Relationships of Cognitive Measures with Cerebrospinal Fluid but Not Imaging Biomarkers of Alzheimer Disease Vary between Black and White Individuals.

OBJECTIVE: Biomarkers of Alzheimer disease vary between groups of self-identified Black and White individuals in some studies. This study examined whether the relationships between biomarkers or between biomarkers and cognitive measures varied by racialized groups. METHODS: Cerebrospinal fluid (CSF), amyloid positron emission tomography (PET), and magnetic resonance imaging measures were harmonized across four studies of memory and aging. Spearman correlations between biomarkers and between biomarkers and cognitive measures were calculated within each racialized group, then compared between groups by standard normal tests after Fisher's Z-transformations. RESULTS: The harmonized dataset included at least one biomarker measurement from 495 Black and 2,600 White participants. The mean age was similar between racialized groups. However, Black participants were less likely to have cognitive impairment (28% vs 36%) and had less abnormality of some CSF biomarkers including CSF Aß42/40, total tau, p-tau181, and neurofilament light. CSF Aß42/40 was negatively correlated with total tau and p-tau181 in both groups, but at a smaller magnitude in Black individuals. CSF Aß42/40, total tau, and p-tau181 had weaker correlations with cognitive measures, especially episodic memory, in Black than White participants. Correlations of amyloid measures between CSF (Aß42/40, Aß42) and PET imaging were also weaker in Black than White participants. Importantly, no differences based on race were found in correlations between different imaging biomarkers, or in correlations between imaging biomarkers and cognitive measures. INTERPRETATION: Relationships between CSF biomarkers but not imaging biomarkers varied by racialized groups. Imaging biomarkers performed more consistently across racialized groups in associations with cognitive measures. ANN NEUROL 2024;95:495-506.

CSF Biomarkers in Longitudinal Alzheimer Disease Cohorts: Pre-Analytic Challenges.

BACKGROUND: The sensitivity of amyloid to pre-analytic factors complicates cerebrospinal fluid (CSF) diagnostics for Alzheimer disease. We report reliability and validity evidence for automated immunoassays from frozen and fresh CSF samples in an ongoing, single-site research program. METHODS: CSF samples were obtained from 2 Wisconsin cohorts (1256 measurements; 727 participants). Levels of amyloid beta 1-42 (Aß42), phosphorylated tau 181 (pTau181), and total tau (tTau) were obtained using an Elecsys cobas e 601 platform. Repeatability and fixed effects of storage tube type, extraction method, and freezing were assessed via mixed models. Concordance with amyloid positron emission tomography (PET) was investigated with 238 participants having a temporally proximal PET scan. RESULTS: Repeatability was high with intraclass correlation (ICC) ≥0.9, but tube type strongly affected measurements. Discriminative accuracy for PET amyloid positivity was strong across tube types (area under the curve [AUC]: Aß42, 0.87; pTau181Aß42 , 0.96), although optimal thresholds differed. CONCLUSIONS: Under real-world conditions, the Elecsys platform had high repeatability. However, strong effects of pre-analytic factors suggest caution in drawing longitudinal inferences.

Identification of plasma metabolites associated with modifiable risk factors and endophenotypes reflecting Alzheimer's disease pathology.

Modifiable factors can influence the risk for Alzheimer's disease (AD) and serve as targets for intervention; however, the biological mechanisms linking these factors to AD are unknown. This study aims to identify plasma metabolites associated with modifiable factors for AD, including MIND diet, physical activity, smoking, and caffeine intake, and test their association with AD endophenotypes to identify their potential roles in pathophysiological mechanisms. The association between each of the 757 plasma metabolites and four modifiable factors was tested in the wisconsin registry for Alzheimer's prevention cohort of initially cognitively unimpaired, asymptomatic middle-aged adults. After Bonferroni correction, the significant plasma metabolites were tested for association with each of the AD endophenotypes, including twelve cerebrospinal fluid (CSF) biomarkers, reflecting key pathophysiologies for AD, and four cognitive composite scores. Finally, causal mediation analyses were conducted to evaluate possible mediation effects. Analyses were performed using linear mixed-effects regression. A total of 27, 3, 23, and 24 metabolites were associated with MIND diet, physical activity, smoking, and caffeine intake, respectively. Potential mediation effects include beta-cryptoxanthin in the association between MIND diet and preclinical Alzheimer cognitive composite score, hippurate between MIND diet and immediate learning, glutamate between physical activity and CSF neurofilament light, and beta-cryptoxanthin between smoking and immediate learning. Our study identified several plasma metabolites that are associated with modifiable factors. These metabolites can be employed as biomarkers for tracking these factors, and they provide a potential biological pathway of how modifiable factors influence the human body and AD risk.

Neuropathology-based APOE genetic risk score better quantifies Alzheimer's risk.

INTRODUCTION: Apolipoprotein E (APOE) ε4-carrier status or ε4 allele count are included in analyses to account for the APOE genetic effect on Alzheimer's disease (AD); however, this does not account for protective effects of APOE ε2 or heterogeneous effect of ε2, ε3, and ε4 haplotypes. METHODS: We leveraged results from an autopsy-confirmed AD study to generate a weighted risk score for APOE (APOE-npscore). We regressed cerebrospinal fluid (CSF) amyloid and tau biomarkers on APOE variables from the Wisconsin Registry for Alzheimer's Prevention (WRAP), Wisconsin Alzheimer's Disease Research Center (WADRC), and Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS: The APOE-npscore explained more variance and provided a better model fit for all three CSF measures than APOE ε4-carrier status and ε4 allele count. These findings were replicated in ADNI and observed in subsets of cognitively unimpaired (CU) participants. DISCUSSION: The APOE-npscore reflects the genetic effect on neuropathology and provides an improved method to account for APOE in AD-related analyses.

Large-scale proteome and metabolome analysis of CSF implicates altered glucose and carbon metabolism and succinylcarnitine in Alzheimer's disease.

INTRODUCTION: A hallmark of Alzheimer's disease (AD) is the aggregation of proteins (amyloid beta [A] and hyperphosphorylated tau [T]) in the brain, making cerebrospinal fluid (CSF) proteins of particular interest. METHODS: We conducted a CSF proteome-wide analysis among participants of varying AT pathology (n = 137 participants; 915 proteins) with nine CSF biomarkers of neurodegeneration and neuroinflammation. RESULTS: We identified 61 proteins significantly associated with the AT category (P < 5.46 × 10-5 ) and 636 significant protein-biomarker associations (P < 6.07 × 10-6 ). Proteins from glucose and carbon metabolism pathways were enriched among amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, whose associations with tau were replicated in an independent cohort (n = 717). CSF metabolomics identified and replicated an association of succinylcarnitine with phosphorylated tau and other biomarkers. DISCUSSION: These results implicate glucose and carbon metabolic dysregulation and increased CSF succinylcarnitine levels with amyloid and tau pathology in AD. HIGHLIGHTS: Cerebrospinal fluid (CSF) proteome enriched for extracellular, neuronal, immune, and protein processing. Glucose/carbon metabolic pathways enriched among amyloid/tau-associated proteins. Key glucose/carbon metabolism protein associations independently replicated. CSF proteome outperformed other omics data in predicting amyloid/tau positivity. CSF metabolomics identified and replicated a succinylcarnitine-phosphorylated tau association.

Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults.

INTRODUCTION: Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS: Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aß)42 /Aß40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS: We observed a significant CSF Aß42 /Aß40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION: NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.

Longitudinal effects of family psychopathology and stress on pubertal maturation and hormone coupling in adolescent twins.

Adolescents experience profound neuroendocrine changes, including hormone "coupling" between cortisol, testosterone, and dehydroepiandrosterone. Emerging research has only begun to elucidate the role of hormone coupling, its genetic and environmental etiology, and the extent to which coupling is impacted by gender, puberty, and family context. We included measures on parent and child mental health, parenting stress, and family conflict of 444 twin pairs and their parents across two timepoints, when youth were on average 8 and 13 years old, respectively. Structural equation models examined the impact of family context effects on coupling during adolescence. Biometric twin models were then used to probe additive genetic, shared, and non-shared environmental effects on hormone coupling. Hormones were more tightly coupled for females than males, and coupling was sensitive to parental depression and co-twin psychopathology symptoms and stress exposure in females. The association between family context and coupling varied across specific neuroendocrine measures and was largely distinct from pubertal maturation. Biometric models revealed robust shared and non-shared environmental influences on coupling. We found that family antecedents modify the strength of coupling. Environmental influences account for much of the variation on coupling during puberty. Gender differences were found in genetic influences on coupling.

An examination of a novel multipanel of CSF biomarkers in the Alzheimer's disease clinical and pathological continuum.

INTRODUCTION: This study examines the utility of a multipanel of cerebrospinal fluid (CSF) biomarkers complementing Alzheimer's disease (AD) biomarkers in a clinical research sample. We compared biomarkers across groups defined by clinical diagnosis and pTau181 /Aß42 status (+/-) and explored their value in predicting cognition. METHODS: CSF biomarkers amyloid beta (Aß)42 , pTau181 , tTau, Aß40 , neurogranin, neurofilament light (NfL), α-synuclein, glial fibrillary acidic protein (GFAP), chitinase-3-like protein 1 (YKL-40), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), S100 calcium binding protein B (S100B), and interleukin 6 (IL6), were measured with the NeuroToolKit (NTK) for 720 adults ages 40 to 93 years (mean age = 63.9 years, standard deviation [SD] = 9.0; 50 with dementia; 54 with mild cognitive impairment [MCI], 616 unimpaired). RESULTS: Neurodegeneration and glial activation biomarkers were elevated in pTau181 /Aß42 + MCI/dementia participants relative to all pTau181 /Aß42 - participants. Neurodegeneration biomarkers increased with clinical severity among pTau181 /Aß42 + participants and predicted worse cognitive performance. Glial activation biomarkers were unrelated to cognitive performance. DISCUSSION: The NTK contains promising markers that improve the pathophysiological characterization of AD. Neurodegeneration biomarkers beyond tTau improved statistical prediction of cognition and disease stages.

Beyond cardiovascular medicine: potential future uses of icosapent ethyl.

The REDUCE-IT trial demonstrated that icosapent ethyl, an ethyl ester of eicosapentaenoic acid (EPA), reduced cardiovascular events in an at-risk population by a substantial degree. While the cardiovascular protective properties of this compound are now proven, several other potential uses are being actively explored in clinical studies. These areas of investigation include cancer, inflammatory bowel disease, infections, Alzheimer's disease, dementia, and depression. The next decade promises to deepen our understanding of the beneficial effects that EPA may offer beyond cardiovascular risk reduction.

Attentional Control Explains Covariation Between Symptoms of Attention-Deficit/Hyperactivity Disorder and Anxiety During Adolescence.

Symptoms of attention-deficit/hyperactivity disorder (ADHD) and anxiety are common during adolescence and frequently co-occur. However, the genetic and environmental influences that underlie this co-occurrence are understudied. Using a large twin sample (N = 1,017), we examined cross-sectional genetic and environmental influences on ADHD and anxiety symptoms during childhood. We also explored whether these influences were shared with attentional control, a putative mechanism for symptom comorbidity. We found evidence for common genetic and nonshared environmental influences on the covariation among attentional control, ADHD, and anxiety symptoms, supporting the putative role of attentional control as a mechanism by which comorbid problems may develop. Genetic factors also accounted for symptom co-occurrence after controlling for covariation with attentional control, suggesting the presence of additional unmeasured mechanisms.

Longitudinal Research at the Interface of Affective Neuroscience, Developmental Psychopathology, Health and Behavioral Genetics: Findings from the Wisconsin Twin Project.

The Wisconsin Twin Project comprises multiple longitudinal studies that span infancy to early adulthood. We summarize recent papers that show how twin designs with deep phenotyping, including biological measures, can inform questions about phenotypic structure, etiology, comorbidity, heterogeneity, and gene-environment interplay of temperamental constructs and mental and physical health conditions of children and adolescents. The general framework for investigations begins with rich characterization of early temperament and follows with study of experiences and exposures across childhood and adolescence. Many studies incorporate neuroimaging and hormone assays.

Sex Differences in the Genetic and Environmental Influences on Self-Reported Non-aggressive and Aggressive Conduct Disorder Symptoms in Early and Middle Adolescence.

Decades of research into the etiology of conduct disorder (CD) has yet to yield a consensus on the existence of sex differences in underlying genetic and environmental influences. This may be partly due to the failure of many previous studies to make a distinction between non-aggressive and aggressive CD symptoms or test for potential developmental changes in sex differences in the etiology of conduct problems. To address these gaps, we fit a series of univariate and bivariate biometric sex-difference models to self-reported non-aggressive and aggressive CD symptoms in a community-based sample of twins (N = 1548, ages 9-17 year), grouped into ages 9-13 and 14-17 years. Relative model fit was evaluated using the Bayesian Information Criterion (BIC), which favors parsimony, and by Chi square difference tests. The univariate sex-scalar model provided the best fit to the data for both non-aggressive and aggressive CD symptoms at ages 9-13 and 14-17 years. Thus, the same genetic and environmental factors influenced CD symptoms in both sexes, but the total variability was lower in females than males. At both ages, the heritability of non-aggressive CD symptoms was lower than heritability of aggressive CD symptoms, and shared environmental effects were only observed for non-aggressive CD symptoms. However, estimates for genetic and environmental factors could be not be constrained to be equal across age groups for either CD subtype, suggesting substantive developmental changes in the relative influence of genetic and environmental factors on individual differences in CD symptoms. For both subtypes, the heritability was larger, and shared environmental effect smaller, in the older age group than the younger age group. A bivariate quantitative sex differences model provided the best fit to the data at ages 9-13 years. Covariation between non-aggressive and aggressive CD symptoms was due to overlapping shared and non-shared environmental factors in males and females but the overall covariation was greater in males than females. In contrast, at ages 14-17 years, the sex-scalar bivariate model provided the best fit to the data, and covariation between non-aggressive and aggressive CD symptoms was due to overlapping genetic and non-shared environmental factors. Thus, the etiology of self-reported conduct disorder varied substantially by symptom type and age. However, quantitative sex differences were only apparent when the covariation between the two subtypes was considered.

Infant stranger fear trajectories predict anxious behaviors and diurnal cortisol rhythm during childhood.

Although a robust literature has linked stable, high levels of fear across childhood to increased risk for anxiety problems, less is known about alternative pathways to anxiety. We tested two putatively normative developmental pathways of early fearfulness for their distinct associations with behavioral (anxiety-related behaviors and symptoms) and biological (diurnal cortisol) markers of anxiety risk in middle childhood in a community-based sample (n = 107). Steeper increases in fear from 6 to 36 months predicted more parent-reported anxiety symptoms at age 8 years. In addition, children who exhibited steep increases in fear during infancy were overrepresented among children with diagnoses of separation anxiety disorder at age 8 years. Finally, we showed that steeper increases in fearfulness in infancy predicted flatter slopes of diurnal cortisol at age 8 years for girls. Thus, differences in stranger fear across infancy may indicate varying degrees of risk for anxious behaviors in later childhood.

Partial replication of two rumination-related candidate gene studies.

Two recent papers associated candidate genes with brooding rumination, a possible cognitive endophenotype for depression, in children ages 8-14 years. Stone et al. reported that BDNF val66met polymorphism predicted brooding in adolescence. Woody et al. reported that children carrying at least one copy of a CRHR1 TAT haplotype reported less brooding than their peers in the presence of maternal depression. We attempted to replicate and extend these findings in a sample of twins aged 12-16 years. We analyzed the BDNF val66met (rs6265) polymorphism and two (rs242924 and rs7209436) out of three single nucleotide polymorphisms (SNPs) that Woody et al. used to create a CRHR1 haplotype. We controlled for maternal history of depression and clustering within families. Unlike Stone et al., we found higher brooding among BDNF Met carriers. This main effect was qualified by an interaction with pubertal status, with the effect driven by more physically mature participants. Similar to Woody et al., we found an interaction between CRHR1 SNPs and maternal depression, with the homozygous minor genotype acting as a protective factor against brooding in the presence of maternal depression. Findings provide partial support for the influence of candidate genes in two environmentally sensitive systems on brooding.

Genetic and Environmental Contributions to Associations between Infant Fussy Temperament and Antisocial Behavior in Childhood and Adolescence.

Previous research suggests that fussy temperament in infancy predicts risk for later antisocial behavior (ASB) in childhood and adolescence. It remains unclear, however, to what extent infant fussiness is related to later ASB through causal processes or if they both reflect the same family risk factors for ASB. The current study used two approaches, the comparison of siblings and bivariate biometric modeling, to reduce familial confounding and examine genetic and environmental influences on associations between fussiness in the first 2 years of life and ASB in childhood and late adolescence. Analyses were conducted on data from a prospective cohort (9237 at 4-9 years and 7034 at 14-17 years) who are the offspring of a nationally representative sample of US women. In the full sample, fussiness predicted both child and adolescent ASB to small but significant extents, controlling for a wide range of measured child and family-level covariates. When siblings who differed in their fussiness were compared, fussiness predicted ASB in childhood, but not ASB during adolescence. Furthermore, results from a bivariate Cholesky model suggested that even the association of fussiness with childhood ASB found when comparing siblings is attributable to familial factors. That is, although families with infants who are higher in fussiness also tend to have children and adolescents who engage in greater ASB, the hypothesis that infant fussiness has an environmentally mediated impact on the development of future ASB was not strongly supported.

A Genetically Informed Study of the Associations Between Maternal Age at Childbearing and Adverse Perinatal Outcomes.

We examined associations of maternal age at childbearing (MAC) with gestational age and fetal growth (i.e., birth weight adjusting for gestational age), using two genetically informed designs (cousin and sibling comparisons) and data from two cohorts, a population-based Swedish sample and a nationally representative United States sample. We also conducted sensitivity analyses to test limitations of the designs. The findings were consistent across samples and suggested that, associations observed in the population between younger MAC and shorter gestational age were confounded by shared familial factors; however, associations of advanced MAC with shorter gestational age remained robust after accounting for shared familial factors. In contrast to the gestational age findings, neither early nor advanced MAC was associated with lower fetal growth after accounting for shared familial factors. Given certain assumptions, these findings provide support for a causal association between advanced MAC and shorter gestational age. The results also suggest that there are not causal associations between early MAC and shorter gestational age, between early MAC and lower fetal growth, and between advanced MAC and lower fetal growth.

Comparing Alternative Biometric Models with and without Gene-by-Measured Environment Interaction in Behavior Genetic Designs: Statistical Operating Characteristics.

To extend Purcell's well known ACE model in testing gene by measured environment interactions (GxM) in behavior genetic designs, Rathouz et al. considered a broader class of models for quantifying and testing such interactions. Only a sub-group of these extended models have been investigated for their statistical operating characteristics by Van Hulle et al. due to lack of closed form likelihood. With an estimation procedure developed using numerical techniques in a companion paper, we study statistical operating characteristics of these extended models, especially those with non-linear effects. Type I error analysis shows the likelihood ratio test for GxM to be conservative in testing models extended from the bivariate Cholesky model, and to be liberal for models extended from the bivariate correlated factors model. Parameter estimation for all models is very good, with little bias exhibited for most models and parameters. Comparisons among alternative models under various simulated conditions show that it is relatively more difficult to confirm the existence of gene by environment interactions versus to detect non-linear effects which exclude such interactions.

Genetic and Environmental Contributions to Covariation Between DHEA and Testosterone in Adolescent Twins.

Although several studies have shown that pubertal tempo and timing are shaped by genetic and environmental factors, few studies consider to what extent endocrine triggers of puberty are shaped by genetic and environmental factors. Doing so moves the field from examining correlated developmentally-sensitive biomarkers toward understanding what drives those associations. Two puberty related hormones, dehydroepiandrosterone and testosterone, were assayed from salivary samples in 118 MZ (62 % female), 111 same sex DZ (46 % female) and 103 opposite-sex DZ twin pairs, aged 12-16 years (M = 13.1, SD = 1.3). Pubertal status was assessed with a composite of mother- and self-reports. We used biometric models to estimate the genetic and environmental influences on the variance and covariance in testosterone and DHEA, with and without controlling for their association with puberty, and to test for sex differences. In males, the variance in testosterone and pubertal status was due to shared and non-shared environmental factors; variation in DHEA was due to genetic and non-shared environmental factors. In females, variance in testosterone was due to genetic and non-shared environmental factors; genetic, shared, and non-shared environmental factors contributed equally to variation in DHEA. In males, the testosterone-DHEA covariance was primarily due to shared environmental factors that overlapped with puberty as well as shared and non-shared environmental covariation specific to testosterone and DHEA. In females, the testosterone-DHEA covariance was due to genetic factors overlapping with pubertal status, and shared and non-shared environmental covariation specific to testosterone and DHEA.

Behavior problems and timing of menarche: a developmental longitudinal biometrical analysis using the NLSY-Children data.

A powerful longitudinal data source, the National Longitudinal Survey of Youth Children data, allows measurement of behavior problems (BP) within a developmental perspective linking them to menarcheal timing (MT). In a preliminary analysis, we evaluate the bivariate relationships between BP measured at different developmental periods and the timing of menarche. Correlations were not consistent with any correlational/causal relationship between BP and MT. In the major part of our study, MT was used to moderate the developmental trajectory of BP, within a genetically-informed design. Girls reaching menarche early had behavior problem variance accounted for by the shared environment; those reaching menarche with average/late timing had behavior problem differences accounted for by genetic variance. Our findings match previous empirical results in important ways, and also extend those results. A theoretical interpretation is offered in relation to a theory linking genetic/shared environmental variance to flexibility and choices available within the family in relation to BP.

Operating Characteristics of Statistical Methods for Detecting Gene-by-Measured Environment Interaction in the Presence of Gene-Environment Correlation under Violations of Distributional Assumptions.

Accurately identifying interactions between genetic vulnerabilities and environmental factors is of critical importance for genetic research on health and behavior. In the previous work of Van Hulle et al. (Behavior Genetics, Vol. 43, 2013, pp. 71-84), we explored the operating characteristics for a set of biometric (e.g., twin) models of Rathouz et al. (Behavior Genetics, Vol. 38, 2008, pp. 301-315), for testing gene-by-measured environment interaction (GxM) in the presence of gene-by-measured environment correlation (rGM) where data followed the assumed distributional structure. Here we explore the effects that violating distributional assumptions have on the operating characteristics of these same models even when structural model assumptions are correct. We simulated N = 2,000 replicates of n = 1,000 twin pairs under a number of conditions. Non-normality was imposed on either the putative moderator or on the ultimate outcome by ordinalizing or censoring the data. We examined the empirical Type I error rates and compared Bayesian information criterion (BIC) values. In general, non-normality in the putative moderator had little impact on the Type I error rates or BIC comparisons. In contrast, non-normality in the outcome was often mistaken for or masked GxM, especially when the outcome data were censored.