Polygenic Risk and Episode Polarity Among Individuals With Bipolar Disorder

Predominant Polarity for Enhanced Phenotyping and Personalized Treatment of Bipolar Disorder: A Narrative Review on Recent Findings

PURPOSE OF REVIEW

This paper explores Predominant Polarity (PP) in Bipolar Disorder (BD), defined as the predominance of either manic or depressive episodes over a patient's course of illness. We examine its clinical relevance, neurobiological foundations, and potential for guiding personalized treatment strategies. The review seeks to determine whether PP is a reliable course specifier and how it can be utilized to improve clinical outcomes.

RECENT FINDINGS

PP has a significant impact on prognosis and treatment planning in BD. Manic and depressive PP are associated with distinct clinical and neurobiological profiles of BD, while individuals without a clear predominance of either episode type represent a more severe to-treat subgroup of patients. The development of the Polarity Index (PI) facilitates treatment decisions based on PP. PP offers a valuable framework for refining BD treatment and understanding its complexity. Future research should focus on refining PP definitions, validating neurobiological markers, and integrating these insights into comprehensive treatment models to improve patient outcomes.

Development and validation of a lung cancer polygenic risk score incorporating susceptibility variants for risk factors

Incorporating susceptibility genetic variants of risk factors has been reported to enhance the risk prediction of polygenic risk score (PRS). However, it remains unclear whether this approach is effective for lung cancer. Hence, we aimed to construct a meta polygenic risk score (metaPRS) of lung cancer and assess its prediction of lung cancer risk and implication for risk stratification. Here, a total of 2180 genetic variants were used to develop nine PRSs for lung cancer, three PRSs for different histopathologic subtypes, and 17 PRSs for lung cancer-related risk factors, respectively. These PRSs were then integrated into a metaPRS for lung cancer using the elastic-net Cox regression model in the UK Biobank (N = 442,508). Furthermore, the predictive effects of the metaPRS were assessed in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial (N = 108,665). The metaPRS was associated with lung cancer risk with a hazard ratio of 1.33 (95% confidence interval: 1.27-1.39) per standard deviation increased. The metaPRS showed the highest C-index (0.580) compared with the previous nine PRSs (C-index: 0.513-0.564) in PLCO. Besides, smokers in the intermediate risk group predicted by the clinical risk model (1.34%-1.51%) with the intermediate-high genetic risk had a 6-year average absolute lung cancer risk that exceeded the clinical risk model threshold (≥1.51%). The addition of metaPRS to the clinical risk model showed continuous net reclassification improvement (continuous NRI = 6.50%) in PLCO. These findings suggest the metaPRS can improve the predictive efficiency of lung cancer compared with the previous PRSs and refine risk stratification for lung cancer.

The Potential of Using Screening Tools for Bipolar Disorder to Predict Lithium Response

Background/Objectives: Lithium is the gold standard for treating Bipolar Disorder (BD), but its effectiveness varies widely. While clinical and environmental factors may influence response, it remains unclear if screening tools can reliably predict lithium response outcomes. This study explores this potential using two widely used screening instruments for BD. Methods: A total of 146 patients with BD were evaluated. Lithium response was assessed using the Alda Scale, while hypomanic and manic symptoms were characterized through the Hypomania Checklist-32 (HCL-32) and the Mood Disorder Questionnaire (MDQ). Group differences in HCL-32 and MDQ scores were analyzed using ANOVA, and a multivariate model was employed to identify predictors of lithium response. Results: Of the total sample, 46 (31.5%) patients were identified as lithium responders based on the Alda Scale. Responders exhibited significantly higher HCL-32 scores compared to non-responders (p = 0.023), while no differences were observed in MDQ scores or other sociodemographic characteristics. Linear regression analysis revealed that HCL-32 scores were a significant predictor of Alda Scale scores, with no associations found for age, gender, or MDQ scores. Conclusions: Our study underscores the importance of considering hypomanic symptoms when estimating lithium response in BD, particularly by utilizing the HCL-32 during screening.

The Nature of the Familial Risk for Psychosis in Bipolar Disorder

BACKGROUND AND HYPOTHESIS

To clarify whether the familial liability to psychosis associated with bipolar disorder (BD) is nonspecific or has a greater effect on risk for psychosis in cases with prominent mood symptoms and/or a remitting course.

STUDY DESIGN

We examined, in 984 809 offspring raised in intact families in Sweden, born 1980-1996 and followed-up through 2018, by multivariable Cox proportional hazards regression, risk in offspring of parents with BD for 7 psychotic disorders: Psychotic MD (PMD), psychotic BD (PBD), schizoaffective disorder (SAD), acute psychoses, psychosis NOS, delusional disorder (DD) and schizophrenia (SZ). Diagnoses were obtained from national registers.

STUDY RESULTS

In the offspring of BD parents, the hazard ratios (HR) for these 7 disorders formed an inverted U-shaped curve, rising from 2.98 for PMD, to peak at 4.49 for PBD and 5.25 for SAD, and then declining to a HR of 3.48 for acute psychoses and 3.22 for psychosis NOS, to a low of 2.19 for DD and 2.33 for SZ. A similar pattern of risks was seen in offspring of mothers and fathers affected with BD and in offspring predicted from age at onset in their BD parent.

CONCLUSIONS

The BD-associated risk for psychosis impacts most strongly on mood disorders, moderately on episodic psychotic syndromes, and least on chronic psychotic disorders. These results support prior clinical studies suggesting a qualitative difference in the familial substrate for psychosis occurring in BD and SZ.

Polygenic Risk Scores for Bipolar Disorder: Progress and Perspectives

Bipolar disorder (BD) is a common and highly heritable psychiatric disorder, the study of BD genetic characteristics can help with early prevention and individualized treatment. At the same time, BD is a highly heterogeneous polygenic genetic disorder with significant genetic overlap with other psychiatric disorders. In recent years, polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) data have been widely used in genetic studies of various complex diseases and can be used to explore the genetic susceptibility of diseases. This review discusses phenotypic associations and genetic correlations with other conditions of BD based on PRS, and provides ideas for genetic studies and prevention of BD.

Multi-PGS enhances polygenic prediction by combining 937 polygenic scores

The predictive performance of polygenic scores (PGS) is largely dependent on the number of samples available to train the PGS. Increasing the sample size for a specific phenotype is expensive and takes time, but this sample size can be effectively increased by using genetically correlated phenotypes. We propose a framework to generate multi-PGS from thousands of publicly available genome-wide association studies (GWAS) with no need to individually select the most relevant ones. In this study, the multi-PGS framework increases prediction accuracy over single PGS for all included psychiatric disorders and other available outcomes, with prediction R2 increases of up to 9-fold for attention-deficit/hyperactivity disorder compared to a single PGS. We also generate multi-PGS for phenotypes without an existing GWAS and for case-case predictions. We benchmark the multi-PGS framework against other methods and highlight its potential application to new emerging biobanks.