Biology subjects

Kremen, W. S.

Publications and source records attributed to Kremen, W. S..

11 recordsLinked to original sources

bioRxiv2024

Testing the causal impact of amyloidosis on total Tau using a genetically informative sample of adult male twins.

INTRODUCTIONThe amyloid cascade hypothesis predicts that amyloid-beta (A{beta}) aggregation drives tau tangle accumulation. We tested competing causal and non-causal hypotheses regarding the direction of causation between A{beta}40 and A{beta}42 and total Tau (t-Tau) plasma biomarkers. METHODSPlasma A{beta}40, A{beta}42, t-Tau, and neurofilament light chain (NFL) were measured in 1,035 men (mean = 67.0 years) using Simoa immunoassays. Genetically informative twin modeling tested the direction of causation between A{beta}s and t-Tau. RESULTSNo clear evidence that A{beta}40 or A{beta}42 directly causes changes in t-Tau was observed; the alternative causal hypotheses also fit the data well. In contrast, exploratory analyses suggested a causal impact of the A{beta} biomarkers on NFL. Separately, reciprocal causation was observed between t-Tau and NFL. DISCUSSIONPlasma A{beta}40 or A{beta}42 do not appear to have a direct causal impact on t-Tau. In contrast, A{beta} aggregation may causally impact NFL in cognitively unimpaired men in their late 60s.

pathology↗

bioRxiv2024

Genetic and environmental contributions to eigengene expression

Multivariate network-based analytic methods such as weighted gene co-expression network analysis are being increasingly applied to human and animal gene-expression data to estimate module eigengenes (MEs). MEs represent multivariate summaries of correlated gene-expression patterns and network connectivity across genes within a module. Although this approach has the potential to elucidate the mechanisms by which molecular genomic variations contribute to individual differences in complex traits, the genetic etiology of MEs has never been empirically established. It is unclear if and to what degree individual differences in blood derived MEs reflect random variation versus familial aggregation arising from heritable or shared environmental influences. We used biometrical genetic analyses to estimate the contribution of genetic and environmental influences on MEs derived from blood lymphocytes collected on a sample of N=661 older male twins from the Vietnam Era Twin Study of Aging (VETSA) whose mean age at assessment was 67.7 years (SD=2.6 years, range=62-74 years). Of the 26 detected MEs, 14 (56%) had statistically significant additive genetic variation with an average heritability of 44% (SD=0.08, range=35-64%). Despite the relatively small sample size, this demonstration of significant family aggregation including estimates of heritability in 14 of the 26 MEs suggests that blood-based MEs are reliable and merit further exploration in terms of their associations with complex traits and diseases.

genetics↗

bioRxiv2022

Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from anatomical, functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to model the genetic architecture of cortical surface area (SA) and cortical thickness (CT) of 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance. Genomic SEM can fit a multivariate GWAS from summary statistics, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA was explained by 6 latent factors and CT was explained by 4 latent factors. The multivariate GWAS of these latent factors identified 74 genome-wide significant (GWS) loci (p<5x10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of latent factor GWAS results found that SA-derived factors had a positive genetic correlation with bipolar disorder (BPD), and major depressive disorder (MDD), and a negative genetic correlation with attention deficit hyperactivity disorder (ADHD), MDD, and insomnia, while CT factors displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping genetically informed cortical networks. HIGHLIGHTSO_LIGenomic SEM can examine genetic correlation across cortical regions. C_LIO_LIWe inferred regional genetic networks of cortical thickness and surface area. C_LIO_LINetwork-associated variants have been implicated in multiple traits. C_LIO_LIThese networks are genetically correlated with several psychiatric disorders including MDD, bipolar, ADHD, and alcohol dependence. C_LI

genomics↗

bioRxiv2022

The genetic and environmental etiology of blood-based biomarkers related to the risks of Alzheimer's Disease in a population-based sample of early old age men

The amyloid-tau-neurodegeneration (ATN) framework has led to an increased focus on Alzheimers disease (AD) biomarkers. The cost and invasiveness of obtaining biomarkers via cerebrospinal fluid has motivated efforts to develop sensitive blood-based biomarkers. Although AD is highly heritable, the biometric genetic and environmental etiology of blood-based biomarkers has never been explored. We therefore, analyzed plasma beta-amyloid (A{beta}40, A{beta}42, A{beta}42/40), total tautau (t-tautau), and neurofilament light (NFL) biomarkers in a sample of 1,050 men aged 60 to 73 years (m=68.2, SD=2.5) from the Vietnam Era Twin Study of Aging (VETSA). Unlike A{beta} and tautau, NFL does not define AD; however, as a biomarker of neurodegeneration it serves as the N component in the ATN framework. Univariate estimates suggest that familial aggregation in A{beta}42, A{beta}42/40, t-tau, and NFL is entirely explained by additive genetic influences accounting for 40%-58% of the total variance. All remaining variance is associated with unshared or unique environmental influences. For A{beta}40, a additive genetic (31%), shared environmental (44%), and unshared environmental (25%) influences contribute to the total variance. In the more powerful multivariate analysis of A{beta}42, A{beta}40, t-tau, and NFL, heritability estimates range from 32% to 58%. A{beta}40 and A{beta}42 are statistically genetically identical (rg = 1.00, 95%CI = 0.92,1.00) and are also moderately environmentally correlated (re = 0.66, 95%CI = 0.59, 0.73). All other genetic and environmental associations were non-significant or small. Our results suggest that plasma biomarkers are heritable and that A{beta}40 and A{beta}42 share the same genetic influences, whereas the genetic influences on plasma t-tau and NFL are mostly unique and uncorrelated with plasma A{beta} in early old-age men.

genetics↗

bioRxiv2021

The genetic etiology of longitudinal measures of predicted brain ageing in a population-based sample of mid to late-age males

Magnetic resonance imaging data are being used in statistical models to predicted brain ageing (PBA) and as biomarkers for neurodegenerative diseases such as Alzheimers Disease. Despite their increasing application, the genetic and environmental etiology of global PBA indices is unknown. Likewise, the degree to which genetic influences in PBA are longitudinally stable and how PBA changes over time are also unknown. We analyzed data from 734 men from the Vietnam Era Twin Study of Aging with repeated MRI assessments between the ages 52 to 72 years. Biometrical genetic analyses twin models revealed significant and highly correlated estimates of additive genetic heritability ranging from 59% to 75%. Multivariate longitudinal modelling revealed that covariation between PBA at different timepoints could be explained by a single latent factor with 73% heritability. Our results suggest that genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and are largely explained by common genetic influences. HighlightsWe explored the genetic and environmental etiology of MRI-based predicted brain age (PBA) in a longitudinal sample of males starting in midlife. Genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and largely explained by common genetic influences.

genetics↗

bioRxiv2019

Multiple memory tests in midlife improve prediction of mild cognitive impairment

INTRODUCTIONPredicting risk for Alzheimers disease when most people are likely still biomarker negative would aid earlier identification. We hypothesized that combining multiple memory tests and scores in middle-aged adults would provide useful, and non-invasive, prediction of 6-year progression to MCI.\n\nMETHODSWe examined 849 men who were cognitively normal at baseline (mean age=55.69{+/-}2.45).\n\nRESULTSCalifornia Verbal Learning Test learning trials was the best individual predictor of amnestic MCI (OR=4.75). A latent factor incorporating 7 measures across 3 memory tests provided much stronger prediction (OR=9.88). This compared favorably with biomarker-based prediction in a study of much older adults.\n\nDISCUSSIONNeuropsychological tests are sensitive and early indicators of Alzheimers disease risk at an age when few individuals are likely to have yet become biomarker positive. Single best measures may appear time- and cost-effective, but 30 additional minutes of testing, and use of multiple scores within tests, provides substantially improved prediction

pathology↗

bioRxiv2019

Aβ-Positivity Predicts Cognitive Decline but Cognition Also Predicts Progression to Aβ-Positivity

IntroductionBiomarker positivity predicts cognitive decline and Alzheimers dementia. But what predicts biomarker positivity? We hypothesized that cognitive function and p-tau would predict progression from normal to abnormal levels of {beta}-amyloid (A{beta}). MethodsBaseline cognition in 292 non-demented, A{beta}-negative Alzheimers Disease Neuroimaging Initiative (ADNI) participants was measured with two cognitive composites and compared between those that progressed to A{beta}-positivity versus A{beta}-stable. Follow-up analyses included continuous CSF A{beta} and p-tau levels to examine subthreshold effects. ResultsContinuously measured baseline subthreshold A{beta} and p-tau predicted progression to A{beta}-positivity, but both baseline cognitive measures predicted progression to A{beta}-positivity even after controlling for baseline biomarker levels. DiscussionCurrent A{beta} thresholds may be ignoring relevant subthreshold pathology. Importantly, cognitive function can be an important early predictor of future risk, even earlier than the key biomarkers as currently measured. Moreover, A-/T+ individuals may still be on the AD pathway because p-tau also predicted progression to positivity.

neuroscience↗

bioRxiv2018

Genetic risk for coronary heart disease alters the influence of Alzheimer’s genetic risk on mild cognitive impairment

BACKGROUNDAlzheimers disease (AD) is under considerable genetic influence. However, known susceptibility loci only explain a modest proportion of variance in disease outcomes. This small proportion could occur if the etiology of AD is heterogeneous. We previously found that an AD polygenic risk score (PRS) was significantly associated with mild cognitive impairment (MCI), an early stage of AD. Poor cardiovascular health is also associated with increased risk for AD and has been found to interact with AD pathology. Conditions such as coronary artery disease (CAD) are also heritable, and may contribute to heterogeneity if there are interactions of genetic risk for these conditions as there is phenotypically. However, case-control designs based on prevalent cases of a disease with relatively high case-fatality rate such as CAD may be biased toward individuals who have long post-event survival times and may therefore also identify loci with protective effects.\n\nMETHODSWe compared interactions between an AD-PRS and two CAD-PRSs, one based on a GWAS of incident cases and one on prevalent cases, on MCI status in 1,209 individuals.\n\nRESULTSAs expected, the incidence-based CAD-PRS interacts with the AD-PRS to further increase MCI risk. Conversely, higher prevalence-based CAD-PRSs reduced the effect of AD genetic risk on MCI status.\n\nCONCLUSIONSThese results demonstrate: i) the utility of including multiple PRSs and their interaction effects; ii) how genetic risk for one disease may modify the impact of genetic risk for another; and iii) the importance of considering ascertainment procedures of GWAS being used for genetic risk prediction.

genomics↗

bioRxiv2018

Planar cell polarity pathway and development of the human visual cortex

The radial unit hypothesis provides a framework for global (proliferation) and regional (distribution) expansion of the primate cerebral cortex. Using principal component analysis (PCA), we have identified cortical regions with shared variance in their surface area and cortical thickness, respectively, segmented from magnetic resonance images obtained in 23,800 participants. We then carried out meta-analyses of genome-wide association studies of the first two principal components for each phenotype. For surface area (but not cortical thickness), we have detected strong associations between each of the components and single nucleotide polymorphisms in a number of gene loci. The first (global) component was associated mainly with loci on chromosome 17 (9.5e-32 [≤] p [≤] 2.8e-10), including those detected previously as linked with intracranial volume and/or general cognitive function. The second (regional) component captured shared variation in the surface area of the primary and adjacent secondary visual cortices and showed a robust association with polymorphisms in a locus on chromosome 14 containing Disheveled Associated Activator of Morphogenesis 1 (DAAM1; p=2.4e-34). DAAM1 is a key component in the planar-cell-polarity signaling pathway. In follow-up studies, we have focused on the latter finding and established that: (1) DAAM1 is highly expressed between 12th and 22nd post-conception weeks in the human cerebral cortex; (2) genes co-expressed with DAAM1 in the primary visual cortex are enriched in mitochondria-related pathways; and (3) volume of the lateral geniculate nucleus, which projects to regions of the visual cortex staining for cytochrome oxidase (a mitochondrial enzyme), correlates with the surface area of the visual cortex in major-allele homozygotes but not in carriers of the minor allele. Altogether, we speculate that, in concert with thalamocortical input to cortical subplate, DAAM1 enables migration of neurons to cytochrome-oxidase rich regions of the visual cortex, and, in turn, facilitates regional expansion of this set of cortical regions during development.

neuroscience↗

bioRxiv2017

Brain structure mediates the association between height and cognitive ability

Height and general cognitive ability (GCA) are positively associated, but the underlying mechanisms of this relationship are unclear. We used a sample of 515 middle-aged male twins with structural magnetic resonance imaging data to study if the association between height and cognitive ability is mediated by cortical size. We used genetically, ontogenetically and phylogenetically distinct cortical metrics of cortical surface area (SA) and cortical thickness (CT). Our results indicate that the well-replicated height-GCA association is accounted for by individual differences in total cortical SA (highly heritable metric related to global brain size), and not mean CT, and that the genetic association between SA and GCA underlies the phenotypic height-GCA relationship.

neuroscience↗

bioRxiv2017

PTSD Blood Transcriptome Mega-Analysis: Shared Inflammatory Pathways Across Genders And Modes Of Traumas

Transcriptome-wide screens of peripheral blood during the onset and development of posttraumatic stress disorder (PTSD) indicate widespread immune dysregulation. However, little is known as to whether biological sex and the type of traumatic event influence shared or distinct biological pathways in PTSD. We performed a combined analysis of five independent PTSD blood transcriptome studies covering seven types of trauma in 229 PTSD and 311 comparison individuals to synthesize the extant data. Analyses by trauma type revealed a clear pattern of PTSD gene expression signatures distinguishing interpersonal (IP)-related traumas from combat-related traumas. Co-expression network analyses integrated all data and identified distinct gene expression perturbations across sex and modes of trauma in PTSD, including one wound-healing module down-regulated in men exposed to combat traumas, one IL12-mediated signaling module up-regulated in men exposed to IP-related traumas, and two modules associated with lipid metabolism and MAPK-activity up-regulated in women exposed to IP-related traumas. Remarkably, a high degree of sharing of transcriptional dysregulation across sex and modes of trauma in PTSD was also observed converging on common signaling cascades, including cytokine, innate immune and type I interferon pathways. Collectively, these findings provide a broad view of immune dysregulation in PTSD and demonstrate inflammatory pathways of molecular convergence and specificity, which may inform mechanisms and diagnostic biomarkers for the disorder.

neuroscience↗