Heritability, phenotypic, and genetic correlations across dimensional and categorical models of bipolar disorder in a family sample.

Background: Bipolar disorder (BD) presents with a wide range of symptoms that vary among relatives, casting doubt on categorical illness models. To address this uncertainty, we investigated the heritability and genetic relationships between categorical and dimensional models of BD in a family sample.

Methods: This retrospective study included participants (n = 397 Females, n = 329 Males, mean age 47 yr) in the Amish-Mennonite Bipolar Genetics (AMBiGen) study from North and South America that were assigned categorical mood disorder diagnoses ("narrow" or "broad") by structured psychiatric interview and completed the Mood Disorder Questionnaire (MDQ), which assesses lifetime history of manic symptoms and associated impairment.

Patient Perceptions of Penicillin Allergy Testing in a Public Health System.

Background: Documented penicillin allergies are associated with increased morbidity, increased hospital stay, and an increase in resistant infections. Penicillin allergy evaluations using a direct oral challenge with or without skin testing has been recommended as a delabeling strategy for patients with penicillin reaction histories. Barriers for achieving equitable access, however, exist.

Independent inheritance of cognition and bipolar disorder in a family sample.

Cognitive deficits in people with bipolar disorder (BD) may be the result of the illness or its treatment, but they could also reflect genetic risk factors shared between BD and cognition. We investigated this question using empirical genetic relationships within a sample of patients with BD and their unaffected relatives. Participants with bipolar I, II, or schizoaffective disorder ("narrow" BD, n = 69), related mood disorders ("broad" BD, n = 135), and their clinically unaffected relatives (n = 227) completed five cognitive tests.

A resource of induced pluripotent stem cell (iPSC) lines including clinical, genomic, and cellular data from genetically isolated families with mood and psychotic disorders.

Genome-wide (GWAS) and copy number variant (CNV) association studies have reproducibly identified numerous risk alleles associated with bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ), but biological characterization of these alleles lags gene discovery, owing to the inaccessibility of live human brain cells and inadequate animal models for human psychiatric conditions. Human-derived induced pluripotent stem cells (iPSCs) provide a renewable cellular reagent that can be differentiated into living, disease-relevant cells and 3D brain organoids carrying the full complement of genetic variants present in the donor germline. Experimental studies of iPSC-derived cells allow functional characterization of risk alleles, establishment of causal relationships between genes and neurobiology, and screening for novel therapeutics.

Lithium Response in Bipolar Disorder is Associated with Focal Adhesion and PI3K-Akt Networks: A Multi-omics Replication Study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium.

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores.

Strong Genetic Overlaps Between Dimensional and Categorical Models of Bipolar Disorders in a Family Sample.

Background: Bipolar disorder (BD) presents with a wide range of symptoms that vary among relatives, casting doubt on categorical illness models. To address this uncertainly, we investigated the heritability and genetic relationships between categorical and dimensional models of BD in a family sample.

Methods: Participants in the Amish-Mennonite Bipolar Genetics (AMBiGen) study were assigned categorical mood disorder diagnoses by structured psychiatric interview and completed the Mood Disorder Questionnaire (MDQ), which assesses lifetime history of manic symptoms and associated impairment.

Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores.

Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study.

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients ( = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score.

Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach.

Background: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

Aims: To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients.

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes.

HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders.

Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region.

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder.

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLiGen) study.

Validity of the Mood Disorder Questionnaire (MDQ) as a screening tool for bipolar spectrum disorders in anabaptist populations.

The Mood Disorder Questionnaire (MDQ) is an established screening tool for bipolar spectrum disorders (BSD), but has not been validated in diverse populations and the best scoring method remains uncertain. This study assessed diagnostic validity of the MDQ among Anabaptists, an underserved population frequently involved in genetic research. 161 participants completed the MDQ and were diagnosed by a best-estimate final diagnosis (BEFD).

Early-Onset Osteoarthritis originates at the chondrocyte level in Hip Dysplasia.

Subjects with developmental dysplasia of the hip (DDH) often show early-onset osteoarthritis (OA); however, the molecular mechanisms underlying this pathology are not known. We investigated whether cellular changes in chondrocytes from OA cartilage can be detected in chondrocytes from DDH cartilage before histological manifestations of degeneration. We characterized undamaged and damaged articular cartilage from 22 participants having hip replacement surgery with and without DDH (9 DDH-OA, 12 OA-only, one femoral fracture).

Is Routine Hardware Removal Following Open Reduction Internal Fixation of Tarsometatarsal Joint Fracture/Dislocation Necessary?

Open reduction internal fixation (ORIF) is an accepted treatment for displaced tarsometatarsal joint (TMTJ) fracture dislocations. In general, hardware is routinely removed after 4 months to allow restoration of joint motion and avoid complications of hardware failure. Because few studies report outcomes of TMTJ fractures with retained hardware, there is little consensus regarding the optimal time for hardware removal or if hardware retention leads to adverse outcomes.

Detecting significant genotype-phenotype association rules in bipolar disorder: market research meets complex genetics.

Background: Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive.