Biology subjects

Panizzon, M. S.

Publications and source records attributed to Panizzon, M. S..

12 recordsLinked to original sources

bioRxiv2026

Neurobiological Signatures of Endometriosis: Characterizing Pain, Cognition, and Brain Morphology

Endometriosis affects approximately 10% of reproductive-age women worldwide and is associated with substantial pain and mental health burden, yet its neurobiological correlates remain poorly characterized. Neuroimaging studies of endometriosis are particularly limited. Here we present a comprehensive, multidimensional investigation of the neurobiology of endometriosis, integrating structural and diffusion neuroimaging, biofluid measures, neuropsychological testing, and detailed health and psychosocial phenotyping in individuals with and without endometriosis. Compared with controls, individuals with endometriosis exhibited higher levels of pain, depression, and anxiety and performed worse across multiple cognitive domains. Global and regional brain morphometric measures did not differ between groups; however, endometriosis-specific pain was associated with altered gray matter volume and white matter microstructure across distributed pain-related neural circuits. These findings identify pain-related neurobiological signatures of endometriosis and establish a foundation for mechanistic and translational studies of its central nervous system effects.

neuroscience↗

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↗

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↗

bioRxiv2021

Sex differences in migraine: A twin study

Migraine is a neurological disorder with a prominent sex difference such that two thirds of sufferers are female. The mechanisms behind the preponderance of migraine in women have yet to be elucidated. With data on 51,872 participants from the Swedish Twin Registry, we report results from two distinct analyses intended to clarify the degree to which genetic and environmental factors contribute to sex differences in migraine. First, we fit a sex-limitation model to determine if quantitative genetic differences (i.e., is migraine equally heritable across men and women) and/or qualitative genetic differences (i.e., are different genes involved in migraine across men and women) were present. Next, we used a multilevel logistic regression model to compare the prevalence of migraine in individuals from opposite-sex and same-sex twin pairs to determine whether differences in the prenatal hormone environment contribute to migraine risk. In the final analytic sample, women were found to have a significantly higher rate of migraine without aura relative to men (17.6% vs 5.5%). The results from an ADE sex-limitation model indicate that migraine is equally heritable in men and women, with a broad sense heritability of .45, (95% CI = .40 - .50), while results from a reduced AE sex-limitation model provide subtle evidence for differences in the genes underlying migraine across men and women. The logistic regression analysis revealed a significant increase in migraine risk for females with a male co-twin relative to females with a female co-twin (OR = 1.51, 95% CI = 1.26 - 1.81). These results suggest that the prominent sex difference in migraine prevalence is not entirely accounted for by genetic factors, while demonstrating that masculinization of the prenatal environment may increase migraine risk for females. This effect points to a potential prenatal neuroendocrine factor in the development of migraine.

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↗

bioRxiv2020

Associations between Early Midlife Lifestyle Behaviors, Young Adult Cognitive Reserve and Advanced Predicted Brain Age in Late Midlife

ImportanceBoth cognitive reserve and modifiable lifestyle behaviors are associated with dementia risk. The effect of early lifestyle behaviors and cognitive reserve on late midlife brain aging could inform early identification and risk reduction of future dementia. ObjectiveDetermine associations of young adult cognitive reserve, early midlife lifestyle behaviors, and the reserve-by-lifestyle interaction on late midlife brain age. Examine the relationship between mild cognitive impairment (MCI) and brain age. DesignParticipants were from the nationally representative Vietnam Era Twin Study of Aging (VETSA). Cognitive reserve was assessed at median age 20 years (IQR=1.38) with the Armed Forces Qualification Test (AFQT). Lifestyle behaviors (smoking, alcohol consumption, and social engagement) were assessed at median age 41 (IQR=5.00). Structural brain imaging conducted at median age 69 (IQR=4.74) was used to construct predicted brain age difference scores (PBAD=chronological age minus predicted brain age) and MCI was ascertained. SettingIn-person cognitive testing (ages 20 and 69); mailed survey (age 41); structural MRI, MCI diagnosis at University of California, San Diego (age 69). Participants431 community-dwelling men. ExposuresAFQT; self-reported health and lifestyle behaviors. Main outcomes and measuresPBAD scores; MCI. ResultsIn fully adjusted mixed linear models, age 20 cognitive reserve and the age 41 lifestyle composite were associated with age 69 PBAD [t (104)=2.62, p=0.01, 95%CI 0.874, 6.285; t (104)=3.37, p=0.001, 95%CI 0.583, 2.249 respectively] as was the reserve-by-lifestyle interaction [t (104) = -2.29, p=0.02, 95%CI -2.330, -0.167]. Unfavorable lifestyle predicted more advanced brain age, but only for those with lower young adult cognitive reserve. The MCI group had more advanced brain age (F (2,130) = 3.13; p=0.05). Conclusions and relevanceFavorable lifestyle behaviors promoted resistance to accelerated brain aging 3 decades later for those with lower young adult cognitive reserve. High reserve appeared to be protective regardless of lifestyle. The association with MCI suggests that advanced PBAD scores reflect poorer brain integrity, although it is unclear if PBAD is related to Alzheimers dementia specifically. Lower cognitive reserve increases risk for dementia, but early lifestyle modification may promote healthier brain aging and dementia risk reduction, particularly in those with lower reserve. Study TypeCohort Study Key PointsO_ST_ABSQuestionC_ST_ABSDo modifiable lifestyle behaviors in early midlife predict later accelerated brain aging and is that association moderated by cognitive reserve? FindingsA lifestyle composite of smoking, alcohol consumption and social engagement at age 41 was associated with estimated brain age in late midlife. There was a significant moderation effect whereby more unfavorable lifestyle behaviors predicted more advanced brain aging, but only in those with low-to-moderate cognitive reserve. MeaningFavorable lifestyle behaviors appear to be protective for brain integrity especially among those with lower cognitive reserve. Early midlife efforts at prevention could be prioritized among those with lower cognitive reserve.

neuroscience↗

bioRxiv2020

Dynamics of Brain Structure and its Genetic Architecture over the Lifespan

Human brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.

genetics↗

bioRxiv2019

Semantic Fluency Predicts Six-Year Progression to Mild Cognitive Impairment in Middle-Aged Men

ObjectiveTest the hypothesis that individual differences in episodic memory and verbal fluency in cognitively normal middle-aged adults will predict progression to amnestic MCI after 6 years.\n\nMethodThe analysis sample included 842 male twins who were cognitively normal at baseline (M=56 years), completed measures of episodic memory and verbal fluency at baseline and again 6 years later (M=62 years).\n\nResultsPoor episodic memory predicted progression to both amnestic MCI (OR=4.42, 95% CI [2.44, 10.60]) and non-amnestic MCI (OR=1.92, 95% CI [1.32, 3.44]). Poor semantic verbal fluency also independently predicted progression to amnestic MCI (OR=1.86, 95% CI [1.12, 3.52]). In the full sample, a semantic-specific fluency latent variable at wave 1 (which controls for letter fluency) predicted change in episodic memory at wave 2 ({beta}=.13), but not vice-versa ({beta}=.04). Associations between episodic memory and verbal fluency factors were primarily explained by genetic, rather than environmental, correlations.\n\nConclusionsAmong individuals who were cognitively normal at wave 1, episodic memory moderately-to-strongly predicted progression to MCI at average age 62, emphasizing the fact that there is still meaningful variability even among cognitively normal individuals. Episodic memory, which is typically a primary focus for AD risk, declined earlier and more quickly than fluency. However, semantic fluency at average age 56 predicted 6-year change in memory as well as progression to amnestic MCI even after accounting for baseline memory performance. These findings emphasize the utility of memory and fluency measures in early identification of AD risk.

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↗

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↗