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Browsing by Author "Nivard, Michel G."
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Item Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts(American Psychiatric Association, 2022) Mallard, Travis T.; Savage, Jeanne E.; Johnson, Emma C.; Huang, Yuye; Edwards, Alexis C.; Hottenga, Jouke J.; Grotzinger, Andrew D.; Gustavson, Daniel E.; Jennings, Mariela V.; Anokhin, Andrey; Dick, Danielle M.; Edenberg, Howard J.; Kramer, John R.; Lai, Dongbing; Meyers, Jacquelyn L.; Pandey, Ashwini K.; Harden, Kathryn Paige; Nivard, Michel G.; de Geus, Eco J. C.; Boomsma, Dorret I.; Agrawal, Arpana; Davis, Lea K.; Clarke, Toni-Kim; Palmer, Abraham A.; Sanchez-Roige, Sandra; Biochemistry and Molecular Biology, School of MedicineObjective: Genome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT. Methods: To explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases. Results: The authors identified novel patterns of similarity (and dissimilarity) among the AUDIT items and found evidence of a correlated two-factor structure at the genetic level ("consumption" and "problems," rg=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (rg=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health. Conclusions: This work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.Item Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci(Springer Nature, 2023) Mignogna, Gianmarco; Carey, Caitlin E.; Wedow, Robbee; Baya, Nikolas; Cordioli, Mattia; Pirastu, Nicola; Bellocco, Rino; Fiuza Malerbi, Kathryn; Nivard, Michel G.; Neale, Benjamin M.; Walters, Raymond K.; Ganna, Andrea; Medical and Molecular Genetics, School of MedicineResponse to survey questionnaires is vital for social and behavioural research, and most analyses assume full and accurate response by participants. However, nonresponse is common and impedes proper interpretation and generalizability of results. We examined item nonresponse behaviour across 109 questionnaire items in the UK Biobank (N = 360,628). Phenotypic factor scores for two participant-selected nonresponse answers, 'Prefer not to answer' (PNA) and 'I don't know' (IDK), each predicted participant nonresponse in follow-up surveys (incremental pseudo-R2 = 0.056), even when controlling for education and self-reported health (incremental pseudo-R2 = 0.046). After performing genome-wide association studies of our factors, PNA and IDK were highly genetically correlated with one another (rg = 0.73 (s.e. = 0.03)) and with education (rg,PNA = -0.51 (s.e. = 0.03); rg,IDK = -0.38 (s.e. = 0.02)), health (rg,PNA = 0.51 (s.e. = 0.03); rg,IDK = 0.49 (s.e. = 0.02)) and income (rg,PNA = -0.57 (s.e. = 0.04); rg,IDK = -0.46 (s.e. = 0.02)), with additional unique genetic associations observed for both PNA and IDK (P < 5 × 10-8). We discuss how these associations may bias studies of traits correlated with item nonresponse and demonstrate how this bias may substantially affect genome-wide association studies. While the UK Biobank data are deidentified, we further protected participant privacy by avoiding exploring non-response behaviour to single questions, assuring that no information can be used to associate results with any particular respondents.Item Plasma biomarkers predict amyloid pathology in cognitively normal monozygotic twins after 10 years(Oxford University Press, 2023-02-04) den Braber, Anouk; Verberk, Inge M. W.; Tomassen, Jori; den Dulk, Ben; Stoops, Erik; Dage, Jeffrey L.; Collij, Lyduine E.; Barkhof, Frederik; Willemsen, Gonneke; Nivard, Michel G.; van Berckel, Bart N. M.; Scheltens, Philip; Visser, Pieter Jelle; de Geus, Eco J. C.; Teunissen, Charlotte E.; Neurology, School of MedicineBlood-based biomarkers could prove useful to predict Alzheimer's disease core pathologies in advance of clinical symptoms. Implementation of such biomarkers requires a solid understanding of their long-term dynamics and the contribution of confounding to their association with Alzheimer's disease pathology. Here we assess the value of plasma amyloid-β1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein to detect early Alzheimer's disease pathology, accounting for confounding by genetic and early environmental factors. Participants were 200 monozygotic twins, aged ≥60 years with normal cognition from the european medical information framework for Alzheimer's disease study. All twins had amyloid-β status and plasma samples available at study enrolment. For 80 twins, additional plasma samples were available that had been collected approximately 10 years prior to amyloid-β status assessment. Single-molecule array assays were applied to measure amyloid-β1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein. Predictive value of and longitudinal change in these biomarkers were assessed using receiver operating characteristic curve analysis and linear mixed models. Amyloid pathology could be predicted using blood-based biomarkers obtained at the time of amyloid status assessment (amyloid-β1-42/1-40: area under the curve = 0.65, P = 0.01; phosphorylated-tau181: area under the curve = 0.84, P < 0.001; glial fibrillary acidic protein: area under the curve = 0.74, P < 0.001), as well as using those obtained 10 years prior to amyloid status assessment (amyloid-β1-42/1-40: area under the curve = 0.69, P = 0.03; phosphorylated-tau181: area under the curve = 0.92, P < 0.001; glial fibrillary acidic protein: area under the curve = 0.84, P < 0.001). Longitudinally, amyloid-β1-42/1-40 levels decreased [β (SE) = -0.12 (0.01), P < 0.001] and phosphorylated-tau181 levels increased [β (SE) = 0.02 (0.01), P = 0.004]. Amyloid-β-positive individuals showed a steeper increase in phosphorylated-tau181 compared with amyloid-β-negative individuals [β (SE) = 0.06 (0.02), P = 0.004]. Also amyloid-β-positive individuals tended to show a steeper increase in glial fibrillary acidic protein [β (SE) = 0.04 (0.02), P = 0.07]. Within monozygotic twin pairs, those with higher plasma phosphorylated-tau181 and lower amyloid-β1-42/1-40 levels were more likely to be amyloid-β positive [β (SE) = 0.95 (0.26), P < 0.001; β (SE) = -0.28 (0.14), P < 0.05] indicating minimal contribution of confounding by genetic and early environmental factors. Our data support the use of amyloid-β1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein as screening tools for Alzheimer's disease pathology in the normal aging population, which is of importance for enrolment of high-risk subjects in secondary, or even primary, prevention trials. Furthermore, these markers show potential as low-invasive monitoring tool of disease progression and possibly treatment effects in clinical trials.