Re-evaluating classical body type theories: genetic correlation between psychiatric disorders and body mass index

Ikeda, Masashi; Tanaka, Satoshi; Takeo, Satoshi; Ozaki, Norio; Kamatani, Yoichiro; Iwata, Nakao

doi:10.1017/s0033291718000685

Cited by 21 publications

(17 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Over the course of illness, most patients with BD and psychosis gain weight, which contributes to morbidity and mortality 56 , 57 . Our finding that BD patients with psychosis have lower genetic predisposition to elevated BMI than BD patients without psychosis suggest that weight gain in those with psychosis may be a side effect of medications, which is in line with historic observations predating discovery of antipsychotic medications 58 . However, the complex relationship between BD and greater body weight needs to be further explored in the context of sub-phenotypes and use of atypical antispychotics or lithium.…”

Section: Discussionsupporting

confidence: 87%

Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores

et al. 2020

View full text Add to dashboard Cite

Bipolar disorder (BD) has high clinical heterogeneity, frequent psychiatric comorbidities, and elevated suicide risk. To determine genetic differences between common clinical sub-phenotypes of BD, we performed a systematic polygenic risk score (PRS) analysis using multiple PRSs from a range of psychiatric, personality, and lifestyle traits to dissect differences in BD sub-phenotypes in two BD cohorts: the Mayo Clinic BD Biobank (N = 968) and Genetic Association Information Network (N = 1001). Participants were assessed for history of psychosis, early-onset BD, rapid cycling (defined as four or more episodes in a year), and suicide attempts using questionnaires and the Structured Clinical Interview for DSM-IV. In a combined sample of 1969 bipolar cases (45.5% male), those with psychosis had higher PRS for SCZ (OR = 1.3 per S.D.; p = 3e-5) but lower PRSs for anhedonia (OR = 0.87; p = 0.003) and BMI (OR = 0.87; p = 0.003). Rapid cycling cases had higher PRS for ADHD (OR = 1.23; p = 7e-5) and MDD (OR = 1.23; p = 4e-5) and lower BD PRS (OR = 0.8; p = 0.004). Cases with a suicide attempt had higher PRS for MDD (OR = 1.26; p = 1e-6) and anhedonia (OR = 1.22; p = 2e-5) as well as lower PRS for educational attainment (OR = 0.87; p = 0.003). The observed novel PRS associations with sub-phenotypes align with clinical observations such as rapid cycling BD patients having a greater lifetime prevalence of ADHD. Our findings confirm that genetic heterogeneity contributes to clinical heterogeneity of BD and consideration of genetic contribution to psychopathologic components of psychiatric disorders may improve genetic prediction of complex psychiatric disorders.

show abstract

Section: Discussionsupporting

confidence: 87%

Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Japanese researchers using a genetic method of analysis tested the accuracy of historical concepts proposed by Kretschmer and Shelden, regarding the compliance of somatotypes with certain mental illnesses. There is a significant correlation between the risk of schizophrenia and a low human body mass index, a positive correlation between the human body mass index and the risk of depressive disorders, and the lack of association between bipolar disorder and body mass index [14].…”

Section: Discussionmentioning

confidence: 99%

Correlations of body structure and size indicators with personality indicators of practically healthy women with mesomorphic somatotype

Andriievskyi

Serebrennikova

Kyrychenko

et al. 2020

Biomed. and Biosoc. Anthrop.

View full text Add to dashboard Cite

The category of personality is one of the basic concepts for psychology, but at the same time the most controversial in theoretical and methodological terms. That is why the study of personal characteristics in different populations, ethnicities, ages, professional groups, etc. still does not lose its relevance in the scientific field. Given that certain components of individual personality traits are innate, it is advisable to find connections between them and the characteristics of the human body. The purpose of the work is to determine and analyze the peculiarities of correlations between indicators of body structure and size and personality indicators of practically healthy women with mesomorphic somatotype. Primary anthropo-somatotypological and personality indicators of 33 practically healthy Ukrainian women of the first mature age of mesomorphic somatotype were selected from the data bank of materials of the research center of National Pirogov Memorial Medical University, Vinnytsya. The analysis of correlations between anthropo-somatotypological and indicators of personality traits was performed in the licensed package "Statistica 6.1" using the non-parametric Spearman's method. Multiple, mostly reliable, medium-strength straight lines (r = -0.35 to -0.50), Eysenck G. insincerity scales with the majority of girth dimensions, thickness of skin and fat folds, somatotype components, and body weight component composition; multiple, mostly significant medium-strength inverse (r = -0.37 to -0.52) correlations of the exaltation character of the exalted type according to Shmishek G. with the majority of girth dimensions, the majority of pelvic sizes, somatotype components and components of body weight composition; multiple significant mean strength inverse (r = -0.38 to -0.49) correlations of the extraversion-introversion scale according to Eysenck G. with the thickness of the skin and fat folds of the upper limb and under the shoulder blade. In other cases, single, medium-strength, reliable and unreliable direct and inverse correlations of anthropo-somatotypological indicators with the leading typological characteristics of temperament, psychodynamic features of personality and indicators of severity and features of accentuated personality traits. As a result of quantitative analysis of reliable and unreliable average correlations of anthropo-somatotypological indicators with personality traits of practically healthy women of mesomorphic somatotype, the highest relative percentage of correlations was found between: leading typological characteristics of temperament according to Eysenck G. and somatotype components body weight composition and body girth; psychodynamic personality traits according to Spielberger C. D. and longitudinal body size, thickness of skin and fat folds and components of the somatotype; indicators of severity and features of accentuated personality traits according to Shmishek G. and indicators of the component composition of body weight, somatotype components, body circumference and thickness of skin and fat folds; indicators of the level of subjective control over Rotter J. and the width of the distal epiphyses of the extremities and the transverse dimensions of the body.

show abstract

“…Specifically, INO80E was associated with both schizophrenia and BMI, and SPN was associated with both BMI and IQ. Genetic correlations of at least -0.05 and as much as -0.5 have been estimated for the BMI/IQ and SCZ/BMI pairs, suggesting that pleiotropy may play a general role in these disorders [102][103][104][105] . Consistent with the genetic correlations, most (8/12) eQTL SNPs in our prediction models for SPN drove the associations with both IQ and BMI.…”

Section: Spn a Gene Highly Associated With Both Iq And Bmi Is Activmentioning

confidence: 99%

Integration of genetic, transcriptomic, and clinical data provides insight into 16p11.2 and 22q11.2 CNV genes

Vysotskiy

Zhong

Zhou

et al. 2020

Preprint

View full text Add to dashboard Cite

Deletions and duplications of the 16p11.2 and 22q11.2 copy number variant (CNV) regions are associated with brain-related disorders including autism spectrum disorder, schizophrenia, bipolar disorder, obesity, and intellectual disability. The contribution of individual genes in each CNV to each phenotype is unknown. We propose a novel in silico approach to systematically interrogate each gene's effect on brain-related disorders. As CNVs affect RNA copy number, we attempted to fine-map each CNV region by asking whether natural gene expression variation in any individual gene would increase risk for the same disorder(s). We first used large genotyped cohorts for five CNV-associated traits: autism spectrum disorder, schizophrenia, bipolar disorder, BMI, and IQ. Imputing the transcriptome from the genome, we performed association testing for CNV genes with the genotype datasets. We found individual genes within 16p11.2 associated with schizophrenia (TMEM219, INO80E, YPEL3), BMI (TMEM219, SPN, TAOK2, INO80E), and IQ (SPN), with independent replication. Using a conditional analysis, we showed that INO80E explains the schizophrenia association. Second, we used a biobank containing electronic health data and genotypes for 23,000 individuals to perform phenome-wide association studies with predicted expressions of 16p11.2 and 22q11.2 genes and over 1,500 health traits, finding eight significant gene-trait pairs. Third, we compared the medical phenome of CNV carriers to controls within an independent group of 3 million individuals. We identified CNV traits may have indicated genetic testing, other traits previously observed in CNV carriers, and novel traits. Our results provide new insight into the contribution of individual CNV genes to CNV-associated traits. Limitations

show abstract

Re-evaluating classical body type theories: genetic correlation between psychiatric disorders and body mass index

Cited by 21 publications

References 17 publications

Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores

Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores

Correlations of body structure and size indicators with personality indicators of practically healthy women with mesomorphic somatotype

Integration of genetic, transcriptomic, and clinical data provides insight into 16p11.2 and 22q11.2 CNV genes

Contact Info

Product

Resources

About