Publications by authors named "M L Pergadia"

Introduction: Rates of light smoking have increased in recent years and are associated with adverse health outcomes. Reducing light smoking is a challenge because it is unclear why some but not others, progress to heavier smoking. Nicotine has profound effects on brain reward systems and individual differences in nicotine's reward-enhancing effects may drive variability in smoking trajectories.

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Depression is a risk factor for nicotine use and withdrawal. Population level epidemiologic studies that include users of either combustible or electronic cigarette (NICUSER) could inform interventions to reduce nicotine dependence in vulnerable populations. The current study examined the relationship between depression diagnosis (DEPDX), NICUSER, and lifetime rates of DSM-V nicotine withdrawal (NW) symptoms in a nationally representative sample of US adults ( = 979), who answered related questions in surveys administered through GfK's KnowledgePanel.

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Accurate knowledge of negative affect (NA)-related smoking abstinence symptoms (SAS) severity and duration and their moderation by pharmacotherapy and NA-related personality traits is critical for efficacious treatments given that elevated state and trait NA are predictors of relapse. However, SAS severity, duration, and moderation are not well characterized. To date, the longest randomized controlled trial (RCT) of NA-related SAS using randomized delayed-quit smoking controls only examined symptoms across 45 days, despite clinical evidence that SAS may last longer.

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Article Synopsis
  • A study investigated the genetic overlap between 25 brain disorders using data from over 1.2 million individuals, finding that psychiatric disorders share more genetic risk compared to neurological disorders, which seem more distinct.
  • The research identified significant relationships between these disorders and various cognitive measures, suggesting shared underlying traits.
  • Simulations were conducted to understand how factors like sample size and diagnosis accuracy influence genetic correlations, emphasizing the role of common genetic variations in the risk of brain disorders.
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