF false positive rate (SSF-FPR) among the simulated "noise" networks. The contribution of rsfMRI networks on SSF-FPR was examined by comparing simulated networks whose clusters were sampled from: (1) all 1,777 cortical tissue samples, (2) all samples, but with non-rsfMRI cluster centers, and (3) only 1,276 non-rsfMRI samples. Results show that SSF-FPR is influenced only by cluster size (r > 0.9, p < 0.001), not by rsfMRI samples. Simulations using 14 mm radius clusters most resembled rsfMRI networks. When thresholding at p < 10-4, the SSF-FPR was 0.47. Genes that maximize SF have high global spatial autocorrelation. In conclusion, SSF is unrelated to rsfMRI networks. The main conclusion of Richiardi et al. (2015) is based on a finding that is ∼50% likely to be a false positive, not <0.01% as originally reported in the article (Richiardi et al., 2015). We discuss why distance corrections alone and external face validity are insufficient to establish a trustworthy relationship between correlated gene expression measures and rsfMRI networks, and propose more rigorous approaches to preclude common pitfalls in related studies.

A comparison of manual tracing and FreeSurfer for estimating hippocampal volume over the adult lifespan.

MRI has become an indispensable tool for brain volumetric studies, with the hippocampus an important region of interest. Automation of the MRI segmentation process has helped advance the field by facilitating the volumetric analysis of larger cohorts and more studies. FreeSurfer has emerged as the de facto standard tool for these analyses, but studies validating its output are all based on older versions. To characterize FreeSurfer's validity, we compare several versions of FreeSurfer software with traditional hand-tracing. Using MRI images of 262 males and 402 females aged 38 to 84, we directly compare estimates of hippocampal volume from multiple versions of FreeSurfer, its hippocampal subfield routines, and our manual tracing protocol. We then use those estimates to assess asymmetry and atrophy, comparing performance of different estimators with each other and with brain atrophy measures. FreeSurfer consistently reports larger volumes than manual tracing. This difference is smaller in larger hippocampi or older people, with these biases weaker in version 6.0.0 than prior versions. All methods tested agree qualitatively on rightward asymmetry and increasing atrophy in older people. FreeSurfer saves time and money, and approximates the same atrophy measures as manual tracing, but it introduces biases that could require statistical adjustments in some studies.

Associations Between Serum Inflammatory Markers and Hippocampal Volume in a Community Sample.

OBJECTIVES: To quantify associations between inflammatory biomarkers and hippocampal volume (HV) and to examine effect modification according to sex, race, and age. DESIGN: Cross-sectional analyses using generalized estimating equations to account for familial clustering; standardized ß-coefficients adjusted for age, sex, race, and education. SETTING: Community cohorts in Jackson, Mississippi and Rochester, Minnesota. PARTICIPANTS: The Genetic Epidemiology Network of Arteriopathy study. MEASUREMENTS: C-reactive protein (CRP), interleukin-6 (IL-6), and soluble tumor necrosis factor receptors 1 (sTNFR-1) and 2 (sTNFR-2) from peripheral blood were measured in a sample of 773 non-Hispanic whites (61% women, aged 60.2 ± 9.8) and 514 African Americans (70% women, aged 63.9 ± 8.1) who also underwent brain magnetic resonance imaging. Biomarkers were standardized and compared according to sex, race and age with HV. RESULTS: In the full sample, higher sTNFR-1 and sTNFR-2 were associated with smaller HV. Each standard deviation (SD) increase in sTNFR-1 was associated with 59.1 mm(3) (95% confidence interval (CI) = -101.4 to -16.7 mm(3) ) smaller HV and each SD increase in sTNFR-2 associated with 48.8 mm(3) (95% CI = -92.2 to -5.3 mm(3) ) smaller HV. Relationships were stronger for sTNFR-2 in men (HV = -116.6 mm(3) for each SD increase, 95% CI = -201.0 to -32.1) than women (HV = -26.0 per SD increase, 95% CI = -72.4-20.5) and sTNFR-1 in non-Hispanic whites (HV = -84.7 mm(3) per SD increase, 95% CI = -142.2 to -27.1) than African Americans (HV = -14.1 mm(3) per SD increase, 95% CI = -78.3-50.1). Associations between IL-6 or CRP and HV were not supported. CONCLUSION: Higher levels of sTNFRs were associated cross-sectionally with smaller hippocampi. Longitudinal data are needed to determine whether these biomarkers may help to identify risk of late-life cognitive impairment.